import os
import pandas as pd
from google.colab import auth
from datetime import datetime
auth.authenticate_user()
!gcloud source repos clone github_aistream-peelout_flow-forecast --project=gmap-997
os.chdir('/content/github_aistream-peelout_flow-forecast')
!git checkout -t origin/covid_fixes
!python setup.py develop
!pip install -r requirements.txt
!mkdir data
from flood_forecast.trainer import train_function
!pip install git+https://github.com/CoronaWhy/task-geo.git
!wandb login
WARNING: Repository "github_aistream-peelout_flow-forecast" in project "gmap-997" is a mirror. Pushing to this clone will have no effect. Instead, clone the mirrored repository directly with $ git clone https://github.com/AIStream-Peelout/flow-forecast Cloning into '/content/github_aistream-peelout_flow-forecast'... remote: Total 3703 (delta 2463), reused 3703 (delta 2463) Receiving objects: 100% (3703/3703), 2.63 MiB | 13.23 MiB/s, done. Resolving deltas: 100% (2463/2463), done. Project [gmap-997] repository [github_aistream-peelout_flow-forecast] was cloned to [/content/github_aistream-peelout_flow-forecast]. Branch 'covid_fixes' set up to track remote branch 'covid_fixes' from 'origin'. Switched to a new branch 'covid_fixes' /usr/local/lib/python3.6/dist-packages/setuptools/dist.py:454: UserWarning: Normalizing '0.01dev' to '0.1.dev0' warnings.warn(tmpl.format(**locals())) running develop running egg_info creating flood_forecast.egg-info writing flood_forecast.egg-info/PKG-INFO writing dependency_links to flood_forecast.egg-info/dependency_links.txt writing requirements to flood_forecast.egg-info/requires.txt writing top-level names to flood_forecast.egg-info/top_level.txt writing manifest file 'flood_forecast.egg-info/SOURCES.txt' package init file 'flood_forecast/__init__.py' not found (or not a regular file) package init file 'flood_forecast/transformer_xl/__init__.py' not found (or not a regular file) package init file 'flood_forecast/preprocessing/__init__.py' not found (or not a regular file) package init file 'flood_forecast/da_rnn/__init__.py' not found (or not a regular file) package init file 'flood_forecast/basic/__init__.py' not found (or not a regular file) package init file 'flood_forecast/custom/__init__.py' not found (or not a regular file) writing manifest file 'flood_forecast.egg-info/SOURCES.txt' running build_ext Creating /usr/local/lib/python3.6/dist-packages/flood-forecast.egg-link (link to .) Adding flood-forecast 0.1.dev0 to easy-install.pth file Installed /content/github_aistream-peelout_flow-forecast Processing dependencies for flood-forecast==0.1.dev0 Searching for google-cloud Reading https://pypi.org/simple/google-cloud/ Downloading https://files.pythonhosted.org/packages/ba/b1/7c54d1950e7808df06642274e677dbcedba57f75307adf2e5ad8d39e5e0e/google_cloud-0.34.0-py2.py3-none-any.whl#sha256=fb1ab7b0548fe44b3d538041f0a374505b7f990d448a935ea36649c5ccab5acf Best match: google-cloud 0.34.0 Processing google_cloud-0.34.0-py2.py3-none-any.whl Installing google_cloud-0.34.0-py2.py3-none-any.whl to /usr/local/lib/python3.6/dist-packages Adding google-cloud 0.34.0 to easy-install.pth file Installed /usr/local/lib/python3.6/dist-packages/google_cloud-0.34.0-py3.6.egg Searching for pandas==1.0.3 Best match: pandas 1.0.3 Adding pandas 1.0.3 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for tensorflow==2.2.0rc4 Best match: tensorflow 2.2.0rc4 Adding tensorflow 2.2.0rc4 to easy-install.pth file Installing estimator_ckpt_converter script to /usr/local/bin Installing saved_model_cli script to /usr/local/bin Installing tensorboard script to /usr/local/bin Installing tf_upgrade_v2 script to /usr/local/bin Installing tflite_convert script to /usr/local/bin Installing toco script to /usr/local/bin Installing toco_from_protos script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for torch==1.5.0+cu101 Best match: torch 1.5.0+cu101 Adding torch 1.5.0+cu101 to easy-install.pth file Installing convert-caffe2-to-onnx script to /usr/local/bin Installing convert-onnx-to-caffe2 script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for scikit-learn==0.22.2.post1 Best match: scikit-learn 0.22.2.post1 Adding scikit-learn 0.22.2.post1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for python-dateutil==2.8.1 Best match: python-dateutil 2.8.1 Adding python-dateutil 2.8.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for numpy==1.18.4 Best match: numpy 1.18.4 Adding numpy 1.18.4 to easy-install.pth file Installing f2py script to /usr/local/bin Installing f2py3 script to /usr/local/bin Installing f2py3.6 script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for pytz==2018.9 Best match: pytz 2018.9 Adding pytz 2018.9 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for wrapt==1.12.1 Best match: wrapt 1.12.1 Adding wrapt 1.12.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for wheel==0.34.2 Best match: wheel 0.34.2 Adding wheel 0.34.2 to easy-install.pth file Installing wheel script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for h5py==2.10.0 Best match: h5py 2.10.0 Adding h5py 2.10.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for six==1.12.0 Best match: six 1.12.0 Adding six 1.12.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for absl-py==0.9.0 Best match: absl-py 0.9.0 Adding absl-py 0.9.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for Keras-Preprocessing==1.1.0 Best match: Keras-Preprocessing 1.1.0 Adding Keras-Preprocessing 1.1.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for google-pasta==0.2.0 Best match: google-pasta 0.2.0 Adding google-pasta 0.2.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for scipy==1.4.1 Best match: scipy 1.4.1 Adding scipy 1.4.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for gast==0.3.3 Best match: gast 0.3.3 Adding gast 0.3.3 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for opt-einsum==3.2.1 Best match: opt-einsum 3.2.1 Adding opt-einsum 3.2.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for protobuf==3.10.0 Best match: protobuf 3.10.0 Adding protobuf 3.10.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for grpcio==1.28.1 Best match: grpcio 1.28.1 Adding grpcio 1.28.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for tensorflow-estimator==2.2.0 Best match: tensorflow-estimator 2.2.0 Adding tensorflow-estimator 2.2.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for tensorboard==2.2.1 Best match: tensorboard 2.2.1 Adding tensorboard 2.2.1 to easy-install.pth file Installing tensorboard script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for astunparse==1.6.3 Best match: astunparse 1.6.3 Adding astunparse 1.6.3 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for termcolor==1.1.0 Best match: termcolor 1.1.0 Adding termcolor 1.1.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for future==0.16.0 Best match: future 0.16.0 Adding future 0.16.0 to easy-install.pth file Installing futurize script to /usr/local/bin Installing pasteurize script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for joblib==0.14.1 Best match: joblib 0.14.1 Adding joblib 0.14.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for setuptools==46.1.3 Best match: setuptools 46.1.3 Adding setuptools 46.1.3 to easy-install.pth file Installing easy_install script to /usr/local/bin Installing easy_install-3.8 script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for Werkzeug==1.0.1 Best match: Werkzeug 1.0.1 Adding Werkzeug 1.0.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for google-auth==1.7.2 Best match: google-auth 1.7.2 Adding google-auth 1.7.2 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for google-auth-oauthlib==0.4.1 Best match: google-auth-oauthlib 0.4.1 Adding google-auth-oauthlib 0.4.1 to easy-install.pth file Installing google-oauthlib-tool script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for Markdown==3.2.1 Best match: Markdown 3.2.1 Adding Markdown 3.2.1 to easy-install.pth file Installing markdown_py script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for tensorboard-plugin-wit==1.6.0.post3 Best match: tensorboard-plugin-wit 1.6.0.post3 Adding tensorboard-plugin-wit 1.6.0.post3 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for requests==2.23.0 Best match: requests 2.23.0 Adding requests 2.23.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for cachetools==3.1.1 Best match: cachetools 3.1.1 Adding cachetools 3.1.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for rsa==4.0 Best match: rsa 4.0 Adding rsa 4.0 to easy-install.pth file Installing pyrsa-decrypt script to /usr/local/bin Installing pyrsa-encrypt script to /usr/local/bin Installing pyrsa-keygen script to /usr/local/bin Installing pyrsa-priv2pub script to /usr/local/bin Installing pyrsa-sign script to /usr/local/bin Installing pyrsa-verify script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for pyasn1-modules==0.2.8 Best match: pyasn1-modules 0.2.8 Adding pyasn1-modules 0.2.8 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for requests-oauthlib==1.3.0 Best match: requests-oauthlib 1.3.0 Adding requests-oauthlib 1.3.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for chardet==3.0.4 Best match: chardet 3.0.4 Adding chardet 3.0.4 to easy-install.pth file Installing chardetect script to /usr/local/bin Using /usr/local/lib/python3.6/dist-packages Searching for urllib3==1.24.3 Best match: urllib3 1.24.3 Adding urllib3 1.24.3 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for idna==2.9 Best match: idna 2.9 Adding idna 2.9 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for certifi==2020.4.5.1 Best match: certifi 2020.4.5.1 Adding certifi 2020.4.5.1 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for pyasn1==0.4.8 Best match: pyasn1 0.4.8 Adding pyasn1 0.4.8 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Searching for oauthlib==3.1.0 Best match: oauthlib 3.1.0 Adding oauthlib 3.1.0 to easy-install.pth file Using /usr/local/lib/python3.6/dist-packages Finished processing dependencies for flood-forecast==0.1.dev0 Requirement already satisfied: scikit-learn in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 1)) (0.22.2.post1) Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 2)) (1.0.3) Requirement already satisfied: torch in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 3)) (1.5.0+cu101) Collecting tb-nightly Downloading https://files.pythonhosted.org/packages/ba/68/c413fa084dfcb95cb1b3fe9ea9d9de072e6c4acac3c3763a0ce50e1d8daf/tb_nightly-2.3.0a20200509-py3-none-any.whl (2.9MB) |████████████████████████████████| 3.0MB 3.5MB/s Requirement already satisfied: seaborn in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 5)) (0.10.1) Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 6)) (0.16.0) Collecting wandb Downloading https://files.pythonhosted.org/packages/2d/c9/ebbcefa6ef2ba14a7c62a4ee4415a5fecef8fac5e4d1b4e22af26fd9fe22/wandb-0.8.35-py2.py3-none-any.whl (1.4MB) |████████████████████████████████| 1.4MB 47.1MB/s Requirement already satisfied: pandas_gbq in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 8)) (0.11.0) Requirement already satisfied: google-cloud in /usr/local/lib/python3.6/dist-packages/google_cloud-0.34.0-py3.6.egg (from -r requirements.txt (line 9)) (0.34.0) Requirement already satisfied: google-cloud-storage in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 10)) (1.18.1) Requirement already satisfied: pyyaml in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 11)) (3.13) Requirement already satisfied: plotly in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 12)) (4.4.1) Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->-r requirements.txt (line 1)) (0.14.1) Requirement already satisfied: numpy>=1.11.0 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->-r requirements.txt (line 1)) (1.18.4) Requirement already satisfied: scipy>=0.17.0 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->-r requirements.txt (line 1)) (1.4.1) Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas->-r requirements.txt (line 2)) (2018.9) Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas->-r requirements.txt (line 2)) (2.8.1) Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (2.23.0) Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (3.2.1) Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (0.4.1) Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.12.0) Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.6.0.post3) Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (46.1.3) Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.7.2) Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.0.1) Requirement already satisfied: wheel>=0.26; python_version >= "3" in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (0.34.2) Requirement already satisfied: protobuf>=3.6.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (3.10.0) Requirement already satisfied: grpcio>=1.24.3 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.28.1) Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (0.9.0) Requirement already satisfied: matplotlib>=2.1.2 in /usr/local/lib/python3.6/dist-packages (from seaborn->-r requirements.txt (line 5)) (3.2.1) Collecting gql==0.2.0 Downloading https://files.pythonhosted.org/packages/c4/6f/cf9a3056045518f06184e804bae89390eb706168349daa9dff8ac609962a/gql-0.2.0.tar.gz Collecting sentry-sdk>=0.4.0 Downloading https://files.pythonhosted.org/packages/20/7e/19545324e83db4522b885808cd913c3b93ecc0c88b03e037b78c6a417fa8/sentry_sdk-0.14.3-py2.py3-none-any.whl (103kB) |████████████████████████████████| 112kB 43.1MB/s Requirement already satisfied: psutil>=5.0.0 in /usr/local/lib/python3.6/dist-packages (from wandb->-r requirements.txt (line 7)) (5.4.8) Requirement already satisfied: nvidia-ml-py3>=7.352.0 in /usr/local/lib/python3.6/dist-packages (from wandb->-r requirements.txt (line 7)) (7.352.0) Collecting shortuuid>=0.5.0 Downloading https://files.pythonhosted.org/packages/25/a6/2ecc1daa6a304e7f1b216f0896b26156b78e7c38e1211e9b798b4716c53d/shortuuid-1.0.1-py3-none-any.whl Collecting configparser>=3.8.1 Downloading https://files.pythonhosted.org/packages/4b/6b/01baa293090240cf0562cc5eccb69c6f5006282127f2b846fad011305c79/configparser-5.0.0-py3-none-any.whl Collecting subprocess32>=3.5.3 Downloading https://files.pythonhosted.org/packages/32/c8/564be4d12629b912ea431f1a50eb8b3b9d00f1a0b1ceff17f266be190007/subprocess32-3.5.4.tar.gz (97kB) |████████████████████████████████| 102kB 9.5MB/s Collecting watchdog>=0.8.3 Downloading https://files.pythonhosted.org/packages/73/c3/ed6d992006837e011baca89476a4bbffb0a91602432f73bd4473816c76e2/watchdog-0.10.2.tar.gz (95kB) |████████████████████████████████| 102kB 10.2MB/s Collecting docker-pycreds>=0.4.0 Downloading https://files.pythonhosted.org/packages/f5/e8/f6bd1eee09314e7e6dee49cbe2c5e22314ccdb38db16c9fc72d2fa80d054/docker_pycreds-0.4.0-py2.py3-none-any.whl Requirement already satisfied: Click>=7.0 in /usr/local/lib/python3.6/dist-packages (from wandb->-r requirements.txt (line 7)) (7.1.2) Collecting GitPython>=1.0.0 Downloading https://files.pythonhosted.org/packages/44/33/917e6fde1cad13daa7053f39b7c8af3be287314f75f1b1ea8d3fe37a8571/GitPython-3.1.2-py3-none-any.whl (451kB) |████████████████████████████████| 460kB 45.8MB/s Requirement already satisfied: pydata-google-auth in /usr/local/lib/python3.6/dist-packages (from pandas_gbq->-r requirements.txt (line 8)) (1.1.0) Requirement already satisfied: google-cloud-bigquery>=1.9.0 in /usr/local/lib/python3.6/dist-packages (from pandas_gbq->-r requirements.txt (line 8)) (1.21.0) Requirement already satisfied: google-cloud-core<2.0dev,>=1.0.0 in /usr/local/lib/python3.6/dist-packages (from google-cloud-storage->-r requirements.txt (line 10)) (1.0.3) Requirement already satisfied: google-resumable-media<0.5.0dev,>=0.3.1 in /usr/local/lib/python3.6/dist-packages (from google-cloud-storage->-r requirements.txt (line 10)) (0.4.1) Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.6/dist-packages (from plotly->-r requirements.txt (line 12)) (1.3.3) Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly->-r requirements.txt (line 4)) (2.9) Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly->-r requirements.txt (line 4)) (1.24.3) Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly->-r requirements.txt (line 4)) (3.0.4) Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly->-r requirements.txt (line 4)) (2020.4.5.1) Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tb-nightly->-r requirements.txt (line 4)) (1.3.0) Requirement already satisfied: cachetools<3.2,>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tb-nightly->-r requirements.txt (line 4)) (3.1.1) Requirement already satisfied: rsa<4.1,>=3.1.4 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tb-nightly->-r requirements.txt (line 4)) (4.0) Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tb-nightly->-r requirements.txt (line 4)) (0.2.8) Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.1.2->seaborn->-r requirements.txt (line 5)) (1.2.0) Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.1.2->seaborn->-r requirements.txt (line 5)) (2.4.7) Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.1.2->seaborn->-r requirements.txt (line 5)) (0.10.0) Collecting graphql-core<2,>=0.5.0 Downloading https://files.pythonhosted.org/packages/b0/89/00ad5e07524d8c523b14d70c685e0299a8b0de6d0727e368c41b89b7ed0b/graphql-core-1.1.tar.gz (70kB) |████████████████████████████████| 71kB 7.2MB/s Requirement already satisfied: promise<3,>=2.0 in /usr/local/lib/python3.6/dist-packages (from gql==0.2.0->wandb->-r requirements.txt (line 7)) (2.3) Collecting pathtools>=0.1.1 Downloading https://files.pythonhosted.org/packages/e7/7f/470d6fcdf23f9f3518f6b0b76be9df16dcc8630ad409947f8be2eb0ed13a/pathtools-0.1.2.tar.gz Collecting gitdb<5,>=4.0.1 Downloading https://files.pythonhosted.org/packages/48/11/d1800bca0a3bae820b84b7d813ad1eff15a48a64caea9c823fc8c1b119e8/gitdb-4.0.5-py3-none-any.whl (63kB) |████████████████████████████████| 71kB 5.7MB/s Requirement already satisfied: google-api-core<2.0.0dev,>=1.14.0 in /usr/local/lib/python3.6/dist-packages (from google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->-r requirements.txt (line 10)) (1.16.0) Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tb-nightly->-r requirements.txt (line 4)) (3.1.0) Requirement already satisfied: pyasn1>=0.1.3 in /usr/local/lib/python3.6/dist-packages (from rsa<4.1,>=3.1.4->google-auth<2,>=1.6.3->tb-nightly->-r requirements.txt (line 4)) (0.4.8) Collecting smmap<4,>=3.0.1 Downloading https://files.pythonhosted.org/packages/b0/9a/4d409a6234eb940e6a78dfdfc66156e7522262f5f2fecca07dc55915952d/smmap-3.0.4-py2.py3-none-any.whl Requirement already satisfied: googleapis-common-protos<2.0dev,>=1.6.0 in /usr/local/lib/python3.6/dist-packages (from google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->-r requirements.txt (line 10)) (1.51.0) Building wheels for collected packages: gql, subprocess32, watchdog, graphql-core, pathtools Building wheel for gql (setup.py) ... done Created wheel for gql: filename=gql-0.2.0-cp36-none-any.whl size=7630 sha256=efdb6942864b790a728bf5da03b8f5217618c33f4db086398a4e65c0702548c9 Stored in directory: /root/.cache/pip/wheels/ce/0e/7b/58a8a5268655b3ad74feef5aa97946f0addafb3cbb6bd2da23 Building wheel for subprocess32 (setup.py) ... done Created wheel for subprocess32: filename=subprocess32-3.5.4-cp36-none-any.whl size=6489 sha256=5ad23f1ec1134b6b82eca206bdd195eeedf3fab18493700cff5834ff8ee37041 Stored in directory: /root/.cache/pip/wheels/68/39/1a/5e402bdfdf004af1786c8b853fd92f8c4a04f22aad179654d1 Building wheel for watchdog (setup.py) ... done Created wheel for watchdog: filename=watchdog-0.10.2-cp36-none-any.whl size=73605 sha256=4f13410c32204b416349c9f898ad95f5a3c89ff1b3e07d3724dfd9de0898886c Stored in directory: /root/.cache/pip/wheels/bc/ed/6c/028dea90d31b359cd2a7c8b0da4db80e41d24a59614154072e Building wheel for graphql-core (setup.py) ... done Created wheel for graphql-core: filename=graphql_core-1.1-cp36-none-any.whl size=104650 sha256=990e5fb8fe2bece99f37b18a8bcc3ebe91f66b477f239cae3791e95b2058d7df Stored in directory: /root/.cache/pip/wheels/45/99/d7/c424029bb0fe910c63b68dbf2aa20d3283d023042521bcd7d5 Building wheel for pathtools (setup.py) ... done Created wheel for pathtools: filename=pathtools-0.1.2-cp36-none-any.whl size=8784 sha256=1959d68adefe6f08809257d74c1bbe351986b205e7cc04b9ad84ad3e024d075b Stored in directory: /root/.cache/pip/wheels/0b/04/79/c3b0c3a0266a3cb4376da31e5bfe8bba0c489246968a68e843 Successfully built gql subprocess32 watchdog graphql-core pathtools Installing collected packages: tb-nightly, graphql-core, gql, sentry-sdk, shortuuid, configparser, subprocess32, pathtools, watchdog, docker-pycreds, smmap, gitdb, GitPython, wandb Successfully installed GitPython-3.1.2 configparser-5.0.0 docker-pycreds-0.4.0 gitdb-4.0.5 gql-0.2.0 graphql-core-1.1 pathtools-0.1.2 sentry-sdk-0.14.3 shortuuid-1.0.1 smmap-3.0.4 subprocess32-3.5.4 tb-nightly-2.3.0a20200509 wandb-0.8.35 watchdog-0.10.2 Collecting git+https://github.com/CoronaWhy/task-geo.git Cloning https://github.com/CoronaWhy/task-geo.git to /tmp/pip-req-build-xptgbhwy Running command git clone -q https://github.com/CoronaWhy/task-geo.git /tmp/pip-req-build-xptgbhwy Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from task-geo==0.1.0.dev0) (1.0.3) Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from task-geo==0.1.0.dev0) (2.23.0) Requirement already satisfied: jupyter in /usr/local/lib/python3.6/dist-packages (from task-geo==0.1.0.dev0) (1.0.0) Collecting hdx-python-api Downloading https://files.pythonhosted.org/packages/79/32/7033d6d9ff01fd592ec649756f78460dc66640c1001f39c2d421037866f3/hdx_python_api-4.5.8-py2.py3-none-any.whl (67kB) |████████████████████████████████| 71kB 2.3MB/s Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from 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qtconsole->jupyter->task-geo==0.1.0.dev0) (19.0.0) Requirement already satisfied: ipython-genutils in /usr/local/lib/python3.6/dist-packages (from qtconsole->jupyter->task-geo==0.1.0.dev0) (0.2.0) Requirement already satisfied: jupyter-client>=4.1 in /usr/local/lib/python3.6/dist-packages (from qtconsole->jupyter->task-geo==0.1.0.dev0) (5.3.4) Requirement already satisfied: qtpy in /usr/local/lib/python3.6/dist-packages (from qtconsole->jupyter->task-geo==0.1.0.dev0) (1.9.0) Requirement already satisfied: prompt-toolkit<2.0.0,>=1.0.0 in /usr/local/lib/python3.6/dist-packages (from jupyter-console->jupyter->task-geo==0.1.0.dev0) (1.0.18) Requirement already satisfied: tornado>=4.0 in /usr/local/lib/python3.6/dist-packages (from ipykernel->jupyter->task-geo==0.1.0.dev0) (4.5.3) Requirement already satisfied: terminado>=0.3.3; sys_platform != "win32" in /usr/local/lib/python3.6/dist-packages (from notebook->jupyter->task-geo==0.1.0.dev0) (0.8.3) Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from ckanapi>=4.3->hdx-python-api->task-geo==0.1.0.dev0) (46.1.3) Requirement already satisfied: docopt in /usr/local/lib/python3.6/dist-packages (from ckanapi>=4.3->hdx-python-api->task-geo==0.1.0.dev0) (0.6.2) Requirement already satisfied: python-slugify>=1.0 in /usr/local/lib/python3.6/dist-packages (from ckanapi>=4.3->hdx-python-api->task-geo==0.1.0.dev0) (4.0.0) Collecting cryptography>=2.8 Downloading https://files.pythonhosted.org/packages/3c/04/686efee2dcdd25aecf357992e7d9362f443eb182ecd623f882bc9f7a6bba/cryptography-2.9.2-cp35-abi3-manylinux2010_x86_64.whl (2.7MB) |████████████████████████████████| 2.7MB 46.7MB/s Requirement already satisfied: inflect in /usr/local/lib/python3.6/dist-packages (from quantulum3>=0.7.3; python_version >= "3"->hdx-python-api->task-geo==0.1.0.dev0) (2.1.0) Collecting num2words Downloading 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/usr/local/lib/python3.6/dist-packages (from botocore<1.17.0,>=1.16.3->boto3>=1.9->tabulator[cchardet]>=1.42.0->hdx-python-utilities>=2.3.4->hdx-python-country>=2.5.6->hdx-python-api->task-geo==0.1.0.dev0) (0.15.2) Building wheels for collected packages: task-geo, ckanapi, libhxl, python-io-wrapper, jsonpath-rw, sshtunnel, ratelimit, openpyxl, linear-tsv, unicodecsv Building wheel for task-geo (setup.py) ... done Created wheel for task-geo: filename=task_geo-0.1.0.dev0-py2.py3-none-any.whl size=177461 sha256=0715f4a9dc29541d20496dcf78309daca37dcecc0766292fd97b6013d48fc64e Stored in directory: /tmp/pip-ephem-wheel-cache-3sl_wni3/wheels/4f/c4/a4/33f04d80a745ae3ff088cae6f8cda3b46c48e007585d9ff0bf Building wheel for ckanapi (setup.py) ... done Created wheel for ckanapi: filename=ckanapi-4.3-cp36-none-any.whl size=38647 sha256=166b963560cbf1edd246d53404ba0507436fb0958384d80cce630caaf3520117 Stored in directory: /root/.cache/pip/wheels/41/f2/fb/c8ce857007de64cc6b36b8f1048272396bc0817c35ee3a3e73 Building wheel for libhxl (setup.py) ... done Created wheel for libhxl: filename=libhxl-4.19-cp36-none-any.whl size=81540 sha256=309fe0e5b61a416b217a1f4582902f2a769dfcd4a1007f300df360d73256c54b Stored in directory: /root/.cache/pip/wheels/99/4e/75/2c1d5d8cd3c34a42dcd9a388562d3dd3fb2197adbb47e20503 Building wheel for python-io-wrapper (setup.py) ... done Created wheel for python-io-wrapper: filename=python_io_wrapper-0.1-cp36-none-any.whl size=2490 sha256=748d1694385e018f7999b32242ef7889fb519e710fc56845cd660a2eb0db8356 Stored in directory: /root/.cache/pip/wheels/6b/26/be/da3c0a774901c557a0bee985e7aade5b9db75fe4dc8ef99ced Building wheel for jsonpath-rw (setup.py) ... done Created wheel for jsonpath-rw: filename=jsonpath_rw-1.4.0-cp36-none-any.whl size=15146 sha256=d5daeb5cf825d4b7f450ca43c889d1d2ae8c9767d9c5bf70cbe25e44c872a0c9 Stored in directory: /root/.cache/pip/wheels/5c/00/9a/82822db383c2d96dcebf839786665a185f92d37e5026f9806f Building wheel for sshtunnel (setup.py) ... done Created wheel for sshtunnel: filename=sshtunnel-0.1.5-py2.py3-none-any.whl size=23243 sha256=fd7eb4dd7d7fe19108857f707f017972fcbea90a053e1856c4431746003fc41a Stored in directory: /root/.cache/pip/wheels/e8/d2/38/b9791b7391f634099194ec6697fa671194f3353906d94c8f92 Building wheel for ratelimit (setup.py) ... done Created wheel for ratelimit: filename=ratelimit-2.2.1-cp36-none-any.whl size=5893 sha256=89b5a5ec5d39b5432f0338b114fce29ea2e1fb09d7dee74c0547102660f13e89 Stored in directory: /root/.cache/pip/wheels/05/d9/82/3c6044cf1a54aab9151612458446d9b17a38416869e1b1d9b8 Building wheel for openpyxl (setup.py) ... done Created wheel for openpyxl: filename=openpyxl-3.0.3-py2.py3-none-any.whl size=241262 sha256=e8124e8bea3e1eea2ed30c228a40eabb8003d9803813984a602fbde0b46c136f Stored in directory: /root/.cache/pip/wheels/b5/85/ca/e768ac132e57e75e645a151f8badac71cc0089e7225dddf76b Building wheel for linear-tsv (setup.py) ... done Created wheel for linear-tsv: filename=linear_tsv-1.1.0-cp36-none-any.whl size=7383 sha256=8b473779da3f1baccf57e16557a6ca83195947f8f2d7d03b26a3ccd7b7b620f8 Stored in directory: /root/.cache/pip/wheels/3f/8a/cb/38917fd1ef4356b9870ace7331b83417dc594bf2c029bd991f Building wheel for unicodecsv (setup.py) ... done Created wheel for unicodecsv: filename=unicodecsv-0.14.1-cp36-none-any.whl size=10768 sha256=52517a383a97e3efcdf4a77de6f33a714ce97cc4565733dd3d95f67cbb8caa52 Stored in directory: /root/.cache/pip/wheels/a6/09/e9/e800279c98a0a8c94543f3de6c8a562f60e51363ed26e71283 Successfully built task-geo ckanapi libhxl python-io-wrapper jsonpath-rw sshtunnel ratelimit openpyxl linear-tsv unicodecsv ERROR: hdx-python-utilities 2.3.4 has requirement six>=1.14.0, but you'll have six 1.12.0 which is incompatible. Installing collected packages: ckanapi, cryptography, pyOpenSSL, num2words, quantulum3, ndg-httpsclient, unidecode, python-io-wrapper, ply, jsonpath-rw, libhxl, pynacl, bcrypt, paramiko, sshtunnel, ratelimit, basicauth, dnspython, email-validator, psycopg2-binary, yamlloader, openpyxl, linear-tsv, jsonlines, ijson, unicodecsv, cchardet, tabulator, colorlog, pyaml, hdx-python-utilities, hdx-python-country, hdx-python-api, task-geo Found existing installation: openpyxl 2.5.9 Uninstalling openpyxl-2.5.9: Successfully uninstalled openpyxl-2.5.9 Successfully installed basicauth-0.4.1 bcrypt-3.1.7 cchardet-2.1.6 ckanapi-4.3 colorlog-4.1.0 cryptography-2.9.2 dnspython-1.16.0 email-validator-1.1.0 hdx-python-api-4.5.8 hdx-python-country-2.5.6 hdx-python-utilities-2.3.4 ijson-3.0.3 jsonlines-1.2.0 jsonpath-rw-1.4.0 libhxl-4.19 linear-tsv-1.1.0 ndg-httpsclient-0.5.1 num2words-0.5.10 openpyxl-3.0.3 paramiko-2.7.1 ply-3.11 psycopg2-binary-2.8.5 pyOpenSSL-19.1.0 pyaml-20.4.0 pynacl-1.3.0 python-io-wrapper-0.1 quantulum3-0.7.3 ratelimit-2.2.1 sshtunnel-0.1.5 tabulator-1.44.0 task-geo-0.1.0.dev0 unicodecsv-0.14.1 unidecode-1.1.1 yamlloader-0.5.5 wandb: You can find your API key in your browser here: https://app.wandb.ai/authorize wandb: Paste an API key from your profile and hit enter: 936f243deff8f026e476a495792f87a7942c65bf wandb: Appending key for api.wandb.ai to your netrc file: /root/.netrc Successfully logged in to Weights & Biases!
def make_config_file(file_path, df_len, weight_path=None):
run = wandb.init(project="covid-forecast")
wandb_config = wandb.config
train_number = df_len * .7
validation_number = df_len *.9
config_default={
"model_name": "MultiAttnHeadSimple",
"model_type": "PyTorch",
"model_params": {
"number_time_series":3,
"seq_len":wandb_config["forecast_history"],
"output_seq_len":wandb_config["out_seq_length"],
"forecast_length":wandb_config["out_seq_length"]
},
"dataset_params":
{ "class": "default",
"training_path": file_path,
"validation_path": file_path,
"test_path": file_path,
"batch_size":wandb_config["batch_size"],
"forecast_history":wandb_config["forecast_history"],
"forecast_length":wandb_config["out_seq_length"],
"train_end": int(train_number),
"valid_start":int(train_number+1),
"valid_end": int(validation_number),
"target_col": ["new_cases"],
"relevant_cols": ["new_cases", "month", "weekday"],
"scaler": "StandardScaler",
"interpolate": False
},
"training_params":
{
"criterion":"MSE",
"optimizer": wandb_config["optimizer"],
"optim_params":
{
"lr": wandb_config["lr"]
},
"epochs": 10,
"batch_size":wandb_config["batch_size"]
},
"GCS": False,
"sweep":True,
"wandb":False,
"forward_params":{},
"metrics":["MSE"],
"inference_params":
{
"datetime_start":"2020-04-21",
"hours_to_forecast":10,
"test_csv_path":file_path,
"decoder_params":{
"decoder_function": "simple_decode",
"unsqueeze_dim": 1
},
"dataset_params":{
"file_path": file_path,
"forecast_history":wandb_config["forecast_history"],
"forecast_length":wandb_config["out_seq_length"],
"relevant_cols": ["new_cases", "month", "weekday"],
"target_col": ["new_cases"],
"scaling": "StandardScaler",
"interpolate_param": False
}
}
}
if weight_path:
config_default["weight_path"] = weight_path
wandb.config.update(config_default)
return config_default
sweep_config = {
"name": "Default sweep",
"method": "grid",
"parameters": {
"batch_size": {
"values": [2, 3, 4, 5]
},
"lr":{
"values":[0.001, 0.002, 0.004, 0.01]
},
"optimizer":{
"values":["Adam"]
},
"forecast_history":{
"values":[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
},
"out_seq_length":{
"values":[1, 2, 3]
}
}
}
def format_corona_data(region_df:pd.DataFrame, region_name:str):
"""
Format data for a specific region into
a format that can be used with flow forecast.
"""
if region_name == 'county':
region_name = region_df['full_county'].iloc[0]
else:
region_name = region_df['state'].iloc[0]
#else:
#region_name = region_df['country'].iloc[0]
print(region_name)
region_df['datetime'] = region_df['date']
region_df['precip'] = 0
region_df['temp'] = 0
region_df = region_df.fillna(0)
region_df['new_cases'] = region_df['cases'].diff()
region_df.iloc[0]['new_cases'] = 0
region_df= region_df.fillna(0)
region_df.to_csv(region_name+".csv")
return region_df, len(region_df), region_name+".csv"
def loop_through_geo_codes(df, column='full_county'):
df_county_list = []
df['full_county'] = df['state'] + "_" + df['county']
for code in df['full_county'].unique():
mask = df['full_county'] == code
df_code = df[mask]
ts_count = len(df_code)
if ts_count > 60:
df_county_list.append(df_code)
return df_county_list
def fetch_time_series() -> pd.DataFrame:
"""Fetch raw time series data from coronadatascraper.com
Returns:
pd.DataFrame: raw timeseries data at county/sub-region level
"""
if 1==1:
url = "https://coronadatascraper.com/timeseries.csv"
urllib.request.urlretrieve(url, "timeseries.csv")
time_series_df = pd.read_csv("timeseries.csv")
return time_series_df
import urllib
df = fetch_time_series()
df['month'] = pd.to_datetime(df['date']).map(lambda x: x.month)
df['weekday'] = pd.to_datetime(df['date']).map(lambda x: x.weekday())
df_list = loop_through_geo_codes(df)
/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2822: DtypeWarning: Columns (2) have mixed types.Specify dtype option on import or set low_memory=False. if self.run_code(code, result):
Run sweep
import wandb
def sweep_all_geo(df_list, region_level, start_index=0, end_index=38):
for array_index in range(start_index, end_index):
region_df, full_len, file_path = format_corona_data(df_list[array_index], region_level)
sweep_id = wandb.sweep(sweep_config, project="covid-forecast")
wandb.agent(sweep_id, lambda:train_function("PyTorch", make_config_file(file_path, full_len)))
print(len(df_list))
sweep_all_geo(df_list, 'county', 40, len(df_list))
173 Colorado_Douglas County
/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy del sys.path[0] /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:15: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy from ipykernel import kernelapp as app /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:18: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
Create sweep with ID: dmjolbmp Sweep URL: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp wandb: Agent Starting Run: ikjglsrm with config: batch_size: 2 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ikjglsrm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.209745293483138
The number of items in train is:
21
The loss for epoch 0
1.0576069187372923
The running loss is:
25.875566819682717
The number of items in train is:
21
The loss for epoch 1
1.23216984855632
The running loss is:
16.456275817006826
The number of items in train is:
21
The loss for epoch 2
0.7836321817622298
The running loss is:
16.631219685077667
The number of items in train is:
21
The loss for epoch 3
0.7919628421465555
The running loss is:
15.837834678590298
The number of items in train is:
21
The loss for epoch 4
0.7541826037423951
The running loss is:
14.741810627281666
The number of items in train is:
21
The loss for epoch 5
0.7019909822515079
The running loss is:
15.050849847495556
The number of items in train is:
21
The loss for epoch 6
0.7167071355950265
The running loss is:
15.953906068578362
The number of items in train is:
21
The loss for epoch 7
0.7597098127894458
The running loss is:
16.0874502658844
The number of items in train is:
21
The loss for epoch 8
0.7660690602802095
The running loss is:
15.227701779454947
The number of items in train is:
21
The loss for epoch 9
0.7251286561645213
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.894448
48 30755 ... 11.626228
49 30756 ... 11.733383
50 30757 ... 12.008819
51 30758 ... 12.359694
52 30759 ... 12.744390
53 30760 ... 13.144247
54 30761 ... 11.959114
55 30762 ... 11.655218
56 30763 ... 11.746380
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ikjglsrm wandb: Agent Starting Run: sccle7in with config: batch_size: 2 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sccle7in
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
32.99953880906105
The number of items in train is:
21
The loss for epoch 0
1.5714066099552881
The running loss is:
34.578114688396454
The number of items in train is:
21
The loss for epoch 1
1.6465768899236406
The running loss is:
25.18665075302124
The number of items in train is:
21
The loss for epoch 2
1.19936432157244
The running loss is:
24.97196725010872
The number of items in train is:
21
The loss for epoch 3
1.1891412976242246
The running loss is:
24.43036612868309
The number of items in train is:
21
The loss for epoch 4
1.1633507680325281
The running loss is:
24.190653383731842
The number of items in train is:
21
The loss for epoch 5
1.151935875415802
The running loss is:
23.219544798135757
The number of items in train is:
21
The loss for epoch 6
1.1056926094350361
The running loss is:
22.971314638853073
The number of items in train is:
21
The loss for epoch 7
1.0938721256596702
The running loss is:
21.56657423079014
The number of items in train is:
21
The loss for epoch 8
1.026979725275721
The running loss is:
22.224213495850563
The number of items in train is:
21
The loss for epoch 9
1.0582958807547886
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 15.966778
48 30755 ... 17.588491
49 30756 ... 18.489956
50 30757 ... 19.005741
51 30758 ... 19.315006
52 30759 ... 19.513683
53 30760 ... 19.653145
54 30761 ... 19.529381
55 30762 ... 19.496183
56 30763 ... 19.511480
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sccle7in wandb: Agent Starting Run: 1kbxwatt with config: batch_size: 2 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1kbxwatt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
27.474478989839554
The number of items in train is:
20
The loss for epoch 0
1.3737239494919777
The running loss is:
35.779832273721695
The number of items in train is:
20
The loss for epoch 1
1.7889916136860848
The running loss is:
23.186582028865814
The number of items in train is:
20
The loss for epoch 2
1.1593291014432907
The running loss is:
22.105967074632645
The number of items in train is:
20
The loss for epoch 3
1.1052983537316323
The running loss is:
21.186039209365845
The number of items in train is:
20
The loss for epoch 4
1.0593019604682923
The running loss is:
21.136306032538414
The number of items in train is:
20
The loss for epoch 5
1.0568153016269206
The running loss is:
20.87136097252369
The number of items in train is:
20
The loss for epoch 6
1.0435680486261845
The running loss is:
20.777209982275963
The number of items in train is:
20
The loss for epoch 7
1.0388604991137982
The running loss is:
20.66132915019989
The number of items in train is:
20
The loss for epoch 8
1.0330664575099946
The running loss is:
20.37255945801735
The number of items in train is:
20
The loss for epoch 9
1.0186279729008674
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 6.496966
48 30755 ... 3.573092
49 30756 ... 2.030942
50 30757 ... 1.022203
51 30758 ... 0.219382
52 30759 ... -0.503940
53 30760 ... -1.196578
54 30761 ... 1.016424
55 30762 ... 1.457347
56 30763 ... 1.214166
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1kbxwatt wandb: Agent Starting Run: yr7zkt33 with config: batch_size: 2 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yr7zkt33
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.944366239011288
The number of items in train is:
21
The loss for epoch 0
0.854493630429109
The running loss is:
34.34139671176672
The number of items in train is:
21
The loss for epoch 1
1.6353046053222247
The running loss is:
27.00930019468069
The number of items in train is:
21
The loss for epoch 2
1.286157152127652
The running loss is:
17.550274595618248
The number of items in train is:
21
The loss for epoch 3
0.8357273616961071
The running loss is:
15.303298708051443
The number of items in train is:
21
The loss for epoch 4
0.7287285099072116
The running loss is:
16.061053287237883
The number of items in train is:
21
The loss for epoch 5
0.764812061297042
The running loss is:
15.270921267569065
The number of items in train is:
21
The loss for epoch 6
0.7271867270270983
The running loss is:
15.990724802017212
The number of items in train is:
21
The loss for epoch 7
0.7614630858103434
The running loss is:
15.62948726862669
The number of items in train is:
21
The loss for epoch 8
0.7442612985060328
The running loss is:
15.671696230769157
The number of items in train is:
21
The loss for epoch 9
0.7462712490842456
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.829262
48 30755 ... 11.559772
49 30756 ... 11.661650
50 30757 ... 11.916553
51 30758 ... 12.234512
52 30759 ... 12.578454
53 30760 ... 12.933103
54 30761 ... 11.801696
55 30762 ... 11.548413
56 30763 ... 11.656969
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yr7zkt33 wandb: Agent Starting Run: 64pwuc2m with config: batch_size: 2 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 64pwuc2m
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
27.359292954206467
The number of items in train is:
21
The loss for epoch 0
1.3028234740098317
The running loss is:
43.42585930228233
The number of items in train is:
21
The loss for epoch 1
2.0678980620134446
The running loss is:
33.279954731464386
The number of items in train is:
21
The loss for epoch 2
1.5847597491173517
The running loss is:
25.072028666734695
The number of items in train is:
21
The loss for epoch 3
1.1939061269873665
The running loss is:
22.292101874947548
The number of items in train is:
21
The loss for epoch 4
1.061528660711788
The running loss is:
23.1343837082386
The number of items in train is:
21
The loss for epoch 5
1.1016373194399334
The running loss is:
21.76330964267254
The number of items in train is:
21
The loss for epoch 6
1.0363480782225019
The running loss is:
21.404461607336998
The number of items in train is:
21
The loss for epoch 7
1.019260076539857
The running loss is:
19.915255278348923
The number of items in train is:
21
The loss for epoch 8
0.9483454894451868
The running loss is:
19.895478509366512
The number of items in train is:
21
The loss for epoch 9
0.9474037385412625
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 14.941013
48 30755 ... 15.908203
49 30756 ... 16.418524
50 30757 ... 16.714504
51 30758 ... 16.909929
52 30759 ... 17.058176
53 30760 ... 17.184292
54 30761 ... 16.904070
55 30762 ... 16.829170
56 30763 ... 16.850595
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 64pwuc2m wandb: Agent Starting Run: s51msur4 with config: batch_size: 2 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: s51msur4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.703781209886074
The number of items in train is:
20
The loss for epoch 0
1.0351890604943037
The running loss is:
47.7876605540514
The number of items in train is:
20
The loss for epoch 1
2.38938302770257
The running loss is:
35.47767253220081
The number of items in train is:
20
The loss for epoch 2
1.7738836266100406
The running loss is:
23.832139432430267
The number of items in train is:
20
The loss for epoch 3
1.1916069716215134
The running loss is:
21.081158697605133
The number of items in train is:
20
The loss for epoch 4
1.0540579348802566
The running loss is:
20.350356683135033
The number of items in train is:
20
The loss for epoch 5
1.0175178341567517
The running loss is:
19.832687944173813
The number of items in train is:
20
The loss for epoch 6
0.9916343972086906
The running loss is:
19.82853750884533
The number of items in train is:
20
The loss for epoch 7
0.9914268754422665
The running loss is:
19.4885743111372
The number of items in train is:
20
The loss for epoch 8
0.97442871555686
The running loss is:
18.965040057897568
The number of items in train is:
20
The loss for epoch 9
0.9482520028948784
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 7.287391
48 30755 ... 4.862523
49 30756 ... 3.617318
50 30757 ... 2.795383
51 30758 ... 2.125319
52 30759 ... 1.509749
53 30760 ... 0.913731
54 30761 ... 2.950763
55 30762 ... 3.306514
56 30763 ... 3.059012
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: s51msur4 wandb: Agent Starting Run: wx5xxkqb with config: batch_size: 2 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: wx5xxkqb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.458090774714947
The number of items in train is:
21
The loss for epoch 0
0.9741947987959498
The running loss is:
24.059880753979087
The number of items in train is:
21
The loss for epoch 1
1.1457086073323375
The running loss is:
23.21456527709961
The number of items in train is:
21
The loss for epoch 2
1.1054554893856956
The running loss is:
28.819509647786617
The number of items in train is:
21
The loss for epoch 3
1.3723576022755533
The running loss is:
31.193957291543484
The number of items in train is:
21
The loss for epoch 4
1.4854265376925468
The running loss is:
27.668494045734406
The number of items in train is:
21
The loss for epoch 5
1.3175473355111622
The running loss is:
25.656272009015083
The number of items in train is:
21
The loss for epoch 6
1.2217272385245277
The running loss is:
20.36942693591118
The number of items in train is:
21
The loss for epoch 7
0.9699727112338656
The running loss is:
15.879903003573418
The number of items in train is:
21
The loss for epoch 8
0.7561858573130199
The running loss is:
16.215510118752718
The number of items in train is:
21
The loss for epoch 9
0.7721671485120342
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 12.331620
48 30755 ... 12.283362
49 30756 ... 12.453766
50 30757 ... 12.701273
51 30758 ... 12.975966
52 30759 ... 13.260247
53 30760 ... 13.547908
54 30761 ... 12.524818
55 30762 ... 12.351486
56 30763 ... 12.477787
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wx5xxkqb wandb: Agent Starting Run: 0wqxnael with config: batch_size: 2 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 0wqxnael
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
25.328899294137955
The number of items in train is:
21
The loss for epoch 0
1.206138061625617
The running loss is:
28.402115911245346
The number of items in train is:
21
The loss for epoch 1
1.3524817100593023
The running loss is:
27.489022433757782
The number of items in train is:
21
The loss for epoch 2
1.3090010682741802
The running loss is:
32.18459129333496
The number of items in train is:
21
The loss for epoch 3
1.532599585396903
The running loss is:
33.80143202841282
The number of items in train is:
21
The loss for epoch 4
1.6095920013529914
The running loss is:
32.85577954351902
The number of items in train is:
21
The loss for epoch 5
1.564560930643763
The running loss is:
30.47883702814579
The number of items in train is:
21
The loss for epoch 6
1.4513731918164663
The running loss is:
25.70555293187499
The number of items in train is:
21
The loss for epoch 7
1.2240739491369044
The running loss is:
20.333487920463085
The number of items in train is:
21
The loss for epoch 8
0.9682613295458612
The running loss is:
18.726626021787524
The number of items in train is:
21
The loss for epoch 9
0.8917440962755964
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 13.114093
48 30755 ... 13.178655
49 30756 ... 13.227503
50 30757 ... 13.271365
51 30758 ... 13.313645
52 30759 ... 13.355424
53 30760 ... 13.397043
54 30761 ... 13.240062
55 30762 ... 13.218620
56 30763 ... 13.240183
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0wqxnael wandb: Agent Starting Run: vi2glmaj with config: batch_size: 2 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: vi2glmaj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.522139191627502
The number of items in train is:
20
The loss for epoch 0
1.0261069595813752
The running loss is:
28.824470579624176
The number of items in train is:
20
The loss for epoch 1
1.4412235289812088
The running loss is:
26.96215519309044
The number of items in train is:
20
The loss for epoch 2
1.348107759654522
The running loss is:
24.277756571769714
The number of items in train is:
20
The loss for epoch 3
1.2138878285884858
The running loss is:
39.18795786798
The number of items in train is:
20
The loss for epoch 4
1.9593978933990002
The running loss is:
27.062116272747517
The number of items in train is:
20
The loss for epoch 5
1.353105813637376
The running loss is:
31.32304859161377
The number of items in train is:
20
The loss for epoch 6
1.5661524295806886
The running loss is:
25.954569905996323
The number of items in train is:
20
The loss for epoch 7
1.297728495299816
The running loss is:
20.310090392827988
The number of items in train is:
20
The loss for epoch 8
1.0155045196413994
The running loss is:
18.296321973204613
The number of items in train is:
20
The loss for epoch 9
0.9148160986602306
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 8.719911
48 30755 ... 7.223289
49 30756 ... 6.481489
50 30757 ... 5.944383
51 30758 ... 5.462785
52 30759 ... 4.996240
53 30760 ... 4.533777
54 30761 ... 6.424037
55 30762 ... 6.600693
56 30763 ... 6.312653
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vi2glmaj wandb: Agent Starting Run: t6tt7nnl with config: batch_size: 2 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: t6tt7nnl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
61.04869698733091
The number of items in train is:
21
The loss for epoch 0
2.9070808089205196
The running loss is:
24.786502487957478
The number of items in train is:
21
The loss for epoch 1
1.1803096422836894
The running loss is:
30.512474812567234
The number of items in train is:
21
The loss for epoch 2
1.4529749910746301
The running loss is:
22.967344410717487
The number of items in train is:
21
The loss for epoch 3
1.0936830671770232
The running loss is:
25.316022649407387
The number of items in train is:
21
The loss for epoch 4
1.2055248880670184
The running loss is:
23.791697189211845
The number of items in train is:
21
The loss for epoch 5
1.1329379613910402
The running loss is:
20.797373056411743
The number of items in train is:
21
The loss for epoch 6
0.9903510979243687
The running loss is:
18.34804441407323
The number of items in train is:
21
The loss for epoch 7
0.8737164006701538
The running loss is:
16.632033981382847
The number of items in train is:
21
The loss for epoch 8
0.7920016181610879
The running loss is:
16.302831880748272
The number of items in train is:
21
The loss for epoch 9
0.7763253276546797
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.427103
48 30755 ... 11.119713
49 30756 ... 11.244295
50 30757 ... 11.516330
51 30758 ... 11.838696
52 30759 ... 12.178244
53 30760 ... 12.523656
54 30761 ... 11.264505
55 30762 ... 11.064211
56 30763 ... 11.225350
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: t6tt7nnl wandb: Agent Starting Run: i0dy7151 with config: batch_size: 2 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: i0dy7151
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
69.45899105072021
The number of items in train is:
21
The loss for epoch 0
3.3075710024152483
The running loss is:
24.351533740758896
The number of items in train is:
21
The loss for epoch 1
1.1595968447980427
The running loss is:
38.97736042737961
The number of items in train is:
21
The loss for epoch 2
1.8560647822561718
The running loss is:
25.299872055649757
The number of items in train is:
21
The loss for epoch 3
1.204755812173798
The running loss is:
23.097379501909018
The number of items in train is:
21
The loss for epoch 4
1.09987521437662
The running loss is:
25.473997458815575
The number of items in train is:
21
The loss for epoch 5
1.2130474980388368
The running loss is:
22.643349528312683
The number of items in train is:
21
The loss for epoch 6
1.0782547394434612
The running loss is:
18.14205700904131
The number of items in train is:
21
The loss for epoch 7
0.8639074766210147
The running loss is:
16.48433183133602
The number of items in train is:
21
The loss for epoch 8
0.7849681824445724
The running loss is:
16.34719529747963
The number of items in train is:
21
The loss for epoch 9
0.7784378713085538
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.766082
48 30755 ... 11.452952
49 30756 ... 11.440730
50 30757 ... 11.526842
51 30758 ... 11.645089
52 30759 ... 11.773837
53 30760 ... 11.906017
54 30761 ... 11.408577
55 30762 ... 11.336123
56 30763 ... 11.402551
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: i0dy7151 wandb: Agent Starting Run: 4tuwhbc3 with config: batch_size: 2 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 4tuwhbc3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
73.17438182234764
The number of items in train is:
20
The loss for epoch 0
3.658719091117382
The running loss is:
24.5871611982584
The number of items in train is:
20
The loss for epoch 1
1.22935805991292
The running loss is:
48.73001056909561
The number of items in train is:
20
The loss for epoch 2
2.4365005284547805
The running loss is:
35.53122544288635
The number of items in train is:
20
The loss for epoch 3
1.7765612721443176
The running loss is:
24.193623542785645
The number of items in train is:
20
The loss for epoch 4
1.2096811771392821
The running loss is:
31.478034928441048
The number of items in train is:
20
The loss for epoch 5
1.5739017464220524
The running loss is:
26.469323992729187
The number of items in train is:
20
The loss for epoch 6
1.3234661996364594
The running loss is:
21.868590533733368
The number of items in train is:
20
The loss for epoch 7
1.0934295266866685
The running loss is:
17.746363550424576
The number of items in train is:
20
The loss for epoch 8
0.8873181775212288
The running loss is:
16.37228138744831
The number of items in train is:
20
The loss for epoch 9
0.8186140693724155
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 10.991632
48 30755 ... 9.842609
49 30756 ... 8.999443
50 30757 ... 8.265136
51 30758 ... 7.569574
52 30759 ... 6.887804
53 30760 ... 6.210940
54 30761 ... 8.575280
55 30762 ... 8.982585
56 30763 ... 8.693344
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4tuwhbc3 wandb: Agent Starting Run: 0r1mvx0k with config: batch_size: 2 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0r1mvx0k
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.008637461811304
The number of items in train is:
21
The loss for epoch 0
1.0956494029433954
The running loss is:
32.2327605355531
The number of items in train is:
21
The loss for epoch 1
1.5348933588358618
The running loss is:
17.726538762450218
The number of items in train is:
21
The loss for epoch 2
0.8441208934500104
The running loss is:
12.940901616588235
The number of items in train is:
21
The loss for epoch 3
0.6162334103137255
The running loss is:
16.331525344401598
The number of items in train is:
21
The loss for epoch 4
0.7776916830667427
The running loss is:
12.3541901409626
The number of items in train is:
21
The loss for epoch 5
0.5882947686172667
The running loss is:
12.735355507582426
The number of items in train is:
21
The loss for epoch 6
0.6064455003610679
The running loss is:
13.34062596410513
The number of items in train is:
21
The loss for epoch 7
0.6352679030526251
The running loss is:
11.95759018138051
The number of items in train is:
21
The loss for epoch 8
0.5694090562562147
The running loss is:
12.26656811311841
The number of items in train is:
21
The loss for epoch 9
0.5841222911008767
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.974232
48 30755 ... 15.381114
49 30756 ... 14.857310
50 30757 ... 15.986811
51 30758 ... 15.042921
52 30759 ... 14.311747
53 30760 ... 12.546846
54 30761 ... 14.352466
55 30762 ... 16.448072
56 30763 ... 16.995480
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0r1mvx0k wandb: Agent Starting Run: e62ibr45 with config: batch_size: 2 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: e62ibr45
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.77712646126747
The number of items in train is:
20
The loss for epoch 0
1.1388563230633735
The running loss is:
30.30465880036354
The number of items in train is:
20
The loss for epoch 1
1.515232940018177
The running loss is:
19.663687139749527
The number of items in train is:
20
The loss for epoch 2
0.9831843569874763
The running loss is:
17.537601500749588
The number of items in train is:
20
The loss for epoch 3
0.8768800750374794
The running loss is:
17.679495960474014
The number of items in train is:
20
The loss for epoch 4
0.8839747980237007
The running loss is:
15.744170039892197
The number of items in train is:
20
The loss for epoch 5
0.7872085019946098
The running loss is:
15.426739200949669
The number of items in train is:
20
The loss for epoch 6
0.7713369600474834
The running loss is:
14.944714151322842
The number of items in train is:
20
The loss for epoch 7
0.7472357075661421
The running loss is:
14.250869244337082
The number of items in train is:
20
The loss for epoch 8
0.712543462216854
The running loss is:
14.41989190876484
The number of items in train is:
20
The loss for epoch 9
0.720994595438242
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.836431
48 30755 ... 14.815100
49 30756 ... 13.822679
50 30757 ... 14.759495
51 30758 ... 13.484217
52 30759 ... 12.383018
53 30760 ... 10.215312
54 30761 ... 12.387611
55 30762 ... 13.979239
56 30763 ... 14.619460
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: e62ibr45 wandb: Agent Starting Run: 0g2cidja with config: batch_size: 2 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 0g2cidja
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.578702680766582
The number of items in train is:
20
The loss for epoch 0
1.078935134038329
The running loss is:
28.895316019654274
The number of items in train is:
20
The loss for epoch 1
1.4447658009827138
The running loss is:
17.934798389673233
The number of items in train is:
20
The loss for epoch 2
0.8967399194836616
The running loss is:
15.32413261756301
The number of items in train is:
20
The loss for epoch 3
0.7662066308781504
The running loss is:
15.212896093726158
The number of items in train is:
20
The loss for epoch 4
0.7606448046863079
The running loss is:
13.6849125623703
The number of items in train is:
20
The loss for epoch 5
0.684245628118515
The running loss is:
15.095305874943733
The number of items in train is:
20
The loss for epoch 6
0.7547652937471867
The running loss is:
13.407148011028767
The number of items in train is:
20
The loss for epoch 7
0.6703574005514383
The running loss is:
14.454618975520134
The number of items in train is:
20
The loss for epoch 8
0.7227309487760067
The running loss is:
13.429822385311127
The number of items in train is:
20
The loss for epoch 9
0.6714911192655564
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.413411
48 30755 ... 15.669946
49 30756 ... 17.122110
50 30757 ... 18.615124
51 30758 ... 19.127787
52 30759 ... 19.283003
53 30760 ... 18.859772
54 30761 ... 21.885056
55 30762 ... 23.855570
56 30763 ... 25.221436
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0g2cidja wandb: Agent Starting Run: rjep75dc with config: batch_size: 2 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: rjep75dc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.55631679482758
The number of items in train is:
21
The loss for epoch 0
0.8836341330870277
The running loss is:
39.76102647557855
The number of items in train is:
21
The loss for epoch 1
1.893382213122788
The running loss is:
31.392640566453338
The number of items in train is:
21
The loss for epoch 2
1.4948876460215874
The running loss is:
21.55244082212448
The number of items in train is:
21
The loss for epoch 3
1.0263067058154516
The running loss is:
13.321244258899242
The number of items in train is:
21
The loss for epoch 4
0.6343449647094876
The running loss is:
16.369411423802376
The number of items in train is:
21
The loss for epoch 5
0.7794957820858274
The running loss is:
12.878714980557561
The number of items in train is:
21
The loss for epoch 6
0.6132721419313124
The running loss is:
15.277130480855703
The number of items in train is:
21
The loss for epoch 7
0.7274824038502716
The running loss is:
12.423281671479344
The number of items in train is:
21
The loss for epoch 8
0.5915848414990164
The running loss is:
13.389100320637226
The number of items in train is:
21
The loss for epoch 9
0.6375762057446298
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.093603
48 30755 ... 15.438350
49 30756 ... 15.362393
50 30757 ... 15.736447
51 30758 ... 15.006408
52 30759 ... 14.255008
53 30760 ... 12.908654
54 30761 ... 14.277620
55 30762 ... 15.742886
56 30763 ... 16.026230
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rjep75dc wandb: Agent Starting Run: 1hy1myeb with config: batch_size: 2 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 1hy1myeb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.790002673864365
The number of items in train is:
20
The loss for epoch 0
0.9895001336932182
The running loss is:
35.51101356744766
The number of items in train is:
20
The loss for epoch 1
1.7755506783723831
The running loss is:
29.900236278772354
The number of items in train is:
20
The loss for epoch 2
1.4950118139386177
The running loss is:
20.32610148191452
The number of items in train is:
20
The loss for epoch 3
1.016305074095726
The running loss is:
17.535978391766548
The number of items in train is:
20
The loss for epoch 4
0.8767989195883275
The running loss is:
15.788296699523926
The number of items in train is:
20
The loss for epoch 5
0.7894148349761962
The running loss is:
15.298003315925598
The number of items in train is:
20
The loss for epoch 6
0.76490016579628
The running loss is:
14.471397161483765
The number of items in train is:
20
The loss for epoch 7
0.7235698580741883
The running loss is:
15.182393252849579
The number of items in train is:
20
The loss for epoch 8
0.759119662642479
The running loss is:
15.049454137682915
The number of items in train is:
20
The loss for epoch 9
0.7524727068841457
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.637438
48 30755 ... 13.303226
49 30756 ... 12.201837
50 30757 ... 12.177489
51 30758 ... 10.806701
52 30759 ... 9.582183
53 30760 ... 7.934246
54 30761 ... 8.110060
55 30762 ... 10.489552
56 30763 ... 10.417169
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1hy1myeb wandb: Agent Starting Run: izha8psp with config: batch_size: 2 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: izha8psp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.73946076631546
The number of items in train is:
20
The loss for epoch 0
0.836973038315773
The running loss is:
34.69972918741405
The number of items in train is:
20
The loss for epoch 1
1.7349864593707025
The running loss is:
28.933668479323387
The number of items in train is:
20
The loss for epoch 2
1.4466834239661694
The running loss is:
20.98772995173931
The number of items in train is:
20
The loss for epoch 3
1.0493864975869656
The running loss is:
14.910560678690672
The number of items in train is:
20
The loss for epoch 4
0.7455280339345336
The running loss is:
13.784054175019264
The number of items in train is:
20
The loss for epoch 5
0.6892027087509632
The running loss is:
14.498991958796978
The number of items in train is:
20
The loss for epoch 6
0.7249495979398489
The running loss is:
13.606230936944485
The number of items in train is:
20
The loss for epoch 7
0.6803115468472243
The running loss is:
14.566328644752502
The number of items in train is:
20
The loss for epoch 8
0.7283164322376251
The running loss is:
12.793043170124292
The number of items in train is:
20
The loss for epoch 9
0.6396521585062146
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.115752
48 30755 ... 14.251652
49 30756 ... 15.619260
50 30757 ... 16.408094
51 30758 ... 16.587444
52 30759 ... 16.368526
53 30760 ... 15.831397
54 30761 ... 17.615082
55 30762 ... 19.396448
56 30763 ... 20.256659
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: izha8psp wandb: Agent Starting Run: j4p3rea7 with config: batch_size: 2 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: j4p3rea7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.612260351888835
The number of items in train is:
21
The loss for epoch 0
0.8386790643756589
The running loss is:
27.575611753884004
The number of items in train is:
21
The loss for epoch 1
1.3131243692325716
The running loss is:
19.56693585170433
The number of items in train is:
21
The loss for epoch 2
0.9317588500811586
The running loss is:
29.6243880931288
The number of items in train is:
21
The loss for epoch 3
1.4106851472918476
The running loss is:
31.01244868338108
The number of items in train is:
21
The loss for epoch 4
1.4767832706371944
The running loss is:
30.337950587272644
The number of items in train is:
21
The loss for epoch 5
1.4446643136796498
The running loss is:
20.72286257147789
The number of items in train is:
21
The loss for epoch 6
0.9868029795941853
The running loss is:
13.726178638637066
The number of items in train is:
21
The loss for epoch 7
0.6536275542208126
The running loss is:
15.882041074335575
The number of items in train is:
21
The loss for epoch 8
0.7562876702064559
The running loss is:
13.951960653066635
The number of items in train is:
21
The loss for epoch 9
0.6643790787174588
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.314129
48 30755 ... 14.173787
49 30756 ... 13.942454
50 30757 ... 14.106256
51 30758 ... 13.663309
52 30759 ... 13.262284
53 30760 ... 12.640742
54 30761 ... 13.062532
55 30762 ... 14.247359
56 30763 ... 14.199184
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: j4p3rea7 wandb: Agent Starting Run: oyn5vyw0 with config: batch_size: 2 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: oyn5vyw0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.16664184629917
The number of items in train is:
20
The loss for epoch 0
0.9583320923149585
The running loss is:
24.30276045203209
The number of items in train is:
20
The loss for epoch 1
1.2151380226016044
The running loss is:
21.017927818000317
The number of items in train is:
20
The loss for epoch 2
1.0508963909000157
The running loss is:
25.24866795539856
The number of items in train is:
20
The loss for epoch 3
1.262433397769928
The running loss is:
29.989633813500404
The number of items in train is:
20
The loss for epoch 4
1.4994816906750201
The running loss is:
27.833610378205776
The number of items in train is:
20
The loss for epoch 5
1.3916805189102888
The running loss is:
20.38179862499237
The number of items in train is:
20
The loss for epoch 6
1.0190899312496184
The running loss is:
19.694613575935364
The number of items in train is:
20
The loss for epoch 7
0.9847306787967682
The running loss is:
16.29368768632412
The number of items in train is:
20
The loss for epoch 8
0.8146843843162059
The running loss is:
16.283535540103912
The number of items in train is:
20
The loss for epoch 9
0.8141767770051956
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.646613
48 30755 ... 12.670735
49 30756 ... 12.202353
50 30757 ... 12.349521
51 30758 ... 11.980251
52 30759 ... 11.627564
53 30760 ... 11.168602
54 30761 ... 11.710465
55 30762 ... 12.506949
56 30763 ... 12.491008
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: oyn5vyw0 wandb: Agent Starting Run: ard0kcgk with config: batch_size: 2 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ard0kcgk
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.326067708432674
The number of items in train is:
20
The loss for epoch 0
0.8663033854216338
The running loss is:
26.125781033188105
The number of items in train is:
20
The loss for epoch 1
1.3062890516594052
The running loss is:
20.05863458663225
The number of items in train is:
20
The loss for epoch 2
1.0029317293316127
The running loss is:
26.94086644053459
The number of items in train is:
20
The loss for epoch 3
1.3470433220267295
The running loss is:
27.031484097242355
The number of items in train is:
20
The loss for epoch 4
1.3515742048621178
The running loss is:
26.107848599553108
The number of items in train is:
20
The loss for epoch 5
1.3053924299776554
The running loss is:
19.87912854552269
The number of items in train is:
20
The loss for epoch 6
0.9939564272761345
The running loss is:
19.120233863592148
The number of items in train is:
20
The loss for epoch 7
0.9560116931796074
The running loss is:
18.272066473960876
The number of items in train is:
20
The loss for epoch 8
0.9136033236980439
The running loss is:
16.09623235464096
The number of items in train is:
20
The loss for epoch 9
0.804811617732048
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.101974
48 30755 ... 10.439401
49 30756 ... 9.826941
50 30757 ... 9.700224
51 30758 ... 9.537777
52 30759 ... 9.432247
53 30760 ... 9.338076
54 30761 ... 8.713398
55 30762 ... 9.319012
56 30763 ... 9.401543
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ard0kcgk wandb: Agent Starting Run: qm4xgxw1 with config: batch_size: 2 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: qm4xgxw1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
88.16768562421203
The number of items in train is:
21
The loss for epoch 0
4.198461220200572
The running loss is:
32.399377366527915
The number of items in train is:
21
The loss for epoch 1
1.5428274936441864
The running loss is:
44.084197610616684
The number of items in train is:
21
The loss for epoch 2
2.0992475052674613
The running loss is:
31.271542832255363
The number of items in train is:
21
The loss for epoch 3
1.4891210872502554
The running loss is:
24.642942052334547
The number of items in train is:
21
The loss for epoch 4
1.17347343106355
The running loss is:
25.46325683966279
The number of items in train is:
21
The loss for epoch 5
1.2125360399839424
The running loss is:
22.69593182578683
The number of items in train is:
21
The loss for epoch 6
1.0807586583708013
The running loss is:
22.1004674769938
The number of items in train is:
21
The loss for epoch 7
1.0524032131901808
The running loss is:
21.082351729273796
The number of items in train is:
21
The loss for epoch 8
1.0039215109178
The running loss is:
20.709456760436296
The number of items in train is:
21
The loss for epoch 9
0.9861646076398236
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.968234
48 30755 ... 12.532819
49 30756 ... 12.348880
50 30757 ... 12.427336
51 30758 ... 12.384806
52 30759 ... 12.386845
53 30760 ... 12.371067
54 30761 ... 11.455049
55 30762 ... 12.432656
56 30763 ... 12.267653
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qm4xgxw1 wandb: Agent Starting Run: xau7eqeu with config: batch_size: 2 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: xau7eqeu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.44850631058216
The number of items in train is:
20
The loss for epoch 0
2.572425315529108
The running loss is:
26.536537259817123
The number of items in train is:
20
The loss for epoch 1
1.3268268629908562
The running loss is:
25.394971758127213
The number of items in train is:
20
The loss for epoch 2
1.2697485879063606
The running loss is:
26.157265178859234
The number of items in train is:
20
The loss for epoch 3
1.3078632589429617
The running loss is:
26.907141968607903
The number of items in train is:
20
The loss for epoch 4
1.345357098430395
The running loss is:
23.60898245871067
The number of items in train is:
20
The loss for epoch 5
1.1804491229355336
The running loss is:
21.588230818510056
The number of items in train is:
20
The loss for epoch 6
1.0794115409255027
The running loss is:
23.299431294202805
The number of items in train is:
20
The loss for epoch 7
1.1649715647101402
The running loss is:
17.95345228165388
The number of items in train is:
20
The loss for epoch 8
0.897672614082694
The running loss is:
21.56754533946514
The number of items in train is:
20
The loss for epoch 9
1.078377266973257
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.127200
48 30755 ... 9.427205
49 30756 ... 8.578013
50 30757 ... 8.423813
51 30758 ... 8.186283
52 30759 ... 8.086294
53 30760 ... 7.967240
54 30761 ... 8.324524
55 30762 ... 8.337108
56 30763 ... 8.307590
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xau7eqeu wandb: Agent Starting Run: falknk2c with config: batch_size: 2 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: falknk2c
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
50.97534599900246
The number of items in train is:
20
The loss for epoch 0
2.5487672999501227
The running loss is:
28.12403143942356
The number of items in train is:
20
The loss for epoch 1
1.406201571971178
The running loss is:
24.375909984111786
The number of items in train is:
20
The loss for epoch 2
1.2187954992055894
The running loss is:
22.562284395098686
The number of items in train is:
20
The loss for epoch 3
1.1281142197549343
The running loss is:
28.00324049592018
The number of items in train is:
20
The loss for epoch 4
1.4001620247960092
The running loss is:
21.4647678732872
The number of items in train is:
20
The loss for epoch 5
1.0732383936643601
The running loss is:
21.226560071110725
The number of items in train is:
20
The loss for epoch 6
1.0613280035555364
The running loss is:
20.05168192088604
The number of items in train is:
20
The loss for epoch 7
1.002584096044302
The running loss is:
19.073723807930946
The number of items in train is:
20
The loss for epoch 8
0.9536861903965473
The running loss is:
20.08955078572035
The number of items in train is:
20
The loss for epoch 9
1.0044775392860175
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.038617
48 30755 ... 10.301286
49 30756 ... 10.527411
50 30757 ... 10.665849
51 30758 ... 10.829441
52 30759 ... 10.893164
53 30760 ... 11.022404
54 30761 ... 9.990615
55 30762 ... 10.360154
56 30763 ... 10.527678
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: falknk2c wandb: Agent Starting Run: 6sarts3o with config: batch_size: 2 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 6sarts3o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.16620772331953
The number of items in train is:
20
The loss for epoch 0
0.6583103861659765
The running loss is:
47.089191913604736
The number of items in train is:
20
The loss for epoch 1
2.354459595680237
The running loss is:
20.295180901885033
The number of items in train is:
20
The loss for epoch 2
1.0147590450942516
The running loss is:
14.66391147999093
The number of items in train is:
20
The loss for epoch 3
0.7331955739995465
The running loss is:
14.51472514308989
The number of items in train is:
20
The loss for epoch 4
0.7257362571544945
The running loss is:
11.414592620916665
The number of items in train is:
20
The loss for epoch 5
0.5707296310458332
The running loss is:
10.380168374627829
The number of items in train is:
20
The loss for epoch 6
0.5190084187313915
The running loss is:
10.854458432644606
The number of items in train is:
20
The loss for epoch 7
0.5427229216322302
The running loss is:
9.902051273267716
The number of items in train is:
20
The loss for epoch 8
0.4951025636633858
The running loss is:
11.478069743141532
The number of items in train is:
20
The loss for epoch 9
0.5739034871570766
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 4.791970
48 30755 ... 4.017214
49 30756 ... 9.296926
50 30757 ... 8.501606
51 30758 ... 7.561368
52 30759 ... 6.628009
53 30760 ... 4.479429
54 30761 ... 3.208868
55 30762 ... 2.426350
56 30763 ... 6.978889
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6sarts3o wandb: Agent Starting Run: u7zvotqr with config: batch_size: 2 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: u7zvotqr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.250229328870773
The number of items in train is:
20
The loss for epoch 0
1.0125114664435386
The running loss is:
36.03919892013073
The number of items in train is:
20
The loss for epoch 1
1.8019599460065365
The running loss is:
21.369008541107178
The number of items in train is:
20
The loss for epoch 2
1.068450427055359
The running loss is:
16.745819223113358
The number of items in train is:
20
The loss for epoch 3
0.8372909611556679
The running loss is:
16.19626347720623
The number of items in train is:
20
The loss for epoch 4
0.8098131738603115
The running loss is:
15.289014890789986
The number of items in train is:
20
The loss for epoch 5
0.7644507445394992
The running loss is:
14.291767127811909
The number of items in train is:
20
The loss for epoch 6
0.7145883563905955
The running loss is:
13.00631546229124
The number of items in train is:
20
The loss for epoch 7
0.650315773114562
The running loss is:
12.850601639598608
The number of items in train is:
20
The loss for epoch 8
0.6425300819799304
The running loss is:
11.07451168447733
The number of items in train is:
20
The loss for epoch 9
0.5537255842238664
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.846800
48 30755 ... 8.844935
49 30756 ... 11.833019
50 30757 ... 11.595754
51 30758 ... 10.915969
52 30759 ... 9.609382
53 30760 ... 6.918744
54 30761 ... 7.512626
55 30762 ... 9.482866
56 30763 ... 11.247615
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u7zvotqr wandb: Agent Starting Run: cf5ckshz with config: batch_size: 2 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: cf5ckshz
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.24230197072029
The number of items in train is:
19
The loss for epoch 0
0.8548579984589627
The running loss is:
33.577625170350075
The number of items in train is:
19
The loss for epoch 1
1.767243430018425
The running loss is:
17.50975675880909
The number of items in train is:
19
The loss for epoch 2
0.9215661452004784
The running loss is:
15.19348393380642
The number of items in train is:
19
The loss for epoch 3
0.7996570491477063
The running loss is:
14.183778703212738
The number of items in train is:
19
The loss for epoch 4
0.7465146685901441
The running loss is:
13.036552771925926
The number of items in train is:
19
The loss for epoch 5
0.686134356417154
The running loss is:
12.580513373017311
The number of items in train is:
19
The loss for epoch 6
0.6621322827903848
The running loss is:
12.409655019640923
The number of items in train is:
19
The loss for epoch 7
0.653139737875838
The running loss is:
12.531418025493622
The number of items in train is:
19
The loss for epoch 8
0.6595483171312433
The running loss is:
11.11167886853218
The number of items in train is:
19
The loss for epoch 9
0.5848252036069569
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.913255
48 30755 ... 10.473210
49 30756 ... 13.590547
50 30757 ... 14.313401
51 30758 ... 14.773838
52 30759 ... 15.313439
53 30760 ... 15.069212
54 30761 ... 17.728813
55 30762 ... 18.329552
56 30763 ... 21.203745
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cf5ckshz wandb: Agent Starting Run: olx3ydle with config: batch_size: 2 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: olx3ydle
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.871346639934927
The number of items in train is:
20
The loss for epoch 0
0.8435673319967464
The running loss is:
38.40473223477602
The number of items in train is:
20
The loss for epoch 1
1.920236611738801
The running loss is:
31.12108042370528
The number of items in train is:
20
The loss for epoch 2
1.556054021185264
The running loss is:
24.62357160821557
The number of items in train is:
20
The loss for epoch 3
1.2311785804107784
The running loss is:
12.468314666301012
The number of items in train is:
20
The loss for epoch 4
0.6234157333150506
The running loss is:
13.174285745597444
The number of items in train is:
20
The loss for epoch 5
0.6587142872798722
The running loss is:
11.788977996446192
The number of items in train is:
20
The loss for epoch 6
0.5894488998223096
The running loss is:
11.11843922547996
The number of items in train is:
20
The loss for epoch 7
0.5559219612739981
The running loss is:
9.287355293519795
The number of items in train is:
20
The loss for epoch 8
0.4643677646759897
The running loss is:
9.838816735893488
The number of items in train is:
20
The loss for epoch 9
0.4919408367946744
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.513413
48 30755 ... 7.168951
49 30756 ... 11.346724
50 30757 ... 10.831080
51 30758 ... 10.000001
52 30759 ... 9.303995
53 30760 ... 7.738368
54 30761 ... 7.970766
55 30762 ... 7.753849
56 30763 ... 10.696944
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: olx3ydle wandb: Agent Starting Run: 6d8tazmf with config: batch_size: 2 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 6d8tazmf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.881873853504658
The number of items in train is:
20
The loss for epoch 0
0.9440936926752329
The running loss is:
33.3425434269011
The number of items in train is:
20
The loss for epoch 1
1.667127171345055
The running loss is:
29.829890869557858
The number of items in train is:
20
The loss for epoch 2
1.4914945434778928
The running loss is:
25.49375832080841
The number of items in train is:
20
The loss for epoch 3
1.2746879160404205
The running loss is:
17.11493468284607
The number of items in train is:
20
The loss for epoch 4
0.8557467341423035
The running loss is:
14.997745260596275
The number of items in train is:
20
The loss for epoch 5
0.7498872630298138
The running loss is:
14.11250153183937
The number of items in train is:
20
The loss for epoch 6
0.7056250765919685
The running loss is:
12.541615918278694
The number of items in train is:
20
The loss for epoch 7
0.6270807959139347
The running loss is:
11.791180847212672
The number of items in train is:
20
The loss for epoch 8
0.5895590423606336
The running loss is:
11.034595467150211
The number of items in train is:
20
The loss for epoch 9
0.5517297733575106
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.561110
48 30755 ... 12.150685
49 30756 ... 14.576173
50 30757 ... 16.192913
51 30758 ... 17.393833
52 30759 ... 18.037010
53 30760 ... 17.864153
54 30761 ... 22.358480
55 30762 ... 24.322353
56 30763 ... 28.962704
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6d8tazmf wandb: Agent Starting Run: tsnek2xz with config: batch_size: 2 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: tsnek2xz
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.180935945361853
The number of items in train is:
19
The loss for epoch 0
0.7989966287032554
The running loss is:
32.76849117875099
The number of items in train is:
19
The loss for epoch 1
1.7246574304605786
The running loss is:
29.06931023299694
The number of items in train is:
19
The loss for epoch 2
1.5299636964735233
The running loss is:
19.419804587960243
The number of items in train is:
19
The loss for epoch 3
1.022094978313697
The running loss is:
15.750009074807167
The number of items in train is:
19
The loss for epoch 4
0.8289478460424825
The running loss is:
13.63320517539978
The number of items in train is:
19
The loss for epoch 5
0.7175371144947252
The running loss is:
12.82888300716877
The number of items in train is:
19
The loss for epoch 6
0.6752043687983563
The running loss is:
12.820624247193336
The number of items in train is:
19
The loss for epoch 7
0.6747696972207019
The running loss is:
12.8362637758255
The number of items in train is:
19
The loss for epoch 8
0.6755928303066053
The running loss is:
12.048322603106499
The number of items in train is:
19
The loss for epoch 9
0.6341222422687631
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.238999
48 30755 ... 12.542111
49 30756 ... 14.634971
50 30757 ... 15.151684
51 30758 ... 15.261534
52 30759 ... 15.495893
53 30760 ... 15.244351
54 30761 ... 18.465002
55 30762 ... 18.929951
56 30763 ... 19.493837
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tsnek2xz wandb: Agent Starting Run: ouepskbi with config: batch_size: 2 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ouepskbi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
25.258195054717362
The number of items in train is:
20
The loss for epoch 0
1.2629097527358681
The running loss is:
28.71645049750805
The number of items in train is:
20
The loss for epoch 1
1.4358225248754024
The running loss is:
21.496938847005367
The number of items in train is:
20
The loss for epoch 2
1.0748469423502685
The running loss is:
32.175556898117065
The number of items in train is:
20
The loss for epoch 3
1.6087778449058532
The running loss is:
31.53068858385086
The number of items in train is:
20
The loss for epoch 4
1.576534429192543
The running loss is:
25.01493700221181
The number of items in train is:
20
The loss for epoch 5
1.2507468501105905
The running loss is:
20.540104411542416
The number of items in train is:
20
The loss for epoch 6
1.0270052205771207
The running loss is:
13.346534442156553
The number of items in train is:
20
The loss for epoch 7
0.6673267221078276
The running loss is:
14.965123616158962
The number of items in train is:
20
The loss for epoch 8
0.7482561808079481
The running loss is:
12.449737954884768
The number of items in train is:
20
The loss for epoch 9
0.6224868977442384
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.540903
48 30755 ... 8.264866
49 30756 ... 11.485750
50 30757 ... 10.229491
51 30758 ... 9.189299
52 30759 ... 8.309838
53 30760 ... 6.608351
54 30761 ... 6.017721
55 30762 ... 5.683835
56 30763 ... 8.788109
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ouepskbi wandb: Agent Starting Run: hvnouxk7 with config: batch_size: 2 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: hvnouxk7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.307929329574108
The number of items in train is:
20
The loss for epoch 0
1.1153964664787055
The running loss is:
24.764474764466286
The number of items in train is:
20
The loss for epoch 1
1.2382237382233143
The running loss is:
20.000230103731155
The number of items in train is:
20
The loss for epoch 2
1.0000115051865577
The running loss is:
27.805497139692307
The number of items in train is:
20
The loss for epoch 3
1.3902748569846153
The running loss is:
25.04505816102028
The number of items in train is:
20
The loss for epoch 4
1.2522529080510139
The running loss is:
27.622999258339405
The number of items in train is:
20
The loss for epoch 5
1.3811499629169703
The running loss is:
21.294054619967937
The number of items in train is:
20
The loss for epoch 6
1.064702730998397
The running loss is:
18.15154094994068
The number of items in train is:
20
The loss for epoch 7
0.907577047497034
The running loss is:
18.175693213939667
The number of items in train is:
20
The loss for epoch 8
0.9087846606969834
The running loss is:
16.293617084622383
The number of items in train is:
20
The loss for epoch 9
0.8146808542311191
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.284172
48 30755 ... 11.301517
49 30756 ... 12.338721
50 30757 ... 12.630889
51 30758 ... 12.970084
52 30759 ... 13.607054
53 30760 ... 14.193722
54 30761 ... 14.774322
55 30762 ... 14.798644
56 30763 ... 14.683531
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hvnouxk7 wandb: Agent Starting Run: j32zrla3 with config: batch_size: 2 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: j32zrla3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.678802952170372
The number of items in train is:
19
The loss for epoch 0
0.9304633132721248
The running loss is:
23.775851890444756
The number of items in train is:
19
The loss for epoch 1
1.2513606258128818
The running loss is:
19.22152805328369
The number of items in train is:
19
The loss for epoch 2
1.0116593712254573
The running loss is:
22.740102007985115
The number of items in train is:
19
The loss for epoch 3
1.1968474741044797
The running loss is:
23.430920630693436
The number of items in train is:
19
The loss for epoch 4
1.233206348983865
The running loss is:
20.96139857172966
The number of items in train is:
19
The loss for epoch 5
1.1032315037752454
The running loss is:
16.538328647613525
The number of items in train is:
19
The loss for epoch 6
0.8704383498743961
The running loss is:
16.061340644955635
The number of items in train is:
19
The loss for epoch 7
0.8453337181555597
The running loss is:
12.803979389369488
The number of items in train is:
19
The loss for epoch 8
0.6738936520720783
The running loss is:
13.952543005347252
The number of items in train is:
19
The loss for epoch 9
0.734344368702487
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.579448
48 30755 ... 8.149343
49 30756 ... 9.415684
50 30757 ... 8.551306
51 30758 ... 7.895852
52 30759 ... 7.565929
53 30760 ... 6.785355
54 30761 ... 6.457073
55 30762 ... 6.417875
56 30763 ... 7.045417
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: j32zrla3 wandb: Agent Starting Run: vwt7qbzu with config: batch_size: 2 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: vwt7qbzu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
109.38623917661607
The number of items in train is:
20
The loss for epoch 0
5.4693119588308035
The running loss is:
36.06812307983637
The number of items in train is:
20
The loss for epoch 1
1.8034061539918185
The running loss is:
27.07236859574914
The number of items in train is:
20
The loss for epoch 2
1.353618429787457
The running loss is:
19.878866678103805
The number of items in train is:
20
The loss for epoch 3
0.9939433339051902
The running loss is:
36.85931820055703
The number of items in train is:
20
The loss for epoch 4
1.8429659100278513
The running loss is:
19.018329231534153
The number of items in train is:
20
The loss for epoch 5
0.9509164615767076
The running loss is:
22.288700968027115
The number of items in train is:
20
The loss for epoch 6
1.1144350484013557
The running loss is:
30.49784292280674
The number of items in train is:
20
The loss for epoch 7
1.524892146140337
The running loss is:
21.91693382896483
The number of items in train is:
20
The loss for epoch 8
1.0958466914482414
The running loss is:
15.250084459781647
The number of items in train is:
20
The loss for epoch 9
0.7625042229890824
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.705070
48 30755 ... 10.367969
49 30756 ... 13.145773
50 30757 ... 12.067879
51 30758 ... 11.397724
52 30759 ... 11.419276
53 30760 ... 10.288182
54 30761 ... 8.814781
55 30762 ... 10.714540
56 30763 ... 12.394072
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vwt7qbzu wandb: Agent Starting Run: d9ptfhot with config: batch_size: 2 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: d9ptfhot
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
68.95865529216826
The number of items in train is:
20
The loss for epoch 0
3.447932764608413
The running loss is:
27.954812914133072
The number of items in train is:
20
The loss for epoch 1
1.3977406457066537
The running loss is:
21.58340122550726
The number of items in train is:
20
The loss for epoch 2
1.079170061275363
The running loss is:
27.75279625505209
The number of items in train is:
20
The loss for epoch 3
1.3876398127526044
The running loss is:
29.550814539194107
The number of items in train is:
20
The loss for epoch 4
1.4775407269597054
The running loss is:
26.29482465982437
The number of items in train is:
20
The loss for epoch 5
1.3147412329912185
The running loss is:
23.998366855084896
The number of items in train is:
20
The loss for epoch 6
1.1999183427542448
The running loss is:
20.050680205225945
The number of items in train is:
20
The loss for epoch 7
1.0025340102612972
The running loss is:
20.464960746467113
The number of items in train is:
20
The loss for epoch 8
1.0232480373233557
The running loss is:
19.200842931866646
The number of items in train is:
20
The loss for epoch 9
0.9600421465933323
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.980211
48 30755 ... 11.990289
49 30756 ... 12.143848
50 30757 ... 12.068938
51 30758 ... 12.045371
52 30759 ... 12.029554
53 30760 ... 12.001999
54 30761 ... 11.946033
55 30762 ... 11.977056
56 30763 ... 12.094289
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: d9ptfhot wandb: Agent Starting Run: x2eijjhc with config: batch_size: 2 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: x2eijjhc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.38577203452587
The number of items in train is:
19
The loss for epoch 0
2.7045143176066246
The running loss is:
26.914206624031067
The number of items in train is:
19
The loss for epoch 1
1.4165371907384772
The running loss is:
27.34442164748907
The number of items in train is:
19
The loss for epoch 2
1.4391800867099511
The running loss is:
21.851982936263084
The number of items in train is:
19
The loss for epoch 3
1.1501043650664782
The running loss is:
19.491085931658745
The number of items in train is:
19
The loss for epoch 4
1.0258466279820393
The running loss is:
20.605526842176914
The number of items in train is:
19
The loss for epoch 5
1.0845014127461534
The running loss is:
17.233258858323097
The number of items in train is:
19
The loss for epoch 6
0.9070136241222683
The running loss is:
16.62893322110176
The number of items in train is:
19
The loss for epoch 7
0.8752070116369348
The running loss is:
14.914175763726234
The number of items in train is:
19
The loss for epoch 8
0.784956619143486
The running loss is:
16.455472081899643
The number of items in train is:
19
The loss for epoch 9
0.866077477994718
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.186721
48 30755 ... 12.263892
49 30756 ... 15.433131
50 30757 ... 14.697458
51 30758 ... 13.453771
52 30759 ... 13.202712
53 30760 ... 11.757782
54 30761 ... 13.192609
55 30762 ... 13.191557
56 30763 ... 15.276033
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: x2eijjhc wandb: Agent Starting Run: ayj47mls with config: batch_size: 2 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ayj47mls
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.244433240033686
The number of items in train is:
20
The loss for epoch 0
0.9122216620016843
The running loss is:
30.7520240098238
The number of items in train is:
20
The loss for epoch 1
1.5376012004911899
The running loss is:
15.300197042524815
The number of items in train is:
20
The loss for epoch 2
0.7650098521262407
The running loss is:
12.945850990712643
The number of items in train is:
20
The loss for epoch 3
0.6472925495356321
The running loss is:
11.861743465065956
The number of items in train is:
20
The loss for epoch 4
0.5930871732532979
The running loss is:
10.992941904813051
The number of items in train is:
20
The loss for epoch 5
0.5496470952406526
The running loss is:
11.330213017761707
The number of items in train is:
20
The loss for epoch 6
0.5665106508880854
The running loss is:
9.959945164620876
The number of items in train is:
20
The loss for epoch 7
0.4979972582310438
The running loss is:
8.969771122094244
The number of items in train is:
20
The loss for epoch 8
0.44848855610471217
The running loss is:
9.06965771317482
The number of items in train is:
20
The loss for epoch 9
0.453482885658741
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.373440
48 30755 ... 10.899719
49 30756 ... 13.438485
50 30757 ... 13.496451
51 30758 ... 13.684741
52 30759 ... 14.650225
53 30760 ... 16.323957
54 30761 ... 15.094393
55 30762 ... 18.117064
56 30763 ... 19.815842
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ayj47mls wandb: Agent Starting Run: ovsyk6z6 with config: batch_size: 2 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ovsyk6z6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.05331265926361
The number of items in train is:
19
The loss for epoch 0
1.1080690873296637
The running loss is:
26.215594351291656
The number of items in train is:
19
The loss for epoch 1
1.3797681237521924
The running loss is:
14.164807230234146
The number of items in train is:
19
The loss for epoch 2
0.7455161700123235
The running loss is:
12.458269132301211
The number of items in train is:
19
The loss for epoch 3
0.6556983753842743
The running loss is:
10.816738000139594
The number of items in train is:
19
The loss for epoch 4
0.5693020000073471
The running loss is:
10.055854829028249
The number of items in train is:
19
The loss for epoch 5
0.5292555173172763
The running loss is:
9.955036200582981
The number of items in train is:
19
The loss for epoch 6
0.5239492737148937
The running loss is:
10.308482509106398
The number of items in train is:
19
The loss for epoch 7
0.5425517110055998
The running loss is:
11.734940055757761
The number of items in train is:
19
The loss for epoch 8
0.6176284239872506
The running loss is:
11.233778834342957
The number of items in train is:
19
The loss for epoch 9
0.5912515175969977
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.582728
48 30755 ... 8.345654
49 30756 ... 8.558024
50 30757 ... 7.619164
51 30758 ... 7.354745
52 30759 ... 7.545932
53 30760 ... 8.023136
54 30761 ... 7.720142
55 30762 ... 7.814631
56 30763 ... 7.839913
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ovsyk6z6 wandb: Agent Starting Run: 47aj1nt6 with config: batch_size: 2 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 47aj1nt6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.88846641778946
The number of items in train is:
19
The loss for epoch 0
0.9941298114626032
The running loss is:
32.47899427264929
The number of items in train is:
19
The loss for epoch 1
1.7094207511920678
The running loss is:
15.767253905534744
The number of items in train is:
19
The loss for epoch 2
0.8298554687123549
The running loss is:
14.174503304064274
The number of items in train is:
19
The loss for epoch 3
0.7460264896875933
The running loss is:
12.41873462498188
The number of items in train is:
19
The loss for epoch 4
0.6536176118411516
The running loss is:
11.58222109079361
The number of items in train is:
19
The loss for epoch 5
0.6095905837259794
The running loss is:
11.454800620675087
The number of items in train is:
19
The loss for epoch 6
0.6028842431934256
The running loss is:
10.778091475367546
The number of items in train is:
19
The loss for epoch 7
0.5672679723877656
The running loss is:
11.654729049652815
The number of items in train is:
19
The loss for epoch 8
0.6134067920869902
The running loss is:
11.17945396900177
The number of items in train is:
19
The loss for epoch 9
0.5883923141579879
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.925244
48 30755 ... 9.496317
49 30756 ... 9.974865
50 30757 ... 9.552412
51 30758 ... 9.775986
52 30759 ... 10.380938
53 30760 ... 11.176371
54 30761 ... 11.189506
55 30762 ... 11.451692
56 30763 ... 11.802545
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 47aj1nt6 wandb: Agent Starting Run: z76wnyg2 with config: batch_size: 2 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: z76wnyg2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.582077455706894
The number of items in train is:
20
The loss for epoch 0
0.7291038727853447
The running loss is:
36.46464059967548
The number of items in train is:
20
The loss for epoch 1
1.8232320299837739
The running loss is:
26.12745802849531
The number of items in train is:
20
The loss for epoch 2
1.3063729014247656
The running loss is:
15.507666435092688
The number of items in train is:
20
The loss for epoch 3
0.7753833217546344
The running loss is:
13.647030219435692
The number of items in train is:
20
The loss for epoch 4
0.6823515109717846
The running loss is:
12.357491072267294
The number of items in train is:
20
The loss for epoch 5
0.6178745536133647
The running loss is:
12.394297644495964
The number of items in train is:
20
The loss for epoch 6
0.6197148822247982
The running loss is:
12.705570708960295
The number of items in train is:
20
The loss for epoch 7
0.6352785354480147
The running loss is:
11.57705445960164
The number of items in train is:
20
The loss for epoch 8
0.5788527229800821
The running loss is:
11.144980823621154
The number of items in train is:
20
The loss for epoch 9
0.5572490411810577
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.404851
48 30755 ... 12.857892
49 30756 ... 12.778332
50 30757 ... 13.997534
51 30758 ... 15.216475
52 30759 ... 16.760254
53 30760 ... 17.938425
54 30761 ... 19.327490
55 30762 ... 20.218571
56 30763 ... 20.834126
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z76wnyg2 wandb: Agent Starting Run: e8mr8uwe with config: batch_size: 2 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: e8mr8uwe
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.169267039746046
The number of items in train is:
19
The loss for epoch 0
0.7457508968287393
The running loss is:
37.72724857926369
The number of items in train is:
19
The loss for epoch 1
1.9856446620665098
The running loss is:
24.199124343693256
The number of items in train is:
19
The loss for epoch 2
1.2736381233522767
The running loss is:
16.194256775081158
The number of items in train is:
19
The loss for epoch 3
0.8523293039516399
The running loss is:
13.103187538683414
The number of items in train is:
19
The loss for epoch 4
0.6896414494043902
The running loss is:
11.879832331091166
The number of items in train is:
19
The loss for epoch 5
0.6252543332153245
The running loss is:
10.950798781588674
The number of items in train is:
19
The loss for epoch 6
0.5763578306099302
The running loss is:
13.645143084228039
The number of items in train is:
19
The loss for epoch 7
0.7181654254856863
The running loss is:
10.349268220365047
The number of items in train is:
19
The loss for epoch 8
0.5446983273876341
The running loss is:
10.853834997862577
The number of items in train is:
19
The loss for epoch 9
0.5712544735717145
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.738805
48 30755 ... 9.343151
49 30756 ... 9.593056
50 30757 ... 7.918449
51 30758 ... 7.861307
52 30759 ... 8.376973
53 30760 ... 9.427421
54 30761 ... 9.342373
55 30762 ... 9.391384
56 30763 ... 9.584616
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: e8mr8uwe wandb: Agent Starting Run: s3zxbtg0 with config: batch_size: 2 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: s3zxbtg0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.212389975786209
The number of items in train is:
19
The loss for epoch 0
0.695388946094011
The running loss is:
38.891341254115105
The number of items in train is:
19
The loss for epoch 1
2.0469126975850056
The running loss is:
29.096228800714016
The number of items in train is:
19
The loss for epoch 2
1.5313804631954746
The running loss is:
16.55887496471405
The number of items in train is:
19
The loss for epoch 3
0.8715197349849501
The running loss is:
14.256739430129528
The number of items in train is:
19
The loss for epoch 4
0.7503547068489226
The running loss is:
12.388054355978966
The number of items in train is:
19
The loss for epoch 5
0.6520028608409982
The running loss is:
10.843463119119406
The number of items in train is:
19
The loss for epoch 6
0.5707085852168108
The running loss is:
10.851479662582278
The number of items in train is:
19
The loss for epoch 7
0.571130508556962
The running loss is:
10.446336604654789
The number of items in train is:
19
The loss for epoch 8
0.5498071897186732
The running loss is:
14.638044934719801
The number of items in train is:
19
The loss for epoch 9
0.7704234176168316
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.673492
48 30755 ... 10.855934
49 30756 ... 11.532489
50 30757 ... 10.763280
51 30758 ... 11.245664
52 30759 ... 12.068069
53 30760 ... 13.055459
54 30761 ... 12.345917
55 30762 ... 13.218924
56 30763 ... 13.677047
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: s3zxbtg0
wandb: Network error resolved after 0:00:14.038303, resuming normal operation.
wandb: Agent Starting Run: maiell3o with config: batch_size: 2 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: maiell3o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.558507455512881
The number of items in train is:
19
The loss for epoch 0
0.7662372345006779
The running loss is:
26.34476036950946
The number of items in train is:
19
The loss for epoch 1
1.3865663352373399
The running loss is:
24.001122549176216
The number of items in train is:
19
The loss for epoch 2
1.2632169762724323
The running loss is:
19.9936896674335
The number of items in train is:
19
The loss for epoch 3
1.0522994561807106
The running loss is:
17.85635165683925
The number of items in train is:
19
The loss for epoch 4
0.939807981938908
The running loss is:
19.134501039981842
The number of items in train is:
19
The loss for epoch 5
1.0070790021043075
The running loss is:
16.33119323849678
The number of items in train is:
19
The loss for epoch 6
0.8595364862366727
The running loss is:
17.35211842507124
The number of items in train is:
19
The loss for epoch 7
0.9132693907932231
The running loss is:
16.150467596948147
The number of items in train is:
19
The loss for epoch 8
0.850024610365692
The running loss is:
15.309038482606411
The number of items in train is:
19
The loss for epoch 9
0.8057388675056005
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.779421
48 30755 ... 8.413671
49 30756 ... 8.781001
50 30757 ... 7.955806
51 30758 ... 6.871974
52 30759 ... 6.721382
53 30760 ... 6.816398
54 30761 ... 7.125331
55 30762 ... 6.847043
56 30763 ... 6.823972
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: maiell3o wandb: Agent Starting Run: 1s257vao with config: batch_size: 2 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1s257vao
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.950616918504238
The number of items in train is:
19
The loss for epoch 0
0.8395061536054862
The running loss is:
25.045804142951965
The number of items in train is:
19
The loss for epoch 1
1.3182002180501033
The running loss is:
28.8318188264966
The number of items in train is:
19
The loss for epoch 2
1.517464148762979
The running loss is:
20.126703716814518
The number of items in train is:
19
The loss for epoch 3
1.0593001956218167
The running loss is:
17.79351157695055
The number of items in train is:
19
The loss for epoch 4
0.9365006093131868
The running loss is:
17.524609372019768
The number of items in train is:
19
The loss for epoch 5
0.922347861685251
The running loss is:
18.517031900584698
The number of items in train is:
19
The loss for epoch 6
0.9745806263465631
The running loss is:
16.52970390021801
The number of items in train is:
19
The loss for epoch 7
0.8699844158009479
The running loss is:
15.491389200091362
The number of items in train is:
19
The loss for epoch 8
0.8153362736890191
The running loss is:
16.75063694268465
The number of items in train is:
19
The loss for epoch 9
0.8816124706676132
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.217892
48 30755 ... 9.550221
49 30756 ... 10.142497
50 30757 ... 10.430239
51 30758 ... 10.068516
52 30759 ... 10.002805
53 30760 ... 10.005158
54 30761 ... 8.552078
55 30762 ... 9.498129
56 30763 ... 10.014200
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1s257vao wandb: Agent Starting Run: gdwm1mi5 with config: batch_size: 2 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: gdwm1mi5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
61.71031776070595
The number of items in train is:
20
The loss for epoch 0
3.0855158880352973
The running loss is:
22.180610413313843
The number of items in train is:
20
The loss for epoch 1
1.109030520665692
The running loss is:
23.172951824963093
The number of items in train is:
20
The loss for epoch 2
1.1586475912481546
The running loss is:
18.153760477900505
The number of items in train is:
20
The loss for epoch 3
0.9076880238950252
The running loss is:
17.846179999411106
The number of items in train is:
20
The loss for epoch 4
0.8923089999705553
The running loss is:
16.6478939242661
The number of items in train is:
20
The loss for epoch 5
0.832394696213305
The running loss is:
22.557837568223476
The number of items in train is:
20
The loss for epoch 6
1.1278918784111738
The running loss is:
21.72391752898693
The number of items in train is:
20
The loss for epoch 7
1.0861958764493465
The running loss is:
18.882404036819935
The number of items in train is:
20
The loss for epoch 8
0.9441202018409968
The running loss is:
16.341234251856804
The number of items in train is:
20
The loss for epoch 9
0.8170617125928402
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.028555
48 30755 ... 10.223789
49 30756 ... 10.591708
50 30757 ... 12.109409
51 30758 ... 10.868167
52 30759 ... 10.671272
53 30760 ... 10.249063
54 30761 ... 9.258160
55 30762 ... 10.242380
56 30763 ... 10.538944
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gdwm1mi5 wandb: Agent Starting Run: w0lg5o37 with config: batch_size: 2 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: w0lg5o37
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
41.49641283042729
The number of items in train is:
19
The loss for epoch 0
2.1840217279172256
The running loss is:
19.970189593732357
The number of items in train is:
19
The loss for epoch 1
1.0510626101964398
The running loss is:
24.242495357990265
The number of items in train is:
19
The loss for epoch 2
1.275920808315277
The running loss is:
22.579135298728943
The number of items in train is:
19
The loss for epoch 3
1.1883755420383655
The running loss is:
20.04605047404766
The number of items in train is:
19
The loss for epoch 4
1.0550552881077717
The running loss is:
19.928060449659824
The number of items in train is:
19
The loss for epoch 5
1.0488452868242013
The running loss is:
20.826875373721123
The number of items in train is:
19
The loss for epoch 6
1.0961513354590064
The running loss is:
17.959194883704185
The number of items in train is:
19
The loss for epoch 7
0.9452207833528519
The running loss is:
19.45036144554615
The number of items in train is:
19
The loss for epoch 8
1.0237032339761132
The running loss is:
19.660989113152027
The number of items in train is:
19
The loss for epoch 9
1.034788900692212
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.188835
48 30755 ... 10.382625
49 30756 ... 10.807488
50 30757 ... 10.160336
51 30758 ... 10.386367
52 30759 ... 10.618712
53 30760 ... 10.833608
54 30761 ... 10.601640
55 30762 ... 10.604479
56 30763 ... 10.606827
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: w0lg5o37 wandb: Agent Starting Run: y5e4tm4j with config: batch_size: 2 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: y5e4tm4j
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
52.42885746061802
The number of items in train is:
19
The loss for epoch 0
2.7594135505588433
The running loss is:
24.32117458432913
The number of items in train is:
19
The loss for epoch 1
1.2800618202278489
The running loss is:
30.122551828622818
The number of items in train is:
19
The loss for epoch 2
1.585397464664359
The running loss is:
20.29300230368972
The number of items in train is:
19
The loss for epoch 3
1.0680527528257746
The running loss is:
18.420647092163563
The number of items in train is:
19
The loss for epoch 4
0.9695077416928191
The running loss is:
17.05812880396843
The number of items in train is:
19
The loss for epoch 5
0.8977962528404436
The running loss is:
17.698757626116276
The number of items in train is:
19
The loss for epoch 6
0.9315135592692777
The running loss is:
15.643727265298367
The number of items in train is:
19
The loss for epoch 7
0.8233540665946508
The running loss is:
17.527575224637985
The number of items in train is:
19
The loss for epoch 8
0.9225039591914729
The running loss is:
13.784894995391369
The number of items in train is:
19
The loss for epoch 9
0.7255207892311247
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.834595
48 30755 ... 10.046051
49 30756 ... 10.053276
50 30757 ... 9.926423
51 30758 ... 9.764924
52 30759 ... 10.050706
53 30760 ... 10.521197
54 30761 ... 10.678264
55 30762 ... 10.684898
56 30763 ... 10.683672
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y5e4tm4j wandb: Agent Starting Run: yw3yr804 with config: batch_size: 2 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yw3yr804
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.151611974462867
The number of items in train is:
19
The loss for epoch 0
1.2185058933927824
The running loss is:
24.21296002715826
The number of items in train is:
19
The loss for epoch 1
1.2743663172188557
The running loss is:
14.147806107997894
The number of items in train is:
19
The loss for epoch 2
0.7446213741051523
The running loss is:
11.688982851803303
The number of items in train is:
19
The loss for epoch 3
0.6152096237791213
The running loss is:
11.189231188967824
The number of items in train is:
19
The loss for epoch 4
0.588906904682517
The running loss is:
10.066100733820349
The number of items in train is:
19
The loss for epoch 5
0.5297947754642289
The running loss is:
9.523541389033198
The number of items in train is:
19
The loss for epoch 6
0.5012390204754315
The running loss is:
10.919814303517342
The number of items in train is:
19
The loss for epoch 7
0.5747270686061758
The running loss is:
9.636709606507793
The number of items in train is:
19
The loss for epoch 8
0.5071952424477786
The running loss is:
10.427344053983688
The number of items in train is:
19
The loss for epoch 9
0.5488075817886152
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.963048
48 30755 ... 7.921071
49 30756 ... 7.497608
50 30757 ... 7.718255
51 30758 ... 7.543673
52 30759 ... 7.132375
53 30760 ... 6.909460
54 30761 ... 6.758762
55 30762 ... 6.579365
56 30763 ... 6.642597
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yw3yr804 wandb: Agent Starting Run: sfugzwzq with config: batch_size: 2 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sfugzwzq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.778223261237144
The number of items in train is:
19
The loss for epoch 0
1.0409591190124814
The running loss is:
32.143462881445885
The number of items in train is:
19
The loss for epoch 1
1.6917612042866255
The running loss is:
16.04269601404667
The number of items in train is:
19
The loss for epoch 2
0.8443524217919299
The running loss is:
14.474790960550308
The number of items in train is:
19
The loss for epoch 3
0.7618311031868583
The running loss is:
12.12663073092699
The number of items in train is:
19
The loss for epoch 4
0.6382437226803679
The running loss is:
11.022467166185379
The number of items in train is:
19
The loss for epoch 5
0.5801298508518621
The running loss is:
10.14216186851263
The number of items in train is:
19
The loss for epoch 6
0.5337979930796122
The running loss is:
10.681325320154428
The number of items in train is:
19
The loss for epoch 7
0.5621750168502331
The running loss is:
11.375485748052597
The number of items in train is:
19
The loss for epoch 8
0.5987097762132946
The running loss is:
9.121527703478932
The number of items in train is:
19
The loss for epoch 9
0.4800804054462596
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.768013
48 30755 ... 10.675665
49 30756 ... 9.865327
50 30757 ... 11.112760
51 30758 ... 11.969445
52 30759 ... 13.426899
53 30760 ... 15.257719
54 30761 ... 15.186352
55 30762 ... 14.411901
56 30763 ... 15.222851
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sfugzwzq wandb: Agent Starting Run: zorqe447 with config: batch_size: 2 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: zorqe447
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.629800878465176
The number of items in train is:
18
The loss for epoch 0
1.0905444932480652
The running loss is:
25.255747854709625
The number of items in train is:
18
The loss for epoch 1
1.4030971030394237
The running loss is:
15.05001075565815
The number of items in train is:
18
The loss for epoch 2
0.836111708647675
The running loss is:
13.016271352767944
The number of items in train is:
18
The loss for epoch 3
0.7231261862648858
The running loss is:
12.27754981070757
The number of items in train is:
18
The loss for epoch 4
0.682086100594865
The running loss is:
11.391240701079369
The number of items in train is:
18
The loss for epoch 5
0.6328467056155205
The running loss is:
11.72953286767006
The number of items in train is:
18
The loss for epoch 6
0.6516407148705589
The running loss is:
11.442858997732401
The number of items in train is:
18
The loss for epoch 7
0.6357143887629112
The running loss is:
12.431051224470139
The number of items in train is:
18
The loss for epoch 8
0.6906139569150077
The running loss is:
11.048863388597965
The number of items in train is:
18
The loss for epoch 9
0.6138257438109981
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.032237
48 30755 ... 12.643246
49 30756 ... 6.603610
50 30757 ... 6.592432
51 30758 ... 4.413502
52 30759 ... 3.218659
53 30760 ... 2.618341
54 30761 ... 1.748638
55 30762 ... 1.638597
56 30763 ... 0.533958
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zorqe447 wandb: Agent Starting Run: 3un1inbj with config: batch_size: 2 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3un1inbj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.982001293450594
The number of items in train is:
19
The loss for epoch 0
0.7885263838658207
The running loss is:
33.174809351563454
The number of items in train is:
19
The loss for epoch 1
1.7460425974507081
The running loss is:
21.882377948611975
The number of items in train is:
19
The loss for epoch 2
1.151704102558525
The running loss is:
15.876857874915004
The number of items in train is:
19
The loss for epoch 3
0.8356240986797371
The running loss is:
13.362504370510578
The number of items in train is:
19
The loss for epoch 4
0.703289703711083
The running loss is:
10.210133947432041
The number of items in train is:
19
The loss for epoch 5
0.5373754709174758
The running loss is:
10.241281794384122
The number of items in train is:
19
The loss for epoch 6
0.5390148312833748
The running loss is:
9.936604705639184
The number of items in train is:
19
The loss for epoch 7
0.5229791950336412
The running loss is:
11.438727487111464
The number of items in train is:
19
The loss for epoch 8
0.6020382887953403
The running loss is:
12.369946470251307
The number of items in train is:
19
The loss for epoch 9
0.651049814223753
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.245392
48 30755 ... 14.129043
49 30756 ... 13.174330
50 30757 ... 13.520782
51 30758 ... 14.763544
52 30759 ... 15.160839
53 30760 ... 15.549007
54 30761 ... 15.544765
55 30762 ... 15.403012
56 30763 ... 15.567816
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3un1inbj wandb: Agent Starting Run: or2ftbf5 with config: batch_size: 2 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: or2ftbf5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.938185892999172
The number of items in train is:
19
The loss for epoch 0
0.7335887312104827
The running loss is:
34.40718472003937
The number of items in train is:
19
The loss for epoch 1
1.8109044589494403
The running loss is:
27.414366364479065
The number of items in train is:
19
The loss for epoch 2
1.4428613876041614
The running loss is:
16.21256609261036
The number of items in train is:
19
The loss for epoch 3
0.8532929522426504
The running loss is:
13.721442848443985
The number of items in train is:
19
The loss for epoch 4
0.7221812025496834
The running loss is:
11.4379528388381
The number of items in train is:
19
The loss for epoch 5
0.6019975178335842
The running loss is:
9.260038580745459
The number of items in train is:
19
The loss for epoch 6
0.48737045161818204
The running loss is:
12.055675242096186
The number of items in train is:
19
The loss for epoch 7
0.6345092232682203
The running loss is:
10.1099742539227
The number of items in train is:
19
The loss for epoch 8
0.5321039081011948
The running loss is:
11.101317666471004
The number of items in train is:
19
The loss for epoch 9
0.5842798771826845
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.715038
48 30755 ... 13.290008
49 30756 ... 10.847966
50 30757 ... 12.697416
51 30758 ... 13.276269
52 30759 ... 14.771571
53 30760 ... 17.032900
54 30761 ... 16.310585
55 30762 ... 14.025554
56 30763 ... 16.796951
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: or2ftbf5 wandb: Agent Starting Run: qyjq7c0a with config: batch_size: 2 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qyjq7c0a
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.219057638198137
The number of items in train is:
18
The loss for epoch 0
0.7899476465665631
The running loss is:
32.766083881258965
The number of items in train is:
18
The loss for epoch 1
1.8203379934032757
The running loss is:
22.88953396677971
The number of items in train is:
18
The loss for epoch 2
1.2716407759322061
The running loss is:
15.694544300436974
The number of items in train is:
18
The loss for epoch 3
0.871919127802054
The running loss is:
13.966531410813332
The number of items in train is:
18
The loss for epoch 4
0.7759184117118517
The running loss is:
11.931890279054642
The number of items in train is:
18
The loss for epoch 5
0.6628827932808135
The running loss is:
11.502507656812668
The number of items in train is:
18
The loss for epoch 6
0.6390282031562593
The running loss is:
10.604379296302795
The number of items in train is:
18
The loss for epoch 7
0.589132183127933
The running loss is:
12.21282433718443
The number of items in train is:
18
The loss for epoch 8
0.6784902409546905
The running loss is:
11.869370594620705
The number of items in train is:
18
The loss for epoch 9
0.6594094774789281
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.175922
48 30755 ... 10.767483
49 30756 ... 4.415483
50 30757 ... 6.104957
51 30758 ... 4.019737
52 30759 ... 3.290065
53 30760 ... 3.420416
54 30761 ... 1.564515
55 30762 ... -3.665913
56 30763 ... -0.584266
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qyjq7c0a wandb: Agent Starting Run: e7l2v3n1 with config: batch_size: 2 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: e7l2v3n1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.939907671883702
The number of items in train is:
19
The loss for epoch 0
0.7863109300991422
The running loss is:
27.58423702418804
The number of items in train is:
19
The loss for epoch 1
1.451801948641476
The running loss is:
21.350735876709223
The number of items in train is:
19
The loss for epoch 2
1.1237229408794327
The running loss is:
22.028746308758855
The number of items in train is:
19
The loss for epoch 3
1.1594077004609924
The running loss is:
20.440568597987294
The number of items in train is:
19
The loss for epoch 4
1.0758193998940682
The running loss is:
18.65727076679468
The number of items in train is:
19
The loss for epoch 5
0.9819616193049833
The running loss is:
19.96857689321041
The number of items in train is:
19
The loss for epoch 6
1.0509777312216007
The running loss is:
18.768428467214108
The number of items in train is:
19
The loss for epoch 7
0.9878120245902162
The running loss is:
18.98760063573718
The number of items in train is:
19
The loss for epoch 8
0.9993474018809042
The running loss is:
18.08189932629466
The number of items in train is:
19
The loss for epoch 9
0.9516789119102453
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.355700
48 30755 ... 11.807974
49 30756 ... 11.397798
50 30757 ... 11.411679
51 30758 ... 11.352333
52 30759 ... 11.283925
53 30760 ... 11.236071
54 30761 ... 11.371363
55 30762 ... 11.656288
56 30763 ... 11.443694
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: e7l2v3n1 wandb: Agent Starting Run: tzqyy8oc with config: batch_size: 2 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: tzqyy8oc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.767386704683304
The number of items in train is:
19
The loss for epoch 0
0.882494037088595
The running loss is:
23.7237149477005
The number of items in train is:
19
The loss for epoch 1
1.2486165761947632
The running loss is:
21.810965567827225
The number of items in train is:
19
The loss for epoch 2
1.147945556201433
The running loss is:
21.628697000443935
The number of items in train is:
19
The loss for epoch 3
1.1383524737075756
The running loss is:
18.608572021126747
The number of items in train is:
19
The loss for epoch 4
0.9793985274277235
The running loss is:
17.807227961719036
The number of items in train is:
19
The loss for epoch 5
0.937222524301002
The running loss is:
16.818491958081722
The number of items in train is:
19
The loss for epoch 6
0.885183787267459
The running loss is:
17.390442237257957
The number of items in train is:
19
The loss for epoch 7
0.9152864335398925
The running loss is:
16.504042580723763
The number of items in train is:
19
The loss for epoch 8
0.8686338200380928
The running loss is:
14.063714668154716
The number of items in train is:
19
The loss for epoch 9
0.7401955088502482
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 17.209160
48 30755 ... 21.750385
49 30756 ... 16.280861
50 30757 ... 16.302153
51 30758 ... 18.620329
52 30759 ... 20.607368
53 30760 ... 19.939861
54 30761 ... 21.928680
55 30762 ... 21.918089
56 30763 ... 22.155098
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tzqyy8oc wandb: Agent Starting Run: y09gepr6 with config: batch_size: 2 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: y09gepr6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.607820570468903
The number of items in train is:
18
The loss for epoch 0
0.8671011428038279
The running loss is:
21.899810507893562
The number of items in train is:
18
The loss for epoch 1
1.2166561393274202
The running loss is:
23.761934000998735
The number of items in train is:
18
The loss for epoch 2
1.3201074444999297
The running loss is:
16.91294802725315
The number of items in train is:
18
The loss for epoch 3
0.9396082237362862
The running loss is:
18.267082534730434
The number of items in train is:
18
The loss for epoch 4
1.0148379185961351
The running loss is:
17.08760144561529
The number of items in train is:
18
The loss for epoch 5
0.9493111914230717
The running loss is:
15.896970629692078
The number of items in train is:
18
The loss for epoch 6
0.8831650349828932
The running loss is:
17.839499786496162
The number of items in train is:
18
The loss for epoch 7
0.9910833214720091
The running loss is:
16.226146705448627
The number of items in train is:
18
The loss for epoch 8
0.901452594747146
The running loss is:
15.652418322861195
The number of items in train is:
18
The loss for epoch 9
0.8695787957145108
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.320057
48 30755 ... 13.447205
49 30756 ... 9.804661
50 30757 ... 9.939509
51 30758 ... 10.391244
52 30759 ... 10.271468
53 30760 ... 10.242510
54 30761 ... 9.979496
55 30762 ... 9.834205
56 30763 ... 9.926790
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y09gepr6 wandb: Agent Starting Run: cbzex9pt with config: batch_size: 2 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cbzex9pt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
47.5149762108922
The number of items in train is:
19
The loss for epoch 0
2.500788221625905
The running loss is:
22.905585899949074
The number of items in train is:
19
The loss for epoch 1
1.2055571526288986
The running loss is:
24.01019530929625
The number of items in train is:
19
The loss for epoch 2
1.2636944899629605
The running loss is:
23.0567737929523
The number of items in train is:
19
The loss for epoch 3
1.213514410155384
The running loss is:
26.211633875966072
The number of items in train is:
19
The loss for epoch 4
1.3795596776824248
The running loss is:
20.059789837221615
The number of items in train is:
19
The loss for epoch 5
1.0557784124853482
The running loss is:
18.259545739740133
The number of items in train is:
19
The loss for epoch 6
0.9610287231442175
The running loss is:
20.72789303958416
The number of items in train is:
19
The loss for epoch 7
1.090941738925482
The running loss is:
23.105668414384127
The number of items in train is:
19
The loss for epoch 8
1.216087811283375
The running loss is:
20.80936250090599
The number of items in train is:
19
The loss for epoch 9
1.0952296053108417
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.992377
48 30755 ... 10.127301
49 30756 ... 10.745222
50 30757 ... 10.946898
51 30758 ... 11.551901
52 30759 ... 11.699575
53 30760 ... 11.576552
54 30761 ... 11.900595
55 30762 ... 10.091677
56 30763 ... 11.018733
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cbzex9pt wandb: Agent Starting Run: y92u1zia with config: batch_size: 2 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: y92u1zia
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
60.506285328418016
The number of items in train is:
19
The loss for epoch 0
3.1845413330746326
The running loss is:
22.747136116027832
The number of items in train is:
19
The loss for epoch 1
1.1972176903172542
The running loss is:
22.141358107328415
The number of items in train is:
19
The loss for epoch 2
1.1653346372278113
The running loss is:
20.66910433769226
The number of items in train is:
19
The loss for epoch 3
1.0878475967206453
The running loss is:
21.232126966118813
The number of items in train is:
19
The loss for epoch 4
1.1174803666378323
The running loss is:
19.210107535123825
The number of items in train is:
19
The loss for epoch 5
1.0110582913223065
The running loss is:
16.590289562940598
The number of items in train is:
19
The loss for epoch 6
0.8731731348916104
The running loss is:
15.67080619931221
The number of items in train is:
19
The loss for epoch 7
0.8247792736480111
The running loss is:
14.635391503572464
The number of items in train is:
19
The loss for epoch 8
0.7702837633459192
The running loss is:
12.694482833147049
The number of items in train is:
19
The loss for epoch 9
0.668130675428792
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.763491
48 30755 ... 12.762318
49 30756 ... 10.953236
50 30757 ... 11.089784
51 30758 ... 10.986698
52 30759 ... 11.406321
53 30760 ... 12.214860
54 30761 ... 12.406092
55 30762 ... 12.407260
56 30763 ... 12.401293
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y92u1zia wandb: Agent Starting Run: 7tyjl8ck with config: batch_size: 2 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 7tyjl8ck
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.1738221719861
The number of items in train is:
18
The loss for epoch 0
2.8429901206658945
The running loss is:
20.108996018767357
The number of items in train is:
18
The loss for epoch 1
1.1171664454870753
The running loss is:
20.94754420220852
The number of items in train is:
18
The loss for epoch 2
1.163752455678251
The running loss is:
19.241921558976173
The number of items in train is:
18
The loss for epoch 3
1.068995642165343
The running loss is:
19.614308521151543
The number of items in train is:
18
The loss for epoch 4
1.0896838067306414
The running loss is:
18.551492542028427
The number of items in train is:
18
The loss for epoch 5
1.0306384745571349
The running loss is:
17.22895458340645
The number of items in train is:
18
The loss for epoch 6
0.9571641435225805
The running loss is:
16.789826542139053
The number of items in train is:
18
The loss for epoch 7
0.9327681412299474
The running loss is:
15.875566244125366
The number of items in train is:
18
The loss for epoch 8
0.8819759024514092
The running loss is:
16.926526993513107
The number of items in train is:
18
The loss for epoch 9
0.9403626107507281
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.480230
48 30755 ... 13.879719
49 30756 ... 13.271286
50 30757 ... 13.021132
51 30758 ... 13.106910
52 30759 ... 13.234471
53 30760 ... 13.401170
54 30761 ... 13.149764
55 30762 ... 12.935968
56 30763 ... 13.315945
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7tyjl8ck wandb: Agent Starting Run: xtufua36 with config: batch_size: 2 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: xtufua36
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.662442736327648
The number of items in train is:
19
The loss for epoch 0
0.9822338282277709
The running loss is:
32.4536609929055
The number of items in train is:
19
The loss for epoch 1
1.7080874206792367
The running loss is:
16.78804411087185
The number of items in train is:
19
The loss for epoch 2
0.8835812689932553
The running loss is:
13.13648857921362
The number of items in train is:
19
The loss for epoch 3
0.6913941357480852
The running loss is:
11.167816616594791
The number of items in train is:
19
The loss for epoch 4
0.5877798219260416
The running loss is:
9.475702971220016
The number of items in train is:
19
The loss for epoch 5
0.4987212090115798
The running loss is:
9.611646829172969
The number of items in train is:
19
The loss for epoch 6
0.5058761489038405
The running loss is:
8.849040357898048
The number of items in train is:
19
The loss for epoch 7
0.4657389662051604
The running loss is:
10.830722641199827
The number of items in train is:
19
The loss for epoch 8
0.5700380337473593
The running loss is:
8.893724239896983
The number of items in train is:
19
The loss for epoch 9
0.46809074946826223
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.932547
48 30755 ... 13.332523
49 30756 ... 16.218235
50 30757 ... 13.282401
51 30758 ... 13.402158
52 30759 ... 13.695475
53 30760 ... 16.110184
54 30761 ... 15.520673
55 30762 ... 16.442516
56 30763 ... 18.135046
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xtufua36 wandb: Agent Starting Run: 6q31wbqt with config: batch_size: 2 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 6q31wbqt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.809781923890114
The number of items in train is:
18
The loss for epoch 0
0.9338767735494508
The running loss is:
31.100095892790705
The number of items in train is:
18
The loss for epoch 1
1.7277831051550392
The running loss is:
14.82688376866281
The number of items in train is:
18
The loss for epoch 2
0.8237157649257116
The running loss is:
12.923846289515495
The number of items in train is:
18
The loss for epoch 3
0.7179914605286386
The running loss is:
10.198259711265564
The number of items in train is:
18
The loss for epoch 4
0.566569983959198
The running loss is:
9.777777466922998
The number of items in train is:
18
The loss for epoch 5
0.5432098592735
The running loss is:
8.726226492086425
The number of items in train is:
18
The loss for epoch 6
0.4847903606714681
The running loss is:
9.029325045645237
The number of items in train is:
18
The loss for epoch 7
0.5016291692025132
The running loss is:
9.306042216718197
The number of items in train is:
18
The loss for epoch 8
0.5170023453732332
The running loss is:
9.190385576337576
The number of items in train is:
18
The loss for epoch 9
0.5105769764631987
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.777914
48 30755 ... 12.234770
49 30756 ... 12.906726
50 30757 ... 9.613279
51 30758 ... 10.035604
52 30759 ... 10.181870
53 30760 ... 11.437014
54 30761 ... 11.337413
55 30762 ... 11.397779
56 30763 ... 11.538319
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6q31wbqt wandb: Agent Starting Run: piuk49km with config: batch_size: 2 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: piuk49km
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.207939341664314
The number of items in train is:
18
The loss for epoch 0
1.067107741203573
The running loss is:
26.95139818638563
The number of items in train is:
18
The loss for epoch 1
1.4972998992436461
The running loss is:
15.8444182574749
The number of items in train is:
18
The loss for epoch 2
0.8802454587486055
The running loss is:
13.982900321483612
The number of items in train is:
18
The loss for epoch 3
0.7768277956379784
The running loss is:
12.15248690545559
The number of items in train is:
18
The loss for epoch 4
0.6751381614141994
The running loss is:
11.28390198200941
The number of items in train is:
18
The loss for epoch 5
0.6268834434449673
The running loss is:
11.802641343325377
The number of items in train is:
18
The loss for epoch 6
0.6557022968514098
The running loss is:
10.794923435896635
The number of items in train is:
18
The loss for epoch 7
0.5997179686609242
The running loss is:
11.76518764346838
The number of items in train is:
18
The loss for epoch 8
0.6536215357482433
The running loss is:
11.923004761338234
The number of items in train is:
18
The loss for epoch 9
0.6623891534076797
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.162495
48 30755 ... 7.129919
49 30756 ... 9.476668
50 30757 ... 4.542667
51 30758 ... 4.005393
52 30759 ... 0.559879
53 30760 ... -1.379381
54 30761 ... -2.445561
55 30762 ... -2.441918
56 30763 ... -2.303915
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: piuk49km wandb: Agent Starting Run: zh6e9hk0 with config: batch_size: 2 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: zh6e9hk0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.526742728427052
The number of items in train is:
19
The loss for epoch 0
0.7645654067593185
The running loss is:
30.84717154005193
The number of items in train is:
19
The loss for epoch 1
1.6235353442132596
The running loss is:
26.77706977725029
The number of items in train is:
19
The loss for epoch 2
1.4093194619605416
The running loss is:
15.642113384790719
The number of items in train is:
19
The loss for epoch 3
0.823269125515301
The running loss is:
11.526011761277914
The number of items in train is:
19
The loss for epoch 4
0.6066321979619955
The running loss is:
10.011572066694498
The number of items in train is:
19
The loss for epoch 5
0.5269248456154999
The running loss is:
10.000060603022575
The number of items in train is:
19
The loss for epoch 6
0.5263189791064513
The running loss is:
8.50434441305697
The number of items in train is:
19
The loss for epoch 7
0.44759707437141943
The running loss is:
9.07707198522985
The number of items in train is:
19
The loss for epoch 8
0.47774063080157103
The running loss is:
7.321829241234809
The number of items in train is:
19
The loss for epoch 9
0.3853594337492005
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.666120
48 30755 ... 9.921270
49 30756 ... 16.465700
50 30757 ... 12.533557
51 30758 ... 12.186483
52 30759 ... 11.201939
53 30760 ... 10.682373
54 30761 ... 9.363009
55 30762 ... 11.541510
56 30763 ... 17.120123
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zh6e9hk0 wandb: Agent Starting Run: 2p9wj7al with config: batch_size: 2 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2p9wj7al
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.093412643298507
The number of items in train is:
18
The loss for epoch 0
0.6718562579610281
The running loss is:
31.850913926959038
The number of items in train is:
18
The loss for epoch 1
1.769495218164391
The running loss is:
24.548495411872864
The number of items in train is:
18
The loss for epoch 2
1.3638053006596036
The running loss is:
14.259857133030891
The number of items in train is:
18
The loss for epoch 3
0.7922142851683829
The running loss is:
11.60143318399787
The number of items in train is:
18
The loss for epoch 4
0.6445240657776594
The running loss is:
10.158630147576332
The number of items in train is:
18
The loss for epoch 5
0.5643683415320184
The running loss is:
10.024041716009378
The number of items in train is:
18
The loss for epoch 6
0.5568912064449655
The running loss is:
10.450636763125658
The number of items in train is:
18
The loss for epoch 7
0.5805909312847588
The running loss is:
12.88908988237381
The number of items in train is:
18
The loss for epoch 8
0.7160605490207672
The running loss is:
9.649638891220093
The number of items in train is:
18
The loss for epoch 9
0.5360910495122274
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.349866
48 30755 ... 12.485463
49 30756 ... 14.009510
50 30757 ... 5.725533
51 30758 ... 5.484777
52 30759 ... 4.383102
53 30760 ... 4.634890
54 30761 ... 4.904810
55 30762 ... 5.281286
56 30763 ... 0.289950
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2p9wj7al wandb: Agent Starting Run: miih8z8l with config: batch_size: 2 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: miih8z8l
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.902076788246632
The number of items in train is:
18
The loss for epoch 0
0.772337599347035
The running loss is:
30.734783306717873
The number of items in train is:
18
The loss for epoch 1
1.7074879614843264
The running loss is:
24.098938152194023
The number of items in train is:
18
The loss for epoch 2
1.3388298973441124
The running loss is:
16.15599799156189
The number of items in train is:
18
The loss for epoch 3
0.8975554439756606
The running loss is:
14.88480393588543
The number of items in train is:
18
The loss for epoch 4
0.8269335519936349
The running loss is:
13.353974744677544
The number of items in train is:
18
The loss for epoch 5
0.7418874858154191
The running loss is:
13.012045174837112
The number of items in train is:
18
The loss for epoch 6
0.7228913986020618
The running loss is:
11.28533148765564
The number of items in train is:
18
The loss for epoch 7
0.6269628604253134
The running loss is:
11.091172754764557
The number of items in train is:
18
The loss for epoch 8
0.6161762641535865
The running loss is:
14.631795093417168
The number of items in train is:
18
The loss for epoch 9
0.8128775051898427
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.164349
48 30755 ... 9.647461
49 30756 ... 11.834938
50 30757 ... 8.905302
51 30758 ... 8.214365
52 30759 ... 8.132830
53 30760 ... 8.303577
54 30761 ... 7.712473
55 30762 ... 8.126958
56 30763 ... 9.033283
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: miih8z8l wandb: Agent Starting Run: 3x0ouo97 with config: batch_size: 2 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3x0ouo97
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.53110232204199
The number of items in train is:
19
The loss for epoch 0
1.080584332739052
The running loss is:
22.649866599589586
The number of items in train is:
19
The loss for epoch 1
1.1920982420836623
The running loss is:
20.07614903151989
The number of items in train is:
19
The loss for epoch 2
1.0566394227115732
The running loss is:
21.142045558430254
The number of items in train is:
19
The loss for epoch 3
1.1127392399173819
The running loss is:
14.569156531244516
The number of items in train is:
19
The loss for epoch 4
0.766797712170764
The running loss is:
13.339449528604746
The number of items in train is:
19
The loss for epoch 5
0.7020762909791971
The running loss is:
11.777572210878134
The number of items in train is:
19
The loss for epoch 6
0.619872221625165
The running loss is:
16.930491030216217
The number of items in train is:
19
The loss for epoch 7
0.8910784752745378
The running loss is:
13.112162977457047
The number of items in train is:
19
The loss for epoch 8
0.6901138409187919
The running loss is:
11.765430979430676
The number of items in train is:
19
The loss for epoch 9
0.6192332094437197
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.341544
48 30755 ... 13.739527
49 30756 ... 16.690649
50 30757 ... 11.087149
51 30758 ... 10.845184
52 30759 ... 10.669495
53 30760 ... 11.297999
54 30761 ... 10.704900
55 30762 ... 11.647568
56 30763 ... 6.396082
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3x0ouo97 wandb: Agent Starting Run: 8zvt4j88 with config: batch_size: 2 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 8zvt4j88
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.847276613116264
The number of items in train is:
18
The loss for epoch 0
0.9359598118397925
The running loss is:
22.086317025125027
The number of items in train is:
18
The loss for epoch 1
1.2270176125069459
The running loss is:
21.75656918808818
The number of items in train is:
18
The loss for epoch 2
1.208698288227121
The running loss is:
20.252290658652782
The number of items in train is:
18
The loss for epoch 3
1.1251272588140435
The running loss is:
17.040222689509392
The number of items in train is:
18
The loss for epoch 4
0.9466790383060774
The running loss is:
16.73467853665352
The number of items in train is:
18
The loss for epoch 5
0.9297043631474177
The running loss is:
15.817666858434677
The number of items in train is:
18
The loss for epoch 6
0.8787592699130377
The running loss is:
17.491646096110344
The number of items in train is:
18
The loss for epoch 7
0.9717581164505746
The running loss is:
14.300822883844376
The number of items in train is:
18
The loss for epoch 8
0.7944901602135764
The running loss is:
14.148024834692478
The number of items in train is:
18
The loss for epoch 9
0.7860013797051377
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.154796
48 30755 ... 9.414880
49 30756 ... 9.848639
50 30757 ... 7.001806
51 30758 ... 7.194446
52 30759 ... 6.755281
53 30760 ... 7.121027
54 30761 ... 6.964331
55 30762 ... 6.581292
56 30763 ... 5.964928
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8zvt4j88 wandb: Agent Starting Run: codhaw7z with config: batch_size: 2 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: codhaw7z
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.63626703619957
The number of items in train is:
18
The loss for epoch 0
0.9242370575666428
The running loss is:
21.218304097652435
The number of items in train is:
18
The loss for epoch 1
1.1787946720918019
The running loss is:
20.293749123811722
The number of items in train is:
18
The loss for epoch 2
1.127430506878429
The running loss is:
19.309033408761024
The number of items in train is:
18
The loss for epoch 3
1.0727240782645013
The running loss is:
17.63574704527855
The number of items in train is:
18
The loss for epoch 4
0.9797637247376971
The running loss is:
16.501740634441376
The number of items in train is:
18
The loss for epoch 5
0.9167633685800765
The running loss is:
16.07330948114395
The number of items in train is:
18
The loss for epoch 6
0.8929616378413306
The running loss is:
14.988985002040863
The number of items in train is:
18
The loss for epoch 7
0.8327213890022702
The running loss is:
15.27691513299942
The number of items in train is:
18
The loss for epoch 8
0.8487175073888567
The running loss is:
15.855083525180817
The number of items in train is:
18
The loss for epoch 9
0.8808379736211565
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.524234
48 30755 ... 11.504997
49 30756 ... 11.519807
50 30757 ... 11.319865
51 30758 ... 11.301481
52 30759 ... 11.427913
53 30760 ... 11.322249
54 30761 ... 11.377673
55 30762 ... 11.367601
56 30763 ... 11.353683
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: codhaw7z wandb: Agent Starting Run: 3tphqgn9 with config: batch_size: 2 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3tphqgn9
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
89.16724638454616
The number of items in train is:
19
The loss for epoch 0
4.693012967607693
The running loss is:
26.253339409828186
The number of items in train is:
19
The loss for epoch 1
1.381754705780431
The running loss is:
22.28419649042189
The number of items in train is:
19
The loss for epoch 2
1.17285244686431
The running loss is:
20.892348155379295
The number of items in train is:
19
The loss for epoch 3
1.0995972713357525
The running loss is:
16.460732923820615
The number of items in train is:
19
The loss for epoch 4
0.8663543644116113
The running loss is:
18.3472553268075
The number of items in train is:
19
The loss for epoch 5
0.9656450172003946
The running loss is:
15.07598640746437
The number of items in train is:
19
The loss for epoch 6
0.7934729688139143
The running loss is:
17.23325503244996
The number of items in train is:
19
The loss for epoch 7
0.9070134227605242
The running loss is:
16.722626268863678
The number of items in train is:
19
The loss for epoch 8
0.8801382246770357
The running loss is:
13.728390574455261
The number of items in train is:
19
The loss for epoch 9
0.7225468723397506
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.590704
48 30755 ... 13.399076
49 30756 ... 13.402116
50 30757 ... 12.507936
51 30758 ... 12.685381
52 30759 ... 12.882812
53 30760 ... 12.423203
54 30761 ... 12.690681
55 30762 ... 12.690515
56 30763 ... 12.690374
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3tphqgn9 wandb: Agent Starting Run: xuut9khr with config: batch_size: 2 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: xuut9khr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
68.00627230107784
The number of items in train is:
18
The loss for epoch 0
3.778126238948769
The running loss is:
19.79006164520979
The number of items in train is:
18
The loss for epoch 1
1.0994478691783216
The running loss is:
17.850837409496307
The number of items in train is:
18
The loss for epoch 2
0.9917131894164615
The running loss is:
24.54628086835146
The number of items in train is:
18
The loss for epoch 3
1.36368227046397
The running loss is:
21.807621747255325
The number of items in train is:
18
The loss for epoch 4
1.2115345415141847
The running loss is:
16.156769186258316
The number of items in train is:
18
The loss for epoch 5
0.897598288125462
The running loss is:
15.531101047992706
The number of items in train is:
18
The loss for epoch 6
0.8628389471107059
The running loss is:
15.293164731934667
The number of items in train is:
18
The loss for epoch 7
0.8496202628852593
The running loss is:
14.162357330322266
The number of items in train is:
18
The loss for epoch 8
0.7867976294623481
The running loss is:
13.308439128100872
The number of items in train is:
18
The loss for epoch 9
0.7393577293389373
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.417884
48 30755 ... 11.351794
49 30756 ... 11.415997
50 30757 ... 10.585990
51 30758 ... 10.834534
52 30759 ... 10.455210
53 30760 ... 10.706393
54 30761 ... 10.487299
55 30762 ... 10.475573
56 30763 ... 10.091512
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xuut9khr wandb: Agent Starting Run: opcbv3h4 with config: batch_size: 2 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: opcbv3h4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
55.38436781615019
The number of items in train is:
18
The loss for epoch 0
3.076909323119455
The running loss is:
20.806777961552143
The number of items in train is:
18
The loss for epoch 1
1.155932108975119
The running loss is:
18.307716690003872
The number of items in train is:
18
The loss for epoch 2
1.0170953716668818
The running loss is:
18.69004149734974
The number of items in train is:
18
The loss for epoch 3
1.0383356387416522
The running loss is:
19.871280409395695
The number of items in train is:
18
The loss for epoch 4
1.1039600227442052
The running loss is:
17.01835998892784
The number of items in train is:
18
The loss for epoch 5
0.9454644438293245
The running loss is:
16.486702501773834
The number of items in train is:
18
The loss for epoch 6
0.915927916765213
The running loss is:
16.326455369591713
The number of items in train is:
18
The loss for epoch 7
0.9070252983106507
The running loss is:
16.18179951608181
The number of items in train is:
18
The loss for epoch 8
0.898988862004545
The running loss is:
15.756254091858864
The number of items in train is:
18
The loss for epoch 9
0.8753474495477147
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.574912
48 30755 ... 11.343673
49 30756 ... 10.713832
50 30757 ... 9.781120
51 30758 ... 9.948353
52 30759 ... 10.150012
53 30760 ... 9.753569
54 30761 ... 9.639825
55 30762 ... 9.856399
56 30763 ... 9.539119
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: opcbv3h4 wandb: Agent Starting Run: payrwmn7 with config: batch_size: 2 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: payrwmn7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.764818392693996
The number of items in train is:
18
The loss for epoch 0
0.7091565773718886
The running loss is:
41.29002905637026
The number of items in train is:
18
The loss for epoch 1
2.293890503131681
The running loss is:
17.83612199127674
The number of items in train is:
18
The loss for epoch 2
0.9908956661820412
The running loss is:
16.420202357694507
The number of items in train is:
18
The loss for epoch 3
0.9122334643163614
The running loss is:
12.88229051977396
The number of items in train is:
18
The loss for epoch 4
0.7156828066541089
The running loss is:
11.19569367915392
The number of items in train is:
18
The loss for epoch 5
0.6219829821752177
The running loss is:
10.120619802735746
The number of items in train is:
18
The loss for epoch 6
0.5622566557075415
The running loss is:
9.58696399955079
The number of items in train is:
18
The loss for epoch 7
0.5326091110861549
The running loss is:
8.832727583125234
The number of items in train is:
18
The loss for epoch 8
0.4907070879514019
The running loss is:
8.69556760089472
The number of items in train is:
18
The loss for epoch 9
0.48308708893859553
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.861172
48 30755 ... 11.517205
49 30756 ... 11.780841
50 30757 ... 11.693560
51 30758 ... 8.127285
52 30759 ... 8.260897
53 30760 ... 8.410134
54 30761 ... 8.223893
55 30762 ... 8.788653
56 30763 ... 8.309381
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: payrwmn7 wandb: Agent Starting Run: yzkklixg with config: batch_size: 2 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: yzkklixg
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.693578988313675
The number of items in train is:
18
The loss for epoch 0
0.8163099437952042
The running loss is:
35.63161541521549
The number of items in train is:
18
The loss for epoch 1
1.979534189734194
The running loss is:
16.785623099654913
The number of items in train is:
18
The loss for epoch 2
0.9325346166474952
The running loss is:
15.402808114886284
The number of items in train is:
18
The loss for epoch 3
0.8557115619381269
The running loss is:
12.666369892656803
The number of items in train is:
18
The loss for epoch 4
0.7036872162587113
The running loss is:
11.15108098834753
The number of items in train is:
18
The loss for epoch 5
0.6195044993526406
The running loss is:
10.014611192047596
The number of items in train is:
18
The loss for epoch 6
0.5563672884470887
The running loss is:
9.563246592879295
The number of items in train is:
18
The loss for epoch 7
0.5312914773821831
The running loss is:
9.08486569300294
The number of items in train is:
18
The loss for epoch 8
0.5047147607223855
The running loss is:
9.686499211937189
The number of items in train is:
18
The loss for epoch 9
0.5381388451076217
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.070226
48 30755 ... 6.394022
49 30756 ... 7.502196
50 30757 ... 8.509747
51 30758 ... 3.066005
52 30759 ... 2.097596
53 30760 ... -1.188965
54 30761 ... -2.204936
55 30762 ... -1.965081
56 30763 ... -2.326006
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yzkklixg wandb: Agent Starting Run: qgblb6h1 with config: batch_size: 2 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qgblb6h1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.94256365299225
The number of items in train is:
17
The loss for epoch 0
0.9966213913524852
The running loss is:
25.57343617081642
The number of items in train is:
17
The loss for epoch 1
1.5043197747539072
The running loss is:
13.54184927791357
The number of items in train is:
17
The loss for epoch 2
0.7965793692890335
The running loss is:
12.523482795804739
The number of items in train is:
17
The loss for epoch 3
0.7366754585767493
The running loss is:
10.940785882994533
The number of items in train is:
17
The loss for epoch 4
0.643575640176149
The running loss is:
10.1965466234833
The number of items in train is:
17
The loss for epoch 5
0.5997968602049
The running loss is:
9.783029923215508
The number of items in train is:
17
The loss for epoch 6
0.5754723484244417
The running loss is:
9.331181142479181
The number of items in train is:
17
The loss for epoch 7
0.5488930083811283
The running loss is:
8.621533285826445
The number of items in train is:
17
The loss for epoch 8
0.5071490168133203
The running loss is:
9.149149924516678
The number of items in train is:
17
The loss for epoch 9
0.5381852896774516
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.083263
48 30755 ... 6.330942
49 30756 ... 6.745354
50 30757 ... 6.260278
51 30758 ... 2.354475
52 30759 ... 1.357481
53 30760 ... -2.238031
54 30761 ... -3.122238
55 30762 ... -3.426826
56 30763 ... -3.572912
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qgblb6h1 wandb: Agent Starting Run: f9x7y7pi with config: batch_size: 2 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: f9x7y7pi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.917671071365476
The number of items in train is:
18
The loss for epoch 0
0.773203948409193
The running loss is:
32.96171744167805
The number of items in train is:
18
The loss for epoch 1
1.8312065245376692
The running loss is:
28.98233161121607
The number of items in train is:
18
The loss for epoch 2
1.6101295339564483
The running loss is:
15.695902362465858
The number of items in train is:
18
The loss for epoch 3
0.8719945756925477
The running loss is:
13.521882995963097
The number of items in train is:
18
The loss for epoch 4
0.7512157219979498
The running loss is:
10.357533072587103
The number of items in train is:
18
The loss for epoch 5
0.5754185040326169
The running loss is:
10.813971852883697
The number of items in train is:
18
The loss for epoch 6
0.6007762140490942
The running loss is:
9.83951736614108
The number of items in train is:
18
The loss for epoch 7
0.5466398536745045
The running loss is:
7.9957271702587605
The number of items in train is:
18
The loss for epoch 8
0.44420706501437557
The running loss is:
9.712909625843167
The number of items in train is:
18
The loss for epoch 9
0.5396060903246204
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.825358
48 30755 ... 8.746976
49 30756 ... 8.922942
50 30757 ... 9.659204
51 30758 ... 3.814860
52 30759 ... 2.959181
53 30760 ... 1.246872
54 30761 ... 2.002126
55 30762 ... 2.633024
56 30763 ... 2.873677
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f9x7y7pi wandb: Agent Starting Run: 582syw3h with config: batch_size: 2 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 582syw3h
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.806585595011711
The number of items in train is:
18
The loss for epoch 0
0.7114769775006506
The running loss is:
30.424656696617603
The number of items in train is:
18
The loss for epoch 1
1.6902587053676446
The running loss is:
26.228094905614853
The number of items in train is:
18
The loss for epoch 2
1.4571163836452696
The running loss is:
15.915115505456924
The number of items in train is:
18
The loss for epoch 3
0.8841730836364958
The running loss is:
13.321218777447939
The number of items in train is:
18
The loss for epoch 4
0.7400677098582188
The running loss is:
12.429280959069729
The number of items in train is:
18
The loss for epoch 5
0.6905156088372072
The running loss is:
10.585802391171455
The number of items in train is:
18
The loss for epoch 6
0.5881001328428587
The running loss is:
10.051417954266071
The number of items in train is:
18
The loss for epoch 7
0.5584121085703373
The running loss is:
10.791548609733582
The number of items in train is:
18
The loss for epoch 8
0.5995304783185323
The running loss is:
10.503232896327972
The number of items in train is:
18
The loss for epoch 9
0.5835129386848874
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.806384
48 30755 ... 9.270082
49 30756 ... 9.476368
50 30757 ... 11.667879
51 30758 ... 7.077388
52 30759 ... 7.040015
53 30760 ... 6.562690
54 30761 ... 6.141752
55 30762 ... 7.215327
56 30763 ... 6.751134
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 582syw3h wandb: Agent Starting Run: rb2iuxuw with config: batch_size: 2 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: rb2iuxuw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.165790781378746
The number of items in train is:
17
The loss for epoch 0
0.7156347518458086
The running loss is:
27.170376665890217
The number of items in train is:
17
The loss for epoch 1
1.5982574509347187
The running loss is:
21.744665786623955
The number of items in train is:
17
The loss for epoch 2
1.279097987448468
The running loss is:
13.72632198035717
The number of items in train is:
17
The loss for epoch 3
0.8074307047268924
The running loss is:
12.807656642049551
The number of items in train is:
17
The loss for epoch 4
0.7533915671793854
The running loss is:
11.399554572999477
The number of items in train is:
17
The loss for epoch 5
0.6705620337058517
The running loss is:
10.820783462375402
The number of items in train is:
17
The loss for epoch 6
0.6365166742573766
The running loss is:
10.212848238646984
The number of items in train is:
17
The loss for epoch 7
0.6007557787439403
The running loss is:
9.258121870458126
The number of items in train is:
17
The loss for epoch 8
0.5445954041445956
The running loss is:
10.42987996339798
The number of items in train is:
17
The loss for epoch 9
0.6135223507881165
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.905188
48 30755 ... 7.925228
49 30756 ... 7.197696
50 30757 ... 6.468437
51 30758 ... 3.872510
52 30759 ... 3.471162
53 30760 ... 2.644137
54 30761 ... 0.842908
55 30762 ... 1.020092
56 30763 ... 0.611532
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rb2iuxuw wandb: Agent Starting Run: q8pk37k7 with config: batch_size: 2 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: q8pk37k7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
25.0777577906847
The number of items in train is:
18
The loss for epoch 0
1.39320876614915
The running loss is:
29.13719865679741
The number of items in train is:
18
The loss for epoch 1
1.618733258710967
The running loss is:
27.344745717942715
The number of items in train is:
18
The loss for epoch 2
1.5191525398857064
The running loss is:
28.274847473949194
The number of items in train is:
18
The loss for epoch 3
1.570824859663844
The running loss is:
13.97701994329691
The number of items in train is:
18
The loss for epoch 4
0.7765011079609394
The running loss is:
12.554442692548037
The number of items in train is:
18
The loss for epoch 5
0.697469038474891
The running loss is:
13.142991535365582
The number of items in train is:
18
The loss for epoch 6
0.730166196409199
The running loss is:
14.788394697010517
The number of items in train is:
18
The loss for epoch 7
0.821577483167251
The running loss is:
14.111675955122337
The number of items in train is:
18
The loss for epoch 8
0.7839819975067965
The running loss is:
12.757243922678754
The number of items in train is:
18
The loss for epoch 9
0.708735773482153
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.673750
48 30755 ... 8.759176
49 30756 ... 11.605460
50 30757 ... 12.306805
51 30758 ... 9.116247
52 30759 ... 8.930177
53 30760 ... 8.762095
54 30761 ... 8.338878
55 30762 ... 8.324352
56 30763 ... 8.409344
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: q8pk37k7 wandb: Agent Starting Run: yuaoe3t1 with config: batch_size: 2 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: yuaoe3t1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.664488945156336
The number of items in train is:
18
The loss for epoch 0
1.092471608064241
The running loss is:
24.840459644794464
The number of items in train is:
18
The loss for epoch 1
1.3800255358219147
The running loss is:
24.18926414847374
The number of items in train is:
18
The loss for epoch 2
1.3438480082485411
The running loss is:
22.759043589234352
The number of items in train is:
18
The loss for epoch 3
1.2643913105130196
The running loss is:
18.388007149100304
The number of items in train is:
18
The loss for epoch 4
1.0215559527277946
The running loss is:
17.054414674639702
The number of items in train is:
18
The loss for epoch 5
0.9474674819244279
The running loss is:
16.19636530429125
The number of items in train is:
18
The loss for epoch 6
0.8997980724606249
The running loss is:
16.092383541166782
The number of items in train is:
18
The loss for epoch 7
0.894021307842599
The running loss is:
16.495493300259113
The number of items in train is:
18
The loss for epoch 8
0.9164162944588397
The running loss is:
14.59353306889534
The number of items in train is:
18
The loss for epoch 9
0.8107518371608522
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.460387
48 30755 ... 11.318052
49 30756 ... 11.491536
50 30757 ... 11.200739
51 30758 ... 7.772702
52 30759 ... 7.833028
53 30760 ... 8.080965
54 30761 ... 7.146588
55 30762 ... 7.603038
56 30763 ... 7.158749
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yuaoe3t1 wandb: Agent Starting Run: msnqy4jq with config: batch_size: 2 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: msnqy4jq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.602887228131294
The number of items in train is:
17
The loss for epoch 0
0.9178168957724291
The running loss is:
20.492954045534134
The number of items in train is:
17
The loss for epoch 1
1.2054678850314196
The running loss is:
18.17607271671295
The number of items in train is:
17
The loss for epoch 2
1.0691807480419384
The running loss is:
17.942578546702862
The number of items in train is:
17
The loss for epoch 3
1.0554457968648743
The running loss is:
15.375115282833576
The number of items in train is:
17
The loss for epoch 4
0.9044185460490339
The running loss is:
14.95146494358778
The number of items in train is:
17
The loss for epoch 5
0.8794979378581047
The running loss is:
14.935466520488262
The number of items in train is:
17
The loss for epoch 6
0.8785568541463684
The running loss is:
13.655654460191727
The number of items in train is:
17
The loss for epoch 7
0.8032737917759839
The running loss is:
13.988929450511932
The number of items in train is:
17
The loss for epoch 8
0.8228782029712901
The running loss is:
12.398067966103554
The number of items in train is:
17
The loss for epoch 9
0.7292981156531502
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.182483
48 30755 ... 11.828949
49 30756 ... 9.899583
50 30757 ... 5.444458
51 30758 ... 6.187648
52 30759 ... 5.976255
53 30760 ... 5.439822
54 30761 ... 4.073036
55 30762 ... 4.531176
56 30763 ... 2.037996
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: msnqy4jq wandb: Agent Starting Run: 28zecqnv with config: batch_size: 2 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 28zecqnv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
132.11954160500318
The number of items in train is:
18
The loss for epoch 0
7.339974533611287
The running loss is:
33.18467270210385
The number of items in train is:
18
The loss for epoch 1
1.8435929278946586
The running loss is:
15.044109242036939
The number of items in train is:
18
The loss for epoch 2
0.83578384677983
The running loss is:
32.12868493422866
The number of items in train is:
18
The loss for epoch 3
1.784926940790481
The running loss is:
16.458579962607473
The number of items in train is:
18
The loss for epoch 4
0.9143655534781929
The running loss is:
16.18535217642784
The number of items in train is:
18
The loss for epoch 5
0.8991862320237689
The running loss is:
13.845332082360983
The number of items in train is:
18
The loss for epoch 6
0.7691851156867213
The running loss is:
18.111790597438812
The number of items in train is:
18
The loss for epoch 7
1.0062105887466006
The running loss is:
15.37386241927743
The number of items in train is:
18
The loss for epoch 8
0.854103467737635
The running loss is:
14.108973555266857
The number of items in train is:
18
The loss for epoch 9
0.7838318641814921
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.096198
48 30755 ... 6.123454
49 30756 ... 17.012180
50 30757 ... 18.440594
51 30758 ... 15.032338
52 30759 ... 14.862954
53 30760 ... 14.920713
54 30761 ... 14.467838
55 30762 ... 14.409379
56 30763 ... 17.330112
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 28zecqnv wandb: Agent Starting Run: wyy0ykxe with config: batch_size: 2 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: wyy0ykxe
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
92.95915368199348
The number of items in train is:
18
The loss for epoch 0
5.164397426777416
The running loss is:
22.1982841193676
The number of items in train is:
18
The loss for epoch 1
1.2332380066315334
The running loss is:
14.565131276845932
The number of items in train is:
18
The loss for epoch 2
0.809173959824774
The running loss is:
27.13835011422634
The number of items in train is:
18
The loss for epoch 3
1.5076861174570189
The running loss is:
19.970424134284258
The number of items in train is:
18
The loss for epoch 4
1.1094680074602365
The running loss is:
16.359486132860184
The number of items in train is:
18
The loss for epoch 5
0.9088603407144547
The running loss is:
15.630101136863232
The number of items in train is:
18
The loss for epoch 6
0.8683389520479573
The running loss is:
14.64559318125248
The number of items in train is:
18
The loss for epoch 7
0.8136440656251378
The running loss is:
16.040196174755692
The number of items in train is:
18
The loss for epoch 8
0.8911220097086496
The running loss is:
15.461667504161596
The number of items in train is:
18
The loss for epoch 9
0.8589815280089775
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.144684
48 30755 ... 8.574534
49 30756 ... 11.426785
50 30757 ... 10.841069
51 30758 ... 10.581007
52 30759 ... 10.608530
53 30760 ... 11.141614
54 30761 ... 10.802588
55 30762 ... 10.750504
56 30763 ... 10.328904
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wyy0ykxe wandb: Agent Starting Run: 00dey2s4 with config: batch_size: 2 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 00dey2s4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
61.90179131925106
The number of items in train is:
17
The loss for epoch 0
3.641281842308886
The running loss is:
19.271656930446625
The number of items in train is:
17
The loss for epoch 1
1.1336268782615662
The running loss is:
19.321099177002907
The number of items in train is:
17
The loss for epoch 2
1.1365352457060534
The running loss is:
15.400234825909138
The number of items in train is:
17
The loss for epoch 3
0.9058961662299493
The running loss is:
14.907342068850994
The number of items in train is:
17
The loss for epoch 4
0.8769024746382937
The running loss is:
14.489337973296642
The number of items in train is:
17
The loss for epoch 5
0.8523139984292143
The running loss is:
14.622908413410187
The number of items in train is:
17
The loss for epoch 6
0.8601710831417757
The running loss is:
13.41513104736805
The number of items in train is:
17
The loss for epoch 7
0.7891253557275323
The running loss is:
13.095239669084549
The number of items in train is:
17
The loss for epoch 8
0.7703082158285028
The running loss is:
12.160573348402977
The number of items in train is:
17
The loss for epoch 9
0.7153278440237045
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.955428
48 30755 ... 10.954730
49 30756 ... 11.092212
50 30757 ... 11.093774
51 30758 ... 8.547292
52 30759 ... 8.556589
53 30760 ... 8.530978
54 30761 ... 6.731397
55 30762 ... 6.504598
56 30763 ... 6.419131
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 00dey2s4 wandb: Agent Starting Run: l00hyprr with config: batch_size: 2 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: l00hyprr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.450659646186978
The number of items in train is:
18
The loss for epoch 0
1.1361477581214987
The running loss is:
25.368839150760323
The number of items in train is:
18
The loss for epoch 1
1.409379952820018
The running loss is:
13.926943810191005
The number of items in train is:
18
The loss for epoch 2
0.773719100566167
The running loss is:
12.035636499524117
The number of items in train is:
18
The loss for epoch 3
0.6686464721957842
The running loss is:
9.788120612502098
The number of items in train is:
18
The loss for epoch 4
0.5437844784723388
The running loss is:
10.819668479263783
The number of items in train is:
18
The loss for epoch 5
0.6010926932924323
The running loss is:
9.73928571306169
The number of items in train is:
18
The loss for epoch 6
0.5410714285034273
The running loss is:
9.011047106876504
The number of items in train is:
18
The loss for epoch 7
0.5006137281598058
The running loss is:
8.731201235204935
The number of items in train is:
18
The loss for epoch 8
0.48506673528916305
The running loss is:
7.952998843044043
The number of items in train is:
18
The loss for epoch 9
0.44183326905800235
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.977856
48 30755 ... 11.868648
49 30756 ... 17.565083
50 30757 ... 15.627804
51 30758 ... 9.883644
52 30759 ... 10.390420
53 30760 ... 11.200606
54 30761 ... 10.064157
55 30762 ... 11.100951
56 30763 ... 13.825031
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l00hyprr wandb: Agent Starting Run: 40olhm4s with config: batch_size: 2 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 40olhm4s
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.027740366756916
The number of items in train is:
17
The loss for epoch 0
1.119278845103348
The running loss is:
26.84563284367323
The number of items in train is:
17
The loss for epoch 1
1.5791548731572487
The running loss is:
14.248602889478207
The number of items in train is:
17
The loss for epoch 2
0.8381531111457768
The running loss is:
12.727784872055054
The number of items in train is:
17
The loss for epoch 3
0.7486932277679443
The running loss is:
12.753539435565472
The number of items in train is:
17
The loss for epoch 4
0.7502082020920866
The running loss is:
11.517959401011467
The number of items in train is:
17
The loss for epoch 5
0.6775270235889098
The running loss is:
11.238709852099419
The number of items in train is:
17
The loss for epoch 6
0.6611005795352599
The running loss is:
10.820317476987839
The number of items in train is:
17
The loss for epoch 7
0.6364892633522258
The running loss is:
10.896733909845352
The number of items in train is:
17
The loss for epoch 8
0.6409843476379619
The running loss is:
9.990343987941742
The number of items in train is:
17
The loss for epoch 9
0.5876672934083378
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.421764
48 30755 ... 11.356266
49 30756 ... 12.500781
50 30757 ... 12.673218
51 30758 ... 11.942869
52 30759 ... 10.421821
53 30760 ... 11.093673
54 30761 ... 11.154191
55 30762 ... 11.348830
56 30763 ... 11.964188
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 40olhm4s wandb: Agent Starting Run: qa1p7boy with config: batch_size: 2 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qa1p7boy
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.990485712885857
The number of items in train is:
17
The loss for epoch 0
1.0582638654638739
The running loss is:
27.865905489772558
The number of items in train is:
17
The loss for epoch 1
1.6391709111630917
The running loss is:
13.985774576663971
The number of items in train is:
17
The loss for epoch 2
0.8226926221567041
The running loss is:
12.147280521690845
The number of items in train is:
17
The loss for epoch 3
0.714545913040638
The running loss is:
10.898061953485012
The number of items in train is:
17
The loss for epoch 4
0.6410624678520596
The running loss is:
10.279500223696232
The number of items in train is:
17
The loss for epoch 5
0.6046764837468371
The running loss is:
10.136913530528545
The number of items in train is:
17
The loss for epoch 6
0.5962890312075615
The running loss is:
9.784845240414143
The number of items in train is:
17
The loss for epoch 7
0.5755791317890672
The running loss is:
9.845538966357708
The number of items in train is:
17
The loss for epoch 8
0.5791493509622181
The running loss is:
9.486583903431892
The number of items in train is:
17
The loss for epoch 9
0.5580343472606996
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.509616
48 30755 ... 9.559368
49 30756 ... 11.189049
50 30757 ... 10.662446
51 30758 ... 9.135548
52 30759 ... 6.710083
53 30760 ... 6.572598
54 30761 ... 6.372887
55 30762 ... 5.868860
56 30763 ... 6.114229
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qa1p7boy wandb: Agent Starting Run: z60hhdo0 with config: batch_size: 2 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: z60hhdo0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.5401990711689
The number of items in train is:
18
The loss for epoch 0
0.8077888372871611
The running loss is:
27.375006180256605
The number of items in train is:
18
The loss for epoch 1
1.5208336766809225
The running loss is:
19.92556830495596
The number of items in train is:
18
The loss for epoch 2
1.1069760169419978
The running loss is:
12.793712127953768
The number of items in train is:
18
The loss for epoch 3
0.7107617848863205
The running loss is:
10.154001401970163
The number of items in train is:
18
The loss for epoch 4
0.5641111889983423
The running loss is:
11.277737976284698
The number of items in train is:
18
The loss for epoch 5
0.6265409986824833
The running loss is:
10.516089941374958
The number of items in train is:
18
The loss for epoch 6
0.5842272189652754
The running loss is:
10.196689029689878
The number of items in train is:
18
The loss for epoch 7
0.5664827238716599
The running loss is:
9.814422994852066
The number of items in train is:
18
The loss for epoch 8
0.5452457219362259
The running loss is:
9.361941157840192
The number of items in train is:
18
The loss for epoch 9
0.5201078421022329
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.364668
48 30755 ... 11.533773
49 30756 ... 18.344410
50 30757 ... 16.221804
51 30758 ... 10.735049
52 30759 ... 11.302640
53 30760 ... 11.773656
54 30761 ... 9.497039
55 30762 ... 11.057786
56 30763 ... 15.525364
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z60hhdo0 wandb: Agent Starting Run: r13hrd64 with config: batch_size: 2 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: r13hrd64
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.9246169552207
The number of items in train is:
17
The loss for epoch 0
0.8190951150129823
The running loss is:
27.833781890571117
The number of items in train is:
17
The loss for epoch 1
1.637281287680654
The running loss is:
20.855405513197184
The number of items in train is:
17
The loss for epoch 2
1.2267885595998342
The running loss is:
13.618450827896595
The number of items in train is:
17
The loss for epoch 3
0.8010853428174468
The running loss is:
13.988207560032606
The number of items in train is:
17
The loss for epoch 4
0.8228357388254475
The running loss is:
12.185236137360334
The number of items in train is:
17
The loss for epoch 5
0.7167785963153138
The running loss is:
12.937843896448612
The number of items in train is:
17
The loss for epoch 6
0.7610496409675654
The running loss is:
12.002348616719246
The number of items in train is:
17
The loss for epoch 7
0.706020506865838
The running loss is:
11.300229970365763
The number of items in train is:
17
The loss for epoch 8
0.6647194100215155
The running loss is:
10.760703813284636
The number of items in train is:
17
The loss for epoch 9
0.6329825772520374
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.507266
48 30755 ... 11.811560
49 30756 ... 13.621972
50 30757 ... 13.042014
51 30758 ... 11.766799
52 30759 ... 9.670241
53 30760 ... 10.042046
54 30761 ... 9.816596
55 30762 ... 9.815838
56 30763 ... 10.284580
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r13hrd64 wandb: Agent Starting Run: ylv24ywo with config: batch_size: 2 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ylv24ywo
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.265747778117657
The number of items in train is:
17
The loss for epoch 0
0.7215145751833916
The running loss is:
25.639500468969345
The number of items in train is:
17
The loss for epoch 1
1.5082059099393732
The running loss is:
21.685997530817986
The number of items in train is:
17
The loss for epoch 2
1.2756469135775286
The running loss is:
13.566235706210136
The number of items in train is:
17
The loss for epoch 3
0.7980138650711845
The running loss is:
12.054102204740047
The number of items in train is:
17
The loss for epoch 4
0.709064835572944
The running loss is:
11.060121264308691
The number of items in train is:
17
The loss for epoch 5
0.6505953684887466
The running loss is:
11.129384398460388
The number of items in train is:
17
The loss for epoch 6
0.6546696704976699
The running loss is:
10.726066958159208
The number of items in train is:
17
The loss for epoch 7
0.6309451151858357
The running loss is:
10.483027771115303
The number of items in train is:
17
The loss for epoch 8
0.6166486924185473
The running loss is:
9.922650948166847
The number of items in train is:
17
The loss for epoch 9
0.5836853498921675
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.026129
48 30755 ... 10.119618
49 30756 ... 13.747051
50 30757 ... 12.436648
51 30758 ... 9.467723
52 30759 ... 8.617616
53 30760 ... 8.754156
54 30761 ... 8.447451
55 30762 ... 8.298104
56 30763 ... 9.212432
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ylv24ywo wandb: Agent Starting Run: 202c29sd with config: batch_size: 2 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 202c29sd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.38165923114866
The number of items in train is:
18
The loss for epoch 0
0.9656477350638144
The running loss is:
22.52288119122386
The number of items in train is:
18
The loss for epoch 1
1.2512711772902145
The running loss is:
20.58570908382535
The number of items in train is:
18
The loss for epoch 2
1.1436505046569638
The running loss is:
17.03510294482112
The number of items in train is:
18
The loss for epoch 3
0.9463946080456177
The running loss is:
16.227192664518952
The number of items in train is:
18
The loss for epoch 4
0.9015107035843862
The running loss is:
15.710538178682327
The number of items in train is:
18
The loss for epoch 5
0.8728076765934626
The running loss is:
16.636069810017943
The number of items in train is:
18
The loss for epoch 6
0.9242261005565524
The running loss is:
16.63070970028639
The number of items in train is:
18
The loss for epoch 7
0.9239283166825771
The running loss is:
14.5533220928628
The number of items in train is:
18
The loss for epoch 8
0.8085178940479333
The running loss is:
12.518009976483881
The number of items in train is:
18
The loss for epoch 9
0.6954449986935489
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.864379
48 30755 ... 13.484338
49 30756 ... 13.468613
50 30757 ... 13.644678
51 30758 ... 13.640962
52 30759 ... 12.436494
53 30760 ... 12.610359
54 30761 ... 12.908359
55 30762 ... 12.950767
56 30763 ... 13.025203
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 202c29sd wandb: Agent Starting Run: u9eo4dfi with config: batch_size: 2 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: u9eo4dfi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.665514931082726
The number of items in train is:
17
The loss for epoch 0
0.9803244077107486
The running loss is:
21.98633325099945
The number of items in train is:
17
The loss for epoch 1
1.2933137206470264
The running loss is:
20.401913326233625
The number of items in train is:
17
The loss for epoch 2
1.200112548601978
The running loss is:
17.110268775373697
The number of items in train is:
17
The loss for epoch 3
1.0064863985513939
The running loss is:
15.317520216107368
The number of items in train is:
17
The loss for epoch 4
0.9010306009474922
The running loss is:
14.436367448419333
The number of items in train is:
17
The loss for epoch 5
0.8491980852011372
The running loss is:
11.61998137831688
The number of items in train is:
17
The loss for epoch 6
0.6835283163715812
The running loss is:
14.995876673609018
The number of items in train is:
17
The loss for epoch 7
0.8821103925652364
The running loss is:
12.463443532586098
The number of items in train is:
17
The loss for epoch 8
0.7331437372109469
The running loss is:
12.348684921860695
The number of items in train is:
17
The loss for epoch 9
0.7263932306976879
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.883090
48 30755 ... 11.924982
49 30756 ... 11.952619
50 30757 ... 11.935939
51 30758 ... 11.950844
52 30759 ... 7.756837
53 30760 ... 7.546932
54 30761 ... 7.714972
55 30762 ... 7.608711
56 30763 ... 7.573092
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u9eo4dfi wandb: Agent Starting Run: gfy2ld4o with config: batch_size: 2 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: gfy2ld4o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.57657253742218
The number of items in train is:
17
The loss for epoch 0
1.0339160316130693
The running loss is:
21.085083961486816
The number of items in train is:
17
The loss for epoch 1
1.240299056558048
The running loss is:
20.510505497455597
The number of items in train is:
17
The loss for epoch 2
1.206500323379741
The running loss is:
18.18516470491886
The number of items in train is:
17
The loss for epoch 3
1.06971557087758
The running loss is:
15.011801198124886
The number of items in train is:
17
The loss for epoch 4
0.8830471293014639
The running loss is:
15.11803139001131
The number of items in train is:
17
The loss for epoch 5
0.8892959641183124
The running loss is:
14.489876501262188
The number of items in train is:
17
The loss for epoch 6
0.8523456765448346
The running loss is:
14.646412342786789
The number of items in train is:
17
The loss for epoch 7
0.8615536672227523
The running loss is:
14.810041315853596
The number of items in train is:
17
The loss for epoch 8
0.8711789009325644
The running loss is:
13.977952808141708
The number of items in train is:
17
The loss for epoch 9
0.8222325181259829
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.258494
48 30755 ... 11.628599
49 30756 ... 12.363077
50 30757 ... 12.457399
51 30758 ... 11.434335
52 30759 ... 11.597588
53 30760 ... 11.598228
54 30761 ... 11.475595
55 30762 ... 11.413112
56 30763 ... 11.466397
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gfy2ld4o wandb: Agent Starting Run: 6b6shvso with config: batch_size: 2 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 6b6shvso
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
78.06080336868763
The number of items in train is:
18
The loss for epoch 0
4.336711298260424
The running loss is:
23.151071030646563
The number of items in train is:
18
The loss for epoch 1
1.2861706128136978
The running loss is:
18.575490936636925
The number of items in train is:
18
The loss for epoch 2
1.0319717187020514
The running loss is:
23.149101957678795
The number of items in train is:
18
The loss for epoch 3
1.2860612198710442
The running loss is:
17.067200284451246
The number of items in train is:
18
The loss for epoch 4
0.9481777935806248
The running loss is:
17.59191408008337
The number of items in train is:
18
The loss for epoch 5
0.9773285600046316
The running loss is:
14.751718316227198
The number of items in train is:
18
The loss for epoch 6
0.8195399064570665
The running loss is:
17.836396224796772
The number of items in train is:
18
The loss for epoch 7
0.9909109013775984
The running loss is:
12.664922920055687
The number of items in train is:
18
The loss for epoch 8
0.7036068288919827
The running loss is:
19.829482200788334
The number of items in train is:
18
The loss for epoch 9
1.1016379000437964
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.880940
48 30755 ... 10.986598
49 30756 ... 10.924918
50 30757 ... 12.085524
51 30758 ... 11.770830
52 30759 ... 11.676743
53 30760 ... 11.817716
54 30761 ... 11.519333
55 30762 ... 11.551911
56 30763 ... 11.689872
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6b6shvso wandb: Agent Starting Run: v0ak9wcn with config: batch_size: 2 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: v0ak9wcn
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
61.02029025554657
The number of items in train is:
17
The loss for epoch 0
3.589428838561563
The running loss is:
19.11992210894823
The number of items in train is:
17
The loss for epoch 1
1.1247013005263664
The running loss is:
20.35962064191699
The number of items in train is:
17
The loss for epoch 2
1.1976247436421759
The running loss is:
17.901119500398636
The number of items in train is:
17
The loss for epoch 3
1.0530070294352138
The running loss is:
19.68121352046728
The number of items in train is:
17
The loss for epoch 4
1.1577184423804283
The running loss is:
15.582372598350048
The number of items in train is:
17
The loss for epoch 5
0.9166101528441205
The running loss is:
15.728278800845146
The number of items in train is:
17
The loss for epoch 6
0.9251928706379497
The running loss is:
15.83667142689228
The number of items in train is:
17
The loss for epoch 7
0.9315689074642518
The running loss is:
15.11179693043232
The number of items in train is:
17
The loss for epoch 8
0.8889292312019011
The running loss is:
14.601482972502708
The number of items in train is:
17
The loss for epoch 9
0.8589107630883946
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.328428
48 30755 ... 12.166418
49 30756 ... 10.337872
50 30757 ... 11.427995
51 30758 ... 12.571464
52 30759 ... 10.586956
53 30760 ... 10.826715
54 30761 ... 11.615481
55 30762 ... 10.511208
56 30763 ... 10.188934
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v0ak9wcn wandb: Agent Starting Run: v0kjygd2 with config: batch_size: 2 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: v0kjygd2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
89.38227146863937
The number of items in train is:
17
The loss for epoch 0
5.257780674625845
The running loss is:
24.08541053533554
The number of items in train is:
17
The loss for epoch 1
1.4167888550197376
The running loss is:
14.835047475993633
The number of items in train is:
17
The loss for epoch 2
0.8726498515290373
The running loss is:
17.46521347016096
The number of items in train is:
17
The loss for epoch 3
1.0273654982447624
The running loss is:
14.109677575528622
The number of items in train is:
17
The loss for epoch 4
0.8299810338546249
The running loss is:
14.43064521253109
The number of items in train is:
17
The loss for epoch 5
0.8488614830900642
The running loss is:
13.140712775290012
The number of items in train is:
17
The loss for epoch 6
0.7729831044288242
The running loss is:
12.153762593865395
The number of items in train is:
17
The loss for epoch 7
0.7149272114038467
The running loss is:
12.104884780943394
The number of items in train is:
17
The loss for epoch 8
0.7120520459378467
The running loss is:
11.55245054513216
The number of items in train is:
17
The loss for epoch 9
0.6795559144195389
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.822438
48 30755 ... 11.070477
49 30756 ... 13.553607
50 30757 ... 11.531958
51 30758 ... 12.513781
52 30759 ... 10.915012
53 30760 ... 11.354100
54 30761 ... 10.394032
55 30762 ... 10.346492
56 30763 ... 10.777813
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v0kjygd2 wandb: Agent Starting Run: 47x2i8jx with config: batch_size: 2 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 47x2i8jx
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.129226248711348
The number of items in train is:
17
The loss for epoch 0
0.9487780146300793
The running loss is:
33.76753030810505
The number of items in train is:
17
The loss for epoch 1
1.9863253122414737
The running loss is:
14.467158187180758
The number of items in train is:
17
The loss for epoch 2
0.8510093051282799
The running loss is:
12.87113780900836
The number of items in train is:
17
The loss for epoch 3
0.75712575347108
The running loss is:
9.909067310392857
The number of items in train is:
17
The loss for epoch 4
0.5828863123760504
The running loss is:
9.568089163396508
The number of items in train is:
17
The loss for epoch 5
0.5628287743174416
The running loss is:
9.66799031291157
The number of items in train is:
17
The loss for epoch 6
0.56870531252421
The running loss is:
9.636533673852682
The number of items in train is:
17
The loss for epoch 7
0.5668549219913342
The running loss is:
8.8233229694888
The number of items in train is:
17
The loss for epoch 8
0.5190189982052235
The running loss is:
7.847568524535745
The number of items in train is:
17
The loss for epoch 9
0.4616216779138674
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.663638
48 30755 ... 9.835592
49 30756 ... 11.178393
50 30757 ... 13.019385
51 30758 ... 12.181848
52 30759 ... 9.387854
53 30760 ... 8.466204
54 30761 ... 8.803273
55 30762 ... 8.617043
56 30763 ... 8.495243
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 47x2i8jx wandb: Agent Starting Run: k64zd0i7 with config: batch_size: 2 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: k64zd0i7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.11563566327095
The number of items in train is:
17
The loss for epoch 0
1.0656256272512323
The running loss is:
24.05933529138565
The number of items in train is:
17
The loss for epoch 1
1.4152550171403324
The running loss is:
12.897609576582909
The number of items in train is:
17
The loss for epoch 2
0.7586829162695828
The running loss is:
11.346729777753353
The number of items in train is:
17
The loss for epoch 3
0.6674546928090208
The running loss is:
10.032144397497177
The number of items in train is:
17
The loss for epoch 4
0.5901261410292458
The running loss is:
9.255228951573372
The number of items in train is:
17
The loss for epoch 5
0.5444252324454925
The running loss is:
8.855674020946026
The number of items in train is:
17
The loss for epoch 6
0.5209220012321192
The running loss is:
8.337467238307
The number of items in train is:
17
The loss for epoch 7
0.4904392493121764
The running loss is:
7.936403177678585
The number of items in train is:
17
The loss for epoch 8
0.4668472457457991
The running loss is:
7.299756273627281
The number of items in train is:
17
The loss for epoch 9
0.4293974278604283
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.314528
48 30755 ... 4.023320
49 30756 ... 7.303198
50 30757 ... 10.772114
51 30758 ... 8.226935
52 30759 ... 2.058505
53 30760 ... -0.580315
54 30761 ... -1.148522
55 30762 ... -3.539087
56 30763 ... -3.183217
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: k64zd0i7 wandb: Agent Starting Run: 90hzhwlz with config: batch_size: 2 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 90hzhwlz
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.229821100831032
The number of items in train is:
16
The loss for epoch 0
0.7643638188019395
The running loss is:
31.796365045011044
The number of items in train is:
16
The loss for epoch 1
1.9872728153131902
The running loss is:
15.763759694993496
The number of items in train is:
16
The loss for epoch 2
0.9852349809370935
The running loss is:
13.028775602579117
The number of items in train is:
16
The loss for epoch 3
0.8142984751611948
The running loss is:
13.04194351285696
The number of items in train is:
16
The loss for epoch 4
0.81512146955356
The running loss is:
10.17906753718853
The number of items in train is:
16
The loss for epoch 5
0.6361917210742831
The running loss is:
9.676793612539768
The number of items in train is:
16
The loss for epoch 6
0.6047996007837355
The running loss is:
9.569400377571583
The number of items in train is:
16
The loss for epoch 7
0.5980875235982239
The running loss is:
9.05061225220561
The number of items in train is:
16
The loss for epoch 8
0.5656632657628506
The running loss is:
8.944659441709518
The number of items in train is:
16
The loss for epoch 9
0.5590412151068449
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.322592
48 30755 ... 8.571899
49 30756 ... 8.965311
50 30757 ... 9.146642
51 30758 ... 9.041492
52 30759 ... 7.654950
53 30760 ... 5.084298
54 30761 ... 4.954723
55 30762 ... 4.857830
56 30763 ... 3.960097
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 90hzhwlz wandb: Agent Starting Run: v8g59dsp with config: batch_size: 2 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: v8g59dsp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.235776502639055
The number of items in train is:
17
The loss for epoch 0
0.7785750883905327
The running loss is:
26.4114770591259
The number of items in train is:
17
The loss for epoch 1
1.5536162975956411
The running loss is:
19.23542471975088
The number of items in train is:
17
The loss for epoch 2
1.1314955717500519
The running loss is:
13.774107448756695
The number of items in train is:
17
The loss for epoch 3
0.8102416146327468
The running loss is:
10.821895120665431
The number of items in train is:
17
The loss for epoch 4
0.6365820659214959
The running loss is:
10.974949937546626
The number of items in train is:
17
The loss for epoch 5
0.6455852904439192
The running loss is:
10.996416509151459
The number of items in train is:
17
The loss for epoch 6
0.6468480299500858
The running loss is:
10.585891755763441
The number of items in train is:
17
The loss for epoch 7
0.6226995150449083
The running loss is:
10.654300592839718
The number of items in train is:
17
The loss for epoch 8
0.6267235642846893
The running loss is:
9.282092098146677
The number of items in train is:
17
The loss for epoch 9
0.5460054175380398
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.044758
48 30755 ... 11.963025
49 30756 ... 12.449036
50 30757 ... 13.799903
51 30758 ... 14.154404
52 30759 ... 11.899445
53 30760 ... 11.876869
54 30761 ... 11.815728
55 30762 ... 12.099028
56 30763 ... 12.176918
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v8g59dsp wandb: Agent Starting Run: mkxr9eu3 with config: batch_size: 2 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: mkxr9eu3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.2156822681427
The number of items in train is:
17
The loss for epoch 0
0.7773930745966294
The running loss is:
24.976793557405472
The number of items in train is:
17
The loss for epoch 1
1.469223150435616
The running loss is:
19.48406381905079
The number of items in train is:
17
The loss for epoch 2
1.1461214011206347
The running loss is:
12.607521995902061
The number of items in train is:
17
The loss for epoch 3
0.7416189409354154
The running loss is:
10.452070504426956
The number of items in train is:
17
The loss for epoch 4
0.6148276767309975
The running loss is:
10.917114395648241
The number of items in train is:
17
The loss for epoch 5
0.6421831997440142
The running loss is:
8.793405067175627
The number of items in train is:
17
The loss for epoch 6
0.5172591215985662
The running loss is:
8.538302391767502
The number of items in train is:
17
The loss for epoch 7
0.5022530818686766
The running loss is:
8.421132470248267
The number of items in train is:
17
The loss for epoch 8
0.4953607335440157
The running loss is:
9.026005014777184
The number of items in train is:
17
The loss for epoch 9
0.5309414714574814
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.012664
48 30755 ... 9.073854
49 30756 ... 9.042130
50 30757 ... 8.332397
51 30758 ... 9.797338
52 30759 ... 8.877247
53 30760 ... 4.768612
54 30761 ... 4.516591
55 30762 ... 4.144512
56 30763 ... 2.947486
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mkxr9eu3 wandb: Agent Starting Run: 1dip79bl with config: batch_size: 2 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1dip79bl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.258202567696571
The number of items in train is:
16
The loss for epoch 0
0.8911376604810357
The running loss is:
24.629937380552292
The number of items in train is:
16
The loss for epoch 1
1.5393710862845182
The running loss is:
21.176617115736008
The number of items in train is:
16
The loss for epoch 2
1.3235385697335005
The running loss is:
15.326480709016323
The number of items in train is:
16
The loss for epoch 3
0.9579050443135202
The running loss is:
12.801851324737072
The number of items in train is:
16
The loss for epoch 4
0.800115707796067
The running loss is:
10.181393705308437
The number of items in train is:
16
The loss for epoch 5
0.6363371065817773
The running loss is:
9.973678585141897
The number of items in train is:
16
The loss for epoch 6
0.6233549115713686
The running loss is:
9.959196142852306
The number of items in train is:
16
The loss for epoch 7
0.6224497589282691
The running loss is:
9.231910694390535
The number of items in train is:
16
The loss for epoch 8
0.5769944183994085
The running loss is:
9.512702483683825
The number of items in train is:
16
The loss for epoch 9
0.594543905230239
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.897227
48 30755 ... 7.666417
49 30756 ... 7.981510
50 30757 ... 7.585426
51 30758 ... 7.403520
52 30759 ... 6.230840
53 30760 ... 2.108467
54 30761 ... 2.234306
55 30762 ... 1.988864
56 30763 ... 0.100393
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1dip79bl wandb: Agent Starting Run: frrjdi26 with config: batch_size: 2 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: frrjdi26
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.684900924563408
The number of items in train is:
17
The loss for epoch 0
1.2755824073272592
The running loss is:
21.957859233021736
The number of items in train is:
17
The loss for epoch 1
1.2916387784130432
The running loss is:
18.442369546741247
The number of items in train is:
17
The loss for epoch 2
1.0848452674553675
The running loss is:
18.312154326587915
The number of items in train is:
17
The loss for epoch 3
1.0771855486228186
The running loss is:
12.220995549112558
The number of items in train is:
17
The loss for epoch 4
0.7188820911242682
The running loss is:
12.270410992205143
The number of items in train is:
17
The loss for epoch 5
0.7217888818944201
The running loss is:
13.395324366167188
The number of items in train is:
17
The loss for epoch 6
0.787960256833364
The running loss is:
12.515632160007954
The number of items in train is:
17
The loss for epoch 7
0.7362136564710561
The running loss is:
13.149393206462264
The number of items in train is:
17
The loss for epoch 8
0.773493718027192
The running loss is:
10.945322513580322
The number of items in train is:
17
The loss for epoch 9
0.6438425007988425
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.736698
48 30755 ... 8.398017
49 30756 ... 9.863556
50 30757 ... 12.266246
51 30758 ... 11.361032
52 30759 ... 9.679527
53 30760 ... 7.219286
54 30761 ... 7.760244
55 30762 ... 7.901274
56 30763 ... 6.949949
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: frrjdi26 wandb: Agent Starting Run: 5e6yghhl with config: batch_size: 2 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 5e6yghhl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.075793281197548
The number of items in train is:
17
The loss for epoch 0
0.9456348988939735
The running loss is:
21.148211747407913
The number of items in train is:
17
The loss for epoch 1
1.2440124557298773
The running loss is:
18.14787855744362
The number of items in train is:
17
The loss for epoch 2
1.0675222680849188
The running loss is:
17.102335512638092
The number of items in train is:
17
The loss for epoch 3
1.006019736037535
The running loss is:
16.263279542326927
The number of items in train is:
17
The loss for epoch 4
0.9566635024898192
The running loss is:
14.015104442834854
The number of items in train is:
17
The loss for epoch 5
0.8244179084020502
The running loss is:
14.513734132051468
The number of items in train is:
17
The loss for epoch 6
0.8537490665912628
The running loss is:
14.677594423294067
The number of items in train is:
17
The loss for epoch 7
0.8633879072525922
The running loss is:
13.664641842246056
The number of items in train is:
17
The loss for epoch 8
0.8038024613085915
The running loss is:
12.593484312295914
The number of items in train is:
17
The loss for epoch 9
0.7407931948409361
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.824028
48 30755 ... 11.951849
49 30756 ... 12.901361
50 30757 ... 12.866081
51 30758 ... 12.723232
52 30759 ... 12.266067
53 30760 ... 10.750948
54 30761 ... 10.552313
55 30762 ... 10.710556
56 30763 ... 10.648995
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5e6yghhl wandb: Agent Starting Run: 49t73wpr with config: batch_size: 2 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 49t73wpr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
27.19437624514103
The number of items in train is:
16
The loss for epoch 0
1.6996485153213143
The running loss is:
23.46845108270645
The number of items in train is:
16
The loss for epoch 1
1.4667781926691532
The running loss is:
23.564942955970764
The number of items in train is:
16
The loss for epoch 2
1.4728089347481728
The running loss is:
21.112747326493263
The number of items in train is:
16
The loss for epoch 3
1.319546707905829
The running loss is:
16.332939110696316
The number of items in train is:
16
The loss for epoch 4
1.0208086944185197
The running loss is:
13.240181624889374
The number of items in train is:
16
The loss for epoch 5
0.8275113515555859
The running loss is:
10.968062326312065
The number of items in train is:
16
The loss for epoch 6
0.6855038953945041
The running loss is:
9.933336228132248
The number of items in train is:
16
The loss for epoch 7
0.6208335142582655
The running loss is:
9.906222566962242
The number of items in train is:
16
The loss for epoch 8
0.6191389104351401
The running loss is:
9.35060365498066
The number of items in train is:
16
The loss for epoch 9
0.5844127284362912
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.286353
48 30755 ... 8.572885
49 30756 ... 9.695906
50 30757 ... 9.246380
51 30758 ... 9.367085
52 30759 ... 7.058271
53 30760 ... 4.291282
54 30761 ... 4.404593
55 30762 ... 4.206285
56 30763 ... 1.904286
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 49t73wpr wandb: Agent Starting Run: fg7lzlcs with config: batch_size: 2 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fg7lzlcs
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
105.85407214425504
The number of items in train is:
17
The loss for epoch 0
6.22671012613265
The running loss is:
28.3312635589391
The number of items in train is:
17
The loss for epoch 1
1.6665449152317118
The running loss is:
22.39996526762843
The number of items in train is:
17
The loss for epoch 2
1.317645015742849
The running loss is:
24.83209763467312
The number of items in train is:
17
The loss for epoch 3
1.460711625569007
The running loss is:
18.151431158185005
The number of items in train is:
17
The loss for epoch 4
1.067731244599118
The running loss is:
15.67039943113923
The number of items in train is:
17
The loss for epoch 5
0.9217882018317195
The running loss is:
16.54207806289196
The number of items in train is:
17
The loss for epoch 6
0.9730634154642329
The running loss is:
15.77171096089296
The number of items in train is:
17
The loss for epoch 7
0.9277477035819388
The running loss is:
13.84425493516028
The number of items in train is:
17
The loss for epoch 8
0.8143679373623693
The running loss is:
14.698465192690492
The number of items in train is:
17
The loss for epoch 9
0.8646155995700289
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.290987
48 30755 ... 12.374711
49 30756 ... 11.975950
50 30757 ... 10.584239
51 30758 ... 11.698794
52 30759 ... 12.389561
53 30760 ... 11.581156
54 30761 ... 11.558187
55 30762 ... 11.589575
56 30763 ... 11.612144
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fg7lzlcs wandb: Agent Starting Run: c0an2nim with config: batch_size: 2 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: c0an2nim
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
68.1619100868702
The number of items in train is:
17
The loss for epoch 0
4.00952412275707
The running loss is:
22.371742129325867
The number of items in train is:
17
The loss for epoch 1
1.3159848311368156
The running loss is:
16.736645698547363
The number of items in train is:
17
The loss for epoch 2
0.9845085705027861
The running loss is:
15.064269214868546
The number of items in train is:
17
The loss for epoch 3
0.8861334832275615
The running loss is:
15.606667906045914
The number of items in train is:
17
The loss for epoch 4
0.9180392885909361
The running loss is:
15.834020808339119
The number of items in train is:
17
The loss for epoch 5
0.9314129887258306
The running loss is:
14.995947480201721
The number of items in train is:
17
The loss for epoch 6
0.8821145576589248
The running loss is:
16.214449003338814
The number of items in train is:
17
The loss for epoch 7
0.9537911178434596
The running loss is:
13.982399955391884
The number of items in train is:
17
The loss for epoch 8
0.822494115023052
The running loss is:
13.378327805548906
The number of items in train is:
17
The loss for epoch 9
0.7869604591499356
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.399013
48 30755 ... 10.975351
49 30756 ... 10.943957
50 30757 ... 11.364924
51 30758 ... 12.050787
52 30759 ... 10.258490
53 30760 ... 11.160790
54 30761 ... 10.898850
55 30762 ... 11.130223
56 30763 ... 10.652694
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c0an2nim wandb: Agent Starting Run: ncqc46kb with config: batch_size: 2 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ncqc46kb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
134.06062477827072
The number of items in train is:
16
The loss for epoch 0
8.37878904864192
The running loss is:
42.89721769094467
The number of items in train is:
16
The loss for epoch 1
2.681076105684042
The running loss is:
42.296622425317764
The number of items in train is:
16
The loss for epoch 2
2.6435389015823603
The running loss is:
14.58924949169159
The number of items in train is:
16
The loss for epoch 3
0.9118280932307243
The running loss is:
13.531480722129345
The number of items in train is:
16
The loss for epoch 4
0.8457175451330841
The running loss is:
11.921478353440762
The number of items in train is:
16
The loss for epoch 5
0.7450923970900476
The running loss is:
11.945398841053247
The number of items in train is:
16
The loss for epoch 6
0.746587427565828
The running loss is:
11.684036530554295
The number of items in train is:
16
The loss for epoch 7
0.7302522831596434
The running loss is:
11.216044843196869
The number of items in train is:
16
The loss for epoch 8
0.7010028026998043
The running loss is:
10.252280615270138
The number of items in train is:
16
The loss for epoch 9
0.6407675384543836
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.261765
48 30755 ... 9.229461
49 30756 ... 9.328590
50 30757 ... 9.209830
51 30758 ... 9.307390
52 30759 ... 9.452641
53 30760 ... 7.193860
54 30761 ... 7.226322
55 30762 ... 7.089177
56 30763 ... 5.841412
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ncqc46kb wandb: Agent Starting Run: yh35fkau with config: batch_size: 2 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yh35fkau
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.99254409223795
The number of items in train is:
17
The loss for epoch 0
1.117208476013997
The running loss is:
27.134451758436626
The number of items in train is:
17
The loss for epoch 1
1.5961442210845074
The running loss is:
14.144931258633733
The number of items in train is:
17
The loss for epoch 2
0.8320547799196314
The running loss is:
12.379254553001374
The number of items in train is:
17
The loss for epoch 3
0.7281914442941985
The running loss is:
10.936451382935047
The number of items in train is:
17
The loss for epoch 4
0.6433206695844146
The running loss is:
10.157983610406518
The number of items in train is:
17
The loss for epoch 5
0.5975284476709717
The running loss is:
10.516974926926196
The number of items in train is:
17
The loss for epoch 6
0.618645583936835
The running loss is:
10.19902788894251
The number of items in train is:
17
The loss for epoch 7
0.5999428169966182
The running loss is:
9.524700343608856
The number of items in train is:
17
The loss for epoch 8
0.560276490800521
The running loss is:
8.423859127797186
The number of items in train is:
17
The loss for epoch 9
0.4955211251645404
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.894247
48 30755 ... 9.785186
49 30756 ... 12.737395
50 30757 ... 12.269347
51 30758 ... 10.923274
52 30759 ... 11.233722
53 30760 ... 10.437478
54 30761 ... 6.463241
55 30762 ... 6.731721
56 30763 ... 7.264863
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yh35fkau wandb: Agent Starting Run: og55gigm with config: batch_size: 2 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: og55gigm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.133108966052532
The number of items in train is:
16
The loss for epoch 0
1.0083193103782833
The running loss is:
28.869964830577374
The number of items in train is:
16
The loss for epoch 1
1.8043728019110858
The running loss is:
12.548532001674175
The number of items in train is:
16
The loss for epoch 2
0.784283250104636
The running loss is:
11.040770269930363
The number of items in train is:
16
The loss for epoch 3
0.6900481418706477
The running loss is:
9.910119865089655
The number of items in train is:
16
The loss for epoch 4
0.6193824915681034
The running loss is:
9.276767298579216
The number of items in train is:
16
The loss for epoch 5
0.579797956161201
The running loss is:
9.77975993603468
The number of items in train is:
16
The loss for epoch 6
0.6112349960021675
The running loss is:
8.785409968346357
The number of items in train is:
16
The loss for epoch 7
0.5490881230216473
The running loss is:
8.258642934262753
The number of items in train is:
16
The loss for epoch 8
0.516165183391422
The running loss is:
8.085627540946007
The number of items in train is:
16
The loss for epoch 9
0.5053517213091254
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.732769
48 30755 ... 5.782502
49 30756 ... 7.366888
50 30757 ... 6.974564
51 30758 ... 5.465569
52 30759 ... 6.234188
53 30760 ... 6.124003
54 30761 ... -0.098097
55 30762 ... -0.405543
56 30763 ... -0.950591
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: og55gigm wandb: Agent Starting Run: lsyxrhtc with config: batch_size: 2 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: lsyxrhtc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.61077520623803
The number of items in train is:
16
The loss for epoch 0
1.038173450389877
The running loss is:
25.137400671839714
The number of items in train is:
16
The loss for epoch 1
1.5710875419899821
The running loss is:
12.270547769963741
The number of items in train is:
16
The loss for epoch 2
0.7669092356227338
The running loss is:
10.999523766338825
The number of items in train is:
16
The loss for epoch 3
0.6874702353961766
The running loss is:
9.699016734957695
The number of items in train is:
16
The loss for epoch 4
0.6061885459348559
The running loss is:
9.058913193643093
The number of items in train is:
16
The loss for epoch 5
0.5661820746026933
The running loss is:
9.072721466422081
The number of items in train is:
16
The loss for epoch 6
0.5670450916513801
The running loss is:
9.164514727890491
The number of items in train is:
16
The loss for epoch 7
0.5727821704931557
The running loss is:
8.674532353878021
The number of items in train is:
16
The loss for epoch 8
0.5421582721173763
The running loss is:
8.324480183422565
The number of items in train is:
16
The loss for epoch 9
0.5202800114639103
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.418834
48 30755 ... 7.616541
49 30756 ... 6.665627
50 30757 ... 7.502685
51 30758 ... 7.146316
52 30759 ... 7.690778
53 30760 ... 7.678141
54 30761 ... 2.797157
55 30762 ... 2.660590
56 30763 ... 2.548421
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lsyxrhtc wandb: Agent Starting Run: raan5oee with config: batch_size: 2 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: raan5oee
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.07104841247201
The number of items in train is:
17
The loss for epoch 0
0.8277087301454124
The running loss is:
22.927550297230482
The number of items in train is:
17
The loss for epoch 1
1.348679429248852
The running loss is:
18.472346489550546
The number of items in train is:
17
The loss for epoch 2
1.086608617032385
The running loss is:
12.637594176456332
The number of items in train is:
17
The loss for epoch 3
0.7433878927327254
The running loss is:
11.350484196096659
The number of items in train is:
17
The loss for epoch 4
0.6676755409468623
The running loss is:
9.470307543873787
The number of items in train is:
17
The loss for epoch 5
0.5570769143455169
The running loss is:
12.329006131738424
The number of items in train is:
17
The loss for epoch 6
0.7252356548081426
The running loss is:
10.936658833175898
The number of items in train is:
17
The loss for epoch 7
0.6433328725397587
The running loss is:
10.534783300827257
The number of items in train is:
17
The loss for epoch 8
0.6196931353427798
The running loss is:
8.076542284339666
The number of items in train is:
17
The loss for epoch 9
0.47509072260821567
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.749610
48 30755 ... 10.477225
49 30756 ... 12.733251
50 30757 ... 11.301854
51 30758 ... 10.135816
52 30759 ... 11.677883
53 30760 ... 14.390694
54 30761 ... 9.135997
55 30762 ... 8.562580
56 30763 ... 7.725478
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: raan5oee wandb: Agent Starting Run: 78dfcr0h with config: batch_size: 2 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 78dfcr0h
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.633374132215977
The number of items in train is:
16
The loss for epoch 0
0.7895858832634985
The running loss is:
24.585037760436535
The number of items in train is:
16
The loss for epoch 1
1.5365648600272834
The running loss is:
20.226487666368484
The number of items in train is:
16
The loss for epoch 2
1.2641554791480303
The running loss is:
10.598256275057793
The number of items in train is:
16
The loss for epoch 3
0.662391017191112
The running loss is:
10.891551569104195
The number of items in train is:
16
The loss for epoch 4
0.6807219730690122
The running loss is:
9.729584485292435
The number of items in train is:
16
The loss for epoch 5
0.6080990303307772
The running loss is:
10.25032301992178
The number of items in train is:
16
The loss for epoch 6
0.6406451887451112
The running loss is:
12.466548934578896
The number of items in train is:
16
The loss for epoch 7
0.779159308411181
The running loss is:
9.112505622208118
The number of items in train is:
16
The loss for epoch 8
0.5695316013880074
The running loss is:
8.59875401854515
The number of items in train is:
16
The loss for epoch 9
0.5374221261590719
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.815525
48 30755 ... 4.415236
49 30756 ... 3.473031
50 30757 ... 4.546901
51 30758 ... 4.515433
52 30759 ... 4.815760
53 30760 ... 5.747679
54 30761 ... 2.746140
55 30762 ... 1.751836
56 30763 ... 1.695187
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 78dfcr0h wandb: Agent Starting Run: hoczfgq1 with config: batch_size: 2 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hoczfgq1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.084807999432087
The number of items in train is:
16
The loss for epoch 0
0.7553004999645054
The running loss is:
22.603727489709854
The number of items in train is:
16
The loss for epoch 1
1.4127329681068659
The running loss is:
18.862066105008125
The number of items in train is:
16
The loss for epoch 2
1.1788791315630078
The running loss is:
12.395430564880371
The number of items in train is:
16
The loss for epoch 3
0.7747144103050232
The running loss is:
11.394499212503433
The number of items in train is:
16
The loss for epoch 4
0.7121562007814646
The running loss is:
10.081028185784817
The number of items in train is:
16
The loss for epoch 5
0.630064261611551
The running loss is:
9.585860520601273
The number of items in train is:
16
The loss for epoch 6
0.5991162825375795
The running loss is:
11.116112791001797
The number of items in train is:
16
The loss for epoch 7
0.6947570494376123
The running loss is:
9.021495692431927
The number of items in train is:
16
The loss for epoch 8
0.5638434807769954
The running loss is:
8.90778385847807
The number of items in train is:
16
The loss for epoch 9
0.5567364911548793
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.413387
48 30755 ... 5.729298
49 30756 ... 4.455645
50 30757 ... 6.159957
51 30758 ... 5.956176
52 30759 ... 6.667638
53 30760 ... 7.277160
54 30761 ... 4.641956
55 30762 ... 4.200748
56 30763 ... 4.200795
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hoczfgq1 wandb: Agent Starting Run: c27e7jkt with config: batch_size: 2 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: c27e7jkt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.021860733628273
The number of items in train is:
17
The loss for epoch 0
1.118932984331075
The running loss is:
19.840141020715237
The number of items in train is:
17
The loss for epoch 1
1.167067118865602
The running loss is:
19.325562549754977
The number of items in train is:
17
The loss for epoch 2
1.1367977970444105
The running loss is:
14.916489260271192
The number of items in train is:
17
The loss for epoch 3
0.8774405447218347
The running loss is:
13.93316643126309
The number of items in train is:
17
The loss for epoch 4
0.819598025368417
The running loss is:
10.690809190273285
The number of items in train is:
17
The loss for epoch 5
0.6288711288396049
The running loss is:
13.479163165204227
The number of items in train is:
17
The loss for epoch 6
0.7928919508943663
The running loss is:
14.082069613039494
The number of items in train is:
17
The loss for epoch 7
0.8283570360611466
The running loss is:
12.653895137831569
The number of items in train is:
17
The loss for epoch 8
0.7443467728136217
The running loss is:
10.394164901226759
The number of items in train is:
17
The loss for epoch 9
0.6114214647780446
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.782250
48 30755 ... 6.847810
49 30756 ... 8.922386
50 30757 ... 9.392108
51 30758 ... 7.796653
52 30759 ... 9.359842
53 30760 ... 10.251583
54 30761 ... 9.111098
55 30762 ... 4.847028
56 30763 ... 8.793217
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c27e7jkt wandb: Agent Starting Run: rc0hdh5k with config: batch_size: 2 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: rc0hdh5k
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.67585827410221
The number of items in train is:
16
The loss for epoch 0
1.2297411421313882
The running loss is:
20.92596773058176
The number of items in train is:
16
The loss for epoch 1
1.30787298316136
The running loss is:
21.21123907715082
The number of items in train is:
16
The loss for epoch 2
1.3257024423219264
The running loss is:
13.602266885340214
The number of items in train is:
16
The loss for epoch 3
0.8501416803337634
The running loss is:
12.655046753585339
The number of items in train is:
16
The loss for epoch 4
0.7909404220990837
The running loss is:
10.041675612330437
The number of items in train is:
16
The loss for epoch 5
0.6276047257706523
The running loss is:
12.342215452343225
The number of items in train is:
16
The loss for epoch 6
0.7713884657714516
The running loss is:
14.822323441505432
The number of items in train is:
16
The loss for epoch 7
0.9263952150940895
The running loss is:
10.33838652074337
The number of items in train is:
16
The loss for epoch 8
0.6461491575464606
The running loss is:
12.166576441377401
The number of items in train is:
16
The loss for epoch 9
0.7604110275860876
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.075967
48 30755 ... 9.071111
49 30756 ... 9.542653
50 30757 ... 9.827929
51 30758 ... 10.330853
52 30759 ... 9.926955
53 30760 ... 9.483013
54 30761 ... 6.208332
55 30762 ... 5.910884
56 30763 ... 6.146338
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rc0hdh5k wandb: Agent Starting Run: 0dph3cu7 with config: batch_size: 2 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 0dph3cu7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.855378910899162
The number of items in train is:
16
The loss for epoch 0
1.0534611819311976
The running loss is:
20.029029339551926
The number of items in train is:
16
The loss for epoch 1
1.2518143337219954
The running loss is:
16.415701150894165
The number of items in train is:
16
The loss for epoch 2
1.0259813219308853
The running loss is:
15.392409943044186
The number of items in train is:
16
The loss for epoch 3
0.9620256214402616
The running loss is:
12.786209851503372
The number of items in train is:
16
The loss for epoch 4
0.7991381157189608
The running loss is:
10.640215292572975
The number of items in train is:
16
The loss for epoch 5
0.665013455785811
The running loss is:
10.768309026956558
The number of items in train is:
16
The loss for epoch 6
0.6730193141847849
The running loss is:
12.681664541363716
The number of items in train is:
16
The loss for epoch 7
0.7926040338352323
The running loss is:
10.68557322025299
The number of items in train is:
16
The loss for epoch 8
0.6678483262658119
The running loss is:
9.19628544151783
The number of items in train is:
16
The loss for epoch 9
0.5747678400948644
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.187110
48 30755 ... 8.600869
49 30756 ... 7.328359
50 30757 ... 9.198733
51 30758 ... 10.732364
52 30759 ... 10.814871
53 30760 ... 12.901135
54 30761 ... 3.767852
55 30762 ... 2.326275
56 30763 ... 3.856884
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0dph3cu7 wandb: Agent Starting Run: scb18cx2 with config: batch_size: 2 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: scb18cx2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
95.02955102175474
The number of items in train is:
17
The loss for epoch 0
5.589973589514985
The running loss is:
24.03973775357008
The number of items in train is:
17
The loss for epoch 1
1.4141022207982399
The running loss is:
15.009492529556155
The number of items in train is:
17
The loss for epoch 2
0.8829113252680091
The running loss is:
15.12568387016654
The number of items in train is:
17
The loss for epoch 3
0.8897461100097965
The running loss is:
14.419101245701313
The number of items in train is:
17
The loss for epoch 4
0.8481824262177243
The running loss is:
14.80416202545166
The number of items in train is:
17
The loss for epoch 5
0.8708330603206859
The running loss is:
14.07496515661478
The number of items in train is:
17
The loss for epoch 6
0.827939126859693
The running loss is:
16.150368846952915
The number of items in train is:
17
The loss for epoch 7
0.9500216968795833
The running loss is:
13.275858359294944
The number of items in train is:
17
The loss for epoch 8
0.7809328446644085
The running loss is:
10.595419317483902
The number of items in train is:
17
The loss for epoch 9
0.6232599598519942
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 15.195083
48 30755 ... 12.213925
49 30756 ... 6.223370
50 30757 ... 10.297009
51 30758 ... 10.625719
52 30759 ... 12.546183
53 30760 ... 13.704164
54 30761 ... 12.491216
55 30762 ... 12.667259
56 30763 ... 12.886582
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: scb18cx2 wandb: Agent Starting Run: wzhv9dbd with config: batch_size: 2 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: wzhv9dbd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
95.46283769607544
The number of items in train is:
16
The loss for epoch 0
5.966427356004715
The running loss is:
27.861441023647785
The number of items in train is:
16
The loss for epoch 1
1.7413400639779866
The running loss is:
13.78494793176651
The number of items in train is:
16
The loss for epoch 2
0.8615592457354069
The running loss is:
21.267036229372025
The number of items in train is:
16
The loss for epoch 3
1.3291897643357515
The running loss is:
19.88978810235858
The number of items in train is:
16
The loss for epoch 4
1.2431117563974112
The running loss is:
15.775068141520023
The number of items in train is:
16
The loss for epoch 5
0.9859417588450015
The running loss is:
14.655570544302464
The number of items in train is:
16
The loss for epoch 6
0.915973159018904
The running loss is:
14.580344870686531
The number of items in train is:
16
The loss for epoch 7
0.9112715544179082
The running loss is:
12.412341699004173
The number of items in train is:
16
The loss for epoch 8
0.7757713561877608
The running loss is:
12.429722763597965
The number of items in train is:
16
The loss for epoch 9
0.7768576727248728
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.551174
48 30755 ... 10.476337
49 30756 ... 8.249887
50 30757 ... 6.252807
51 30758 ... 11.140751
52 30759 ... 10.062581
53 30760 ... 13.128551
54 30761 ... 8.388356
55 30762 ... 8.294368
56 30763 ... 8.297700
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wzhv9dbd wandb: Agent Starting Run: g6lldpjl with config: batch_size: 2 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: g6lldpjl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
74.41158412396908
The number of items in train is:
16
The loss for epoch 0
4.650724007748067
The running loss is:
21.020324990153313
The number of items in train is:
16
The loss for epoch 1
1.313770311884582
The running loss is:
16.04583202302456
The number of items in train is:
16
The loss for epoch 2
1.002864501439035
The running loss is:
17.90377826243639
The number of items in train is:
16
The loss for epoch 3
1.1189861414022744
The running loss is:
14.566076338291168
The number of items in train is:
16
The loss for epoch 4
0.910379771143198
The running loss is:
14.132137462496758
The number of items in train is:
16
The loss for epoch 5
0.8832585914060473
The running loss is:
13.948560565710068
The number of items in train is:
16
The loss for epoch 6
0.8717850353568792
The running loss is:
13.438048601150513
The number of items in train is:
16
The loss for epoch 7
0.839878037571907
The running loss is:
13.514577560126781
The number of items in train is:
16
The loss for epoch 8
0.8446610975079238
The running loss is:
12.867796912789345
The number of items in train is:
16
The loss for epoch 9
0.804237307049334
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.610271
48 30755 ... 10.570126
49 30756 ... 10.616474
50 30757 ... 10.498391
51 30758 ... 11.009744
52 30759 ... 10.557771
53 30760 ... 10.617533
54 30761 ... 10.595282
55 30762 ... 10.595298
56 30763 ... 10.593192
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: g6lldpjl wandb: Agent Starting Run: 5kgpjqql with config: batch_size: 3 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5kgpjqql
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.670363292098045
The number of items in train is:
14
The loss for epoch 0
1.2621688065784318
The running loss is:
10.943816676735878
The number of items in train is:
14
The loss for epoch 1
0.7817011911954198
The running loss is:
10.41209028288722
The number of items in train is:
14
The loss for epoch 2
0.7437207344919443
The running loss is:
9.48156014829874
The number of items in train is:
14
The loss for epoch 3
0.6772542963070529
The running loss is:
9.911844491958618
The number of items in train is:
14
The loss for epoch 4
0.7079888922827584
The running loss is:
9.89071624726057
The number of items in train is:
14
The loss for epoch 5
0.7064797319471836
The running loss is:
9.785955913364887
The number of items in train is:
14
The loss for epoch 6
0.6989968509546348
The running loss is:
9.477959398645908
The number of items in train is:
14
The loss for epoch 7
0.6769970999032792
The running loss is:
10.341568265110254
The number of items in train is:
14
The loss for epoch 8
0.7386834475078753
The running loss is:
10.629889108240604
The number of items in train is:
14
The loss for epoch 9
0.7592777934457574
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 12.328932
48 30755 ... 11.992808
49 30756 ... 11.800481
50 30757 ... 11.669888
51 30758 ... 11.565799
52 30759 ... 11.473088
53 30760 ... 11.385262
54 30761 ... 11.635700
55 30762 ... 11.695193
56 30763 ... 11.672710
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5kgpjqql wandb: Agent Starting Run: 7qvksyb1 with config: batch_size: 3 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 7qvksyb1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.802268385887146
The number of items in train is:
14
The loss for epoch 0
1.6287334561347961
The running loss is:
17.569238662719727
The number of items in train is:
14
The loss for epoch 1
1.2549456187656947
The running loss is:
16.22460624575615
The number of items in train is:
14
The loss for epoch 2
1.1589004461254393
The running loss is:
14.956971347332
The number of items in train is:
14
The loss for epoch 3
1.068355096238
The running loss is:
15.105294823646545
The number of items in train is:
14
The loss for epoch 4
1.0789496302604675
The running loss is:
15.303263306617737
The number of items in train is:
14
The loss for epoch 5
1.0930902361869812
The running loss is:
15.001798063516617
The number of items in train is:
14
The loss for epoch 6
1.0715570045369012
The running loss is:
14.771975100040436
The number of items in train is:
14
The loss for epoch 7
1.055141078574317
The running loss is:
14.277655333280563
The number of items in train is:
14
The loss for epoch 8
1.0198325238057546
The running loss is:
14.258073136210442
The number of items in train is:
14
The loss for epoch 9
1.018433795443603
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 17.221895
48 30755 ... 19.612215
49 30756 ... 20.901167
50 30757 ... 21.527845
51 30758 ... 21.756281
52 30759 ... 21.745245
53 30760 ... 21.590210
54 30761 ... 22.387379
55 30762 ... 22.718334
56 30763 ... 22.768944
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7qvksyb1 wandb: Agent Starting Run: py7m8aa2 with config: batch_size: 3 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: py7m8aa2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.336795777082443
The number of items in train is:
14
The loss for epoch 0
1.5954854126487459
The running loss is:
16.64599171280861
The number of items in train is:
14
The loss for epoch 1
1.1889994080577577
The running loss is:
14.604424864053726
The number of items in train is:
14
The loss for epoch 2
1.0431732045752662
The running loss is:
14.123595744371414
The number of items in train is:
14
The loss for epoch 3
1.008828267455101
The running loss is:
14.480102002620697
The number of items in train is:
14
The loss for epoch 4
1.0342930001871926
The running loss is:
13.984807938337326
The number of items in train is:
14
The loss for epoch 5
0.9989148527383804
The running loss is:
14.12735378742218
The number of items in train is:
14
The loss for epoch 6
1.0090966991015844
The running loss is:
14.249413669109344
The number of items in train is:
14
The loss for epoch 7
1.017815262079239
The running loss is:
13.871794015169144
The number of items in train is:
14
The loss for epoch 8
0.9908424296549388
The running loss is:
13.480072140693665
The number of items in train is:
14
The loss for epoch 9
0.9628622957638332
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 7.018013
48 30755 ... 3.923897
49 30756 ... 2.033710
50 30757 ... 0.645433
51 30758 ... -0.533605
52 30759 ... -1.625411
53 30760 ... -2.680852
54 30761 ... 0.480797
55 30762 ... 1.198586
56 30763 ... 0.897552
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: py7m8aa2 wandb: Agent Starting Run: fhkws31a with config: batch_size: 3 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fhkws31a
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.473997741937637
The number of items in train is:
14
The loss for epoch 0
0.9624284101384026
The running loss is:
27.837897576391697
The number of items in train is:
14
The loss for epoch 1
1.9884212554565497
The running loss is:
11.861431896686554
The number of items in train is:
14
The loss for epoch 2
0.847245135477611
The running loss is:
10.067777810618281
The number of items in train is:
14
The loss for epoch 3
0.7191269864727344
The running loss is:
9.917817741632462
The number of items in train is:
14
The loss for epoch 4
0.7084155529737473
The running loss is:
9.74946603924036
The number of items in train is:
14
The loss for epoch 5
0.6963904313743114
The running loss is:
9.383864752948284
The number of items in train is:
14
The loss for epoch 6
0.6702760537820203
The running loss is:
9.33708634832874
The number of items in train is:
14
The loss for epoch 7
0.6669347391663385
The running loss is:
10.058764830231667
The number of items in train is:
14
The loss for epoch 8
0.7184832021594048
The running loss is:
10.721103806048632
The number of items in train is:
14
The loss for epoch 9
0.7657931290034737
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 12.203970
48 30755 ... 11.892198
49 30756 ... 11.772248
50 30757 ... 11.728283
51 30758 ... 11.714417
52 30759 ... 11.712473
53 30760 ... 11.715252
54 30761 ... 11.695059
55 30762 ... 11.690609
56 30763 ... 11.692395
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fhkws31a wandb: Agent Starting Run: o8fp0wdh with config: batch_size: 3 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: o8fp0wdh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.880937218666077
The number of items in train is:
14
The loss for epoch 0
1.3486383727618627
The running loss is:
30.557601034641266
The number of items in train is:
14
The loss for epoch 1
2.1826857881886617
The running loss is:
16.620768785476685
The number of items in train is:
14
The loss for epoch 2
1.1871977703911918
The running loss is:
15.550219416618347
The number of items in train is:
14
The loss for epoch 3
1.110729958329882
The running loss is:
14.529386848211288
The number of items in train is:
14
The loss for epoch 4
1.0378133463008063
The running loss is:
14.709754675626755
The number of items in train is:
14
The loss for epoch 5
1.0506967625447683
The running loss is:
14.263691067695618
The number of items in train is:
14
The loss for epoch 6
1.0188350762639726
The running loss is:
13.642646819353104
The number of items in train is:
14
The loss for epoch 7
0.974474772810936
The running loss is:
13.388307765126228
The number of items in train is:
14
The loss for epoch 8
0.9563076975090163
The running loss is:
13.098741456866264
The number of items in train is:
14
The loss for epoch 9
0.9356243897761617
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 16.511818
48 30755 ... 18.479959
49 30756 ... 19.515354
50 30757 ... 19.987150
51 30758 ... 20.118399
52 30759 ... 20.043875
53 30760 ... 19.845016
54 30761 ... 20.647829
55 30762 ... 20.979090
56 30763 ... 21.025421
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: o8fp0wdh wandb: Agent Starting Run: npyvux13 with config: batch_size: 3 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: npyvux13
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.19215828180313
The number of items in train is:
14
The loss for epoch 0
1.2280113058430808
The running loss is:
35.54996246099472
The number of items in train is:
14
The loss for epoch 1
2.539283032928194
The running loss is:
16.276898205280304
The number of items in train is:
14
The loss for epoch 2
1.1626355860914503
The running loss is:
15.494183450937271
The number of items in train is:
14
The loss for epoch 3
1.1067273893526621
The running loss is:
13.394286423921585
The number of items in train is:
14
The loss for epoch 4
0.9567347445658275
The running loss is:
13.729548782110214
The number of items in train is:
14
The loss for epoch 5
0.9806820558650153
The running loss is:
13.483346164226532
The number of items in train is:
14
The loss for epoch 6
0.9630961545876094
The running loss is:
13.767163097858429
The number of items in train is:
14
The loss for epoch 7
0.9833687927041735
The running loss is:
13.156352579593658
The number of items in train is:
14
The loss for epoch 8
0.9397394699709756
The running loss is:
12.842736065387726
The number of items in train is:
14
The loss for epoch 9
0.9173382903848376
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 7.175701
48 30755 ... 4.349280
49 30756 ... 2.709584
50 30757 ... 1.539658
51 30758 ... 0.555692
52 30759 ... -0.354660
53 30760 ... -1.235872
54 30761 ... 1.540366
55 30762 ... 2.118507
56 30763 ... 1.826522
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: npyvux13 wandb: Agent Starting Run: v4j861hu with config: batch_size: 3 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: v4j861hu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.81423806399107
The number of items in train is:
14
The loss for epoch 0
1.272445575999362
The running loss is:
27.287052668631077
The number of items in train is:
14
The loss for epoch 1
1.9490751906165056
The running loss is:
23.304617062211037
The number of items in train is:
14
The loss for epoch 2
1.6646155044436455
The running loss is:
13.46847514808178
The number of items in train is:
14
The loss for epoch 3
0.9620339391486985
The running loss is:
10.77438042499125
The number of items in train is:
14
The loss for epoch 4
0.7695986017850893
The running loss is:
10.228682920336723
The number of items in train is:
14
The loss for epoch 5
0.7306202085954803
The running loss is:
9.9163583740592
The number of items in train is:
14
The loss for epoch 6
0.7083113124328
The running loss is:
9.541842748411
The number of items in train is:
14
The loss for epoch 7
0.6815601963150714
The running loss is:
10.52641460672021
The number of items in train is:
14
The loss for epoch 8
0.751886757622872
The running loss is:
10.936396487057209
The number of items in train is:
14
The loss for epoch 9
0.7811711776469435
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.996588
48 30755 ... 11.617249
49 30756 ... 11.487004
50 30757 ... 11.456182
51 30758 ... 11.465044
52 30759 ... 11.489745
53 30760 ... 11.520768
54 30761 ... 11.406167
55 30762 ... 11.381589
56 30763 ... 11.392943
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v4j861hu wandb: Agent Starting Run: pb2xg24u with config: batch_size: 3 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: pb2xg24u
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.450218737125397
The number of items in train is:
14
The loss for epoch 0
1.3178727669375283
The running loss is:
33.69246228039265
The number of items in train is:
14
The loss for epoch 1
2.4066044485994746
The running loss is:
30.424543470144272
The number of items in train is:
14
The loss for epoch 2
2.1731816764388765
The running loss is:
21.68705663084984
The number of items in train is:
14
The loss for epoch 3
1.5490754736321313
The running loss is:
15.464419141411781
The number of items in train is:
14
The loss for epoch 4
1.1046013672436987
The running loss is:
13.43197026848793
The number of items in train is:
14
The loss for epoch 5
0.9594264477491379
The running loss is:
13.450857311487198
The number of items in train is:
14
The loss for epoch 6
0.9607755222490856
The running loss is:
12.503621444106102
The number of items in train is:
14
The loss for epoch 7
0.8931158174361501
The running loss is:
12.548032850027084
The number of items in train is:
14
The loss for epoch 8
0.8962880607162204
The running loss is:
12.026508867740631
The number of items in train is:
14
The loss for epoch 9
0.8590363476957593
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 15.448249
48 30755 ... 16.847450
49 30756 ... 17.598450
50 30757 ... 17.948925
51 30758 ... 18.051918
52 30759 ... 18.001993
53 30760 ... 17.857580
54 30761 ... 18.449734
55 30762 ... 18.702061
56 30763 ... 18.744408
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pb2xg24u wandb: Agent Starting Run: w8s1lsld with config: batch_size: 3 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: w8s1lsld
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.729584485292435
The number of items in train is:
14
The loss for epoch 0
1.194970320378031
The running loss is:
31.90469980239868
The number of items in train is:
14
The loss for epoch 1
2.278907128742763
The running loss is:
26.94806531071663
The number of items in train is:
14
The loss for epoch 2
1.9248618079083306
The running loss is:
21.172048971056938
The number of items in train is:
14
The loss for epoch 3
1.5122892122183527
The running loss is:
14.548314154148102
The number of items in train is:
14
The loss for epoch 4
1.0391652967248644
The running loss is:
14.059065759181976
The number of items in train is:
14
The loss for epoch 5
1.0042189827987127
The running loss is:
13.152787834405899
The number of items in train is:
14
The loss for epoch 6
0.9394848453147071
The running loss is:
13.332339078187943
The number of items in train is:
14
The loss for epoch 7
0.9523099341562816
The running loss is:
12.577288955450058
The number of items in train is:
14
The loss for epoch 8
0.898377782532147
The running loss is:
12.499642044305801
The number of items in train is:
14
The loss for epoch 9
0.8928315745932716
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 8.248249
48 30755 ... 6.103832
49 30756 ... 4.877185
50 30757 ... 3.973589
51 30758 ... 3.183706
52 30759 ... 2.433849
53 30760 ... 1.698083
54 30761 ... 4.270024
55 30762 ... 4.703514
56 30763 ... 4.384280
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: w8s1lsld wandb: Agent Starting Run: 5rzp4ajy with config: batch_size: 3 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5rzp4ajy
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
36.93057554960251
The number of items in train is:
14
The loss for epoch 0
2.637898253543036
The running loss is:
26.37780451774597
The number of items in train is:
14
The loss for epoch 1
1.8841288941247123
The running loss is:
22.75959214195609
The number of items in train is:
14
The loss for epoch 2
1.6256851529968637
The running loss is:
30.54565773718059
The number of items in train is:
14
The loss for epoch 3
2.1818326955128993
The running loss is:
36.84430718794465
The number of items in train is:
14
The loss for epoch 4
2.631736227710332
The running loss is:
36.018092423677444
The number of items in train is:
14
The loss for epoch 5
2.5727208874055316
The running loss is:
19.373262114822865
The number of items in train is:
14
The loss for epoch 6
1.3838044367730618
The running loss is:
11.502933956682682
The number of items in train is:
14
The loss for epoch 7
0.8216381397630487
The running loss is:
10.898656576871872
The number of items in train is:
14
The loss for epoch 8
0.7784754697765622
The running loss is:
10.19880486652255
The number of items in train is:
14
The loss for epoch 9
0.7284860618944679
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 12.216917
48 30755 ... 11.971518
49 30756 ... 11.933516
50 30757 ... 11.975511
51 30758 ... 12.048363
52 30759 ... 12.133118
53 30760 ... 12.222463
54 30761 ... 11.917004
55 30762 ... 11.855834
56 30763 ... 11.888893
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5rzp4ajy wandb: Agent Starting Run: 3ek9rvyd with config: batch_size: 3 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 3ek9rvyd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
41.207330763339996
The number of items in train is:
14
The loss for epoch 0
2.9433807688099995
The running loss is:
27.082152098417282
The number of items in train is:
14
The loss for epoch 1
1.9344394356012344
The running loss is:
25.876445710659027
The number of items in train is:
14
The loss for epoch 2
1.8483175507613592
The running loss is:
33.90110743790865
The number of items in train is:
14
The loss for epoch 3
2.421507674136332
The running loss is:
44.29538279771805
The number of items in train is:
14
The loss for epoch 4
3.1639559141227176
The running loss is:
37.04779974371195
The number of items in train is:
14
The loss for epoch 5
2.6462714102651392
The running loss is:
17.184944421052933
The number of items in train is:
14
The loss for epoch 6
1.2274960300752096
The running loss is:
13.733961462974548
The number of items in train is:
14
The loss for epoch 7
0.9809972473553249
The running loss is:
14.716185823082924
The number of items in train is:
14
The loss for epoch 8
1.0511561302202088
The running loss is:
13.83261838182807
The number of items in train is:
14
The loss for epoch 9
0.9880441701305764
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 9.035178
48 30755 ... 8.766874
49 30756 ... 8.916343
50 30757 ... 9.113027
51 30758 ... 9.315046
52 30759 ... 9.517670
53 30760 ... 9.720361
54 30761 ... 8.664521
55 30762 ... 8.724984
56 30763 ... 8.911608
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3ek9rvyd wandb: Agent Starting Run: 874h0d1x with config: batch_size: 3 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 874h0d1x
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
44.45691132545471
The number of items in train is:
14
The loss for epoch 0
3.175493666103908
The running loss is:
29.342597395181656
The number of items in train is:
14
The loss for epoch 1
2.095899813941547
The running loss is:
31.56341904401779
The number of items in train is:
14
The loss for epoch 2
2.2545299317155565
The running loss is:
22.378557235002518
The number of items in train is:
14
The loss for epoch 3
1.5984683739287513
The running loss is:
29.19557212293148
The number of items in train is:
14
The loss for epoch 4
2.08539800878082
The running loss is:
19.708526015281677
The number of items in train is:
14
The loss for epoch 5
1.4077518582344055
The running loss is:
16.751707702875137
The number of items in train is:
14
The loss for epoch 6
1.196550550205367
The running loss is:
17.867665767669678
The number of items in train is:
14
The loss for epoch 7
1.276261840547834
The running loss is:
17.180501848459244
The number of items in train is:
14
The loss for epoch 8
1.2271787034613746
The running loss is:
11.488581970334053
The number of items in train is:
14
The loss for epoch 9
0.8206129978810038
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 9.363071
48 30755 ... 8.094663
49 30756 ... 7.382749
50 30757 ... 6.801587
51 30758 ... 6.251144
52 30759 ... 5.707920
53 30760 ... 5.166392
54 30761 ... 7.522529
55 30762 ... 7.662219
56 30763 ... 7.281145
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 874h0d1x wandb: Agent Starting Run: 59n65cyk with config: batch_size: 3 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 59n65cyk
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.64117774181068
The number of items in train is:
14
The loss for epoch 0
1.3315126958436199
The running loss is:
13.435925766825676
The number of items in train is:
14
The loss for epoch 1
0.9597089833446911
The running loss is:
9.767426192760468
The number of items in train is:
14
The loss for epoch 2
0.6976732994828906
The running loss is:
8.82443618774414
The number of items in train is:
14
The loss for epoch 3
0.6303168705531529
The running loss is:
8.694632604718208
The number of items in train is:
14
The loss for epoch 4
0.6210451860513005
The running loss is:
9.05456755310297
The number of items in train is:
14
The loss for epoch 5
0.6467548252216407
The running loss is:
8.356636479496956
The number of items in train is:
14
The loss for epoch 6
0.596902605678354
The running loss is:
9.370028473436832
The number of items in train is:
14
The loss for epoch 7
0.6692877481026309
The running loss is:
9.064932033419609
The number of items in train is:
14
The loss for epoch 8
0.6474951452442578
The running loss is:
7.789532475173473
The number of items in train is:
14
The loss for epoch 9
0.5563951767981052
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.928371
48 30755 ... 15.471230
49 30756 ... 15.420227
50 30757 ... 15.615501
51 30758 ... 14.940125
52 30759 ... 14.135720
53 30760 ... 12.981010
54 30761 ... 14.701076
55 30762 ... 15.958694
56 30763 ... 16.192640
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 59n65cyk wandb: Agent Starting Run: mwiqfbe8 with config: batch_size: 3 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: mwiqfbe8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.326901137828827
The number of items in train is:
14
The loss for epoch 0
1.3090643669877733
The running loss is:
15.11211396753788
The number of items in train is:
14
The loss for epoch 1
1.0794367119669914
The running loss is:
12.211668342351913
The number of items in train is:
14
The loss for epoch 2
0.8722620244537082
The running loss is:
11.787426233291626
The number of items in train is:
14
The loss for epoch 3
0.8419590166636876
The running loss is:
11.032762914896011
The number of items in train is:
14
The loss for epoch 4
0.7880544939211437
The running loss is:
10.791624754667282
The number of items in train is:
14
The loss for epoch 5
0.7708303396190915
The running loss is:
10.629769459366798
The number of items in train is:
14
The loss for epoch 6
0.7592692470976284
The running loss is:
10.726359777152538
The number of items in train is:
14
The loss for epoch 7
0.7661685555108956
The running loss is:
10.42826895415783
The number of items in train is:
14
The loss for epoch 8
0.7448763538684163
The running loss is:
10.19526007771492
The number of items in train is:
14
The loss for epoch 9
0.7282328626939228
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.490717
48 30755 ... 11.641187
49 30756 ... 9.905563
50 30757 ... 9.972510
51 30758 ... 8.155688
52 30759 ... 6.332791
53 30760 ... 3.572726
54 30761 ... 2.926773
55 30762 ... 4.603442
56 30763 ... 4.082183
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mwiqfbe8 wandb: Agent Starting Run: odk5x886 with config: batch_size: 3 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: odk5x886
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.417068786919117
The number of items in train is:
13
The loss for epoch 0
1.3397745220707014
The running loss is:
12.89317137002945
The number of items in train is:
13
The loss for epoch 1
0.9917824130791885
The running loss is:
10.928997546434402
The number of items in train is:
13
The loss for epoch 2
0.8406921189564925
The running loss is:
9.924030363559723
The number of items in train is:
13
The loss for epoch 3
0.7633869510430557
The running loss is:
9.564537711441517
The number of items in train is:
13
The loss for epoch 4
0.7357336701108859
The running loss is:
9.373335793614388
The number of items in train is:
13
The loss for epoch 5
0.7210258302780298
The running loss is:
9.464933928102255
The number of items in train is:
13
The loss for epoch 6
0.7280718406232504
The running loss is:
8.969834722578526
The number of items in train is:
13
The loss for epoch 7
0.6899872863521943
The running loss is:
9.041607558727264
The number of items in train is:
13
The loss for epoch 8
0.6955082737482511
The running loss is:
8.688183203339577
The number of items in train is:
13
The loss for epoch 9
0.6683217848722751
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.460793
48 30755 ... 12.863463
49 30756 ... 13.743500
50 30757 ... 14.807247
51 30758 ... 15.064708
52 30759 ... 14.955314
53 30760 ... 14.306695
54 30761 ... 16.493378
55 30762 ... 18.610914
56 30763 ... 19.960632
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: odk5x886 wandb: Agent Starting Run: t7774fje with config: batch_size: 3 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: t7774fje
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.82401143014431
The number of items in train is:
14
The loss for epoch 0
1.058857959296022
The running loss is:
32.10828600823879
The number of items in train is:
14
The loss for epoch 1
2.293449000588485
The running loss is:
16.21480782330036
The number of items in train is:
14
The loss for epoch 2
1.1582005588071687
The running loss is:
10.950186144560575
The number of items in train is:
14
The loss for epoch 3
0.7821561531828982
The running loss is:
9.553723186254501
The number of items in train is:
14
The loss for epoch 4
0.6824087990181786
The running loss is:
9.226969838142395
The number of items in train is:
14
The loss for epoch 5
0.6590692741530282
The running loss is:
8.455528162419796
The number of items in train is:
14
The loss for epoch 6
0.6039662973156997
The running loss is:
8.660504542291164
The number of items in train is:
14
The loss for epoch 7
0.6186074673065117
The running loss is:
9.142078697681427
The number of items in train is:
14
The loss for epoch 8
0.653005621262959
The running loss is:
7.957540884613991
The number of items in train is:
14
The loss for epoch 9
0.5683957774724279
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.434075
48 30755 ... 15.096694
49 30756 ... 14.959582
50 30757 ... 14.883185
51 30758 ... 14.149712
52 30759 ... 13.306772
53 30760 ... 12.192998
54 30761 ... 13.766081
55 30762 ... 14.880667
56 30763 ... 15.032399
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: t7774fje wandb: Agent Starting Run: hebxlk2l with config: batch_size: 3 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: hebxlk2l
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.723597005009651
The number of items in train is:
14
The loss for epoch 0
1.1231140717864037
The running loss is:
28.490644335746765
The number of items in train is:
14
The loss for epoch 1
2.035046023981912
The running loss is:
13.955412358045578
The number of items in train is:
14
The loss for epoch 2
0.996815168431827
The running loss is:
13.241860419511795
The number of items in train is:
14
The loss for epoch 3
0.945847172822271
The running loss is:
11.466906487941742
The number of items in train is:
14
The loss for epoch 4
0.8190647491386959
The running loss is:
10.924891918897629
The number of items in train is:
14
The loss for epoch 5
0.780349422778402
The running loss is:
10.513674184679985
The number of items in train is:
14
The loss for epoch 6
0.7509767274771418
The running loss is:
9.895356297492981
The number of items in train is:
14
The loss for epoch 7
0.7068111641066415
The running loss is:
9.991915211081505
The number of items in train is:
14
The loss for epoch 8
0.7137082293629646
The running loss is:
9.326003551483154
The number of items in train is:
14
The loss for epoch 9
0.6661431108202253
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.664345
48 30755 ... 13.185613
49 30756 ... 11.520662
50 30757 ... 11.929882
51 30758 ... 10.195442
52 30759 ... 8.390749
53 30760 ... 5.661302
54 30761 ... 5.480610
55 30762 ... 7.734272
56 30763 ... 7.415340
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hebxlk2l wandb: Agent Starting Run: f9q3bn5p with config: batch_size: 3 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: f9q3bn5p
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.760922595858574
The number of items in train is:
13
The loss for epoch 0
1.0585325073737364
The running loss is:
28.3547403216362
The number of items in train is:
13
The loss for epoch 1
2.1811338708950925
The running loss is:
12.500449031591415
The number of items in train is:
13
The loss for epoch 2
0.9615730024301089
The running loss is:
11.595830231904984
The number of items in train is:
13
The loss for epoch 3
0.8919869409157679
The running loss is:
9.472603611648083
The number of items in train is:
13
The loss for epoch 4
0.7286618162806218
The running loss is:
9.583042055368423
The number of items in train is:
13
The loss for epoch 5
0.7371570811821864
The running loss is:
9.448577012866735
The number of items in train is:
13
The loss for epoch 6
0.7268136163743643
The running loss is:
8.934248983860016
The number of items in train is:
13
The loss for epoch 7
0.6872499218353858
The running loss is:
8.718861654400826
The number of items in train is:
13
The loss for epoch 8
0.6706816657231405
The running loss is:
8.367036566138268
The number of items in train is:
13
The loss for epoch 9
0.6436181973952514
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.351791
48 30755 ... 13.041138
49 30756 ... 14.050688
50 30757 ... 14.945793
51 30758 ... 15.019467
52 30759 ... 14.608635
53 30760 ... 13.617412
54 30761 ... 15.745596
55 30762 ... 18.032488
56 30763 ... 19.294676
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f9q3bn5p wandb: Agent Starting Run: mx7h8bz8 with config: batch_size: 3 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: mx7h8bz8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.776539117097855
The number of items in train is:
14
The loss for epoch 0
1.1983242226498467
The running loss is:
26.58887927979231
The number of items in train is:
14
The loss for epoch 1
1.8992056628423077
The running loss is:
24.896283831447363
The number of items in train is:
14
The loss for epoch 2
1.7783059879605259
The running loss is:
17.928823247551918
The number of items in train is:
14
The loss for epoch 3
1.280630231967994
The running loss is:
12.109752431511879
The number of items in train is:
14
The loss for epoch 4
0.8649823165365628
The running loss is:
8.675509860739112
The number of items in train is:
14
The loss for epoch 5
0.6196792757670794
The running loss is:
10.843803316354752
The number of items in train is:
14
The loss for epoch 6
0.7745573797396251
The running loss is:
9.790428780019283
The number of items in train is:
14
The loss for epoch 7
0.6993163414299488
The running loss is:
8.949594028294086
The number of items in train is:
14
The loss for epoch 8
0.6392567163067204
The running loss is:
8.564673632383347
The number of items in train is:
14
The loss for epoch 9
0.6117624023130962
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.665448
48 30755 ... 13.411776
49 30756 ... 13.063972
50 30757 ... 12.983979
51 30758 ... 12.259508
52 30759 ... 11.530276
53 30760 ... 10.420552
54 30761 ... 11.024097
55 30762 ... 12.358281
56 30763 ... 12.445353
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mx7h8bz8 wandb: Agent Starting Run: lm9loxi1 with config: batch_size: 3 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: lm9loxi1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.176710434257984
The number of items in train is:
14
The loss for epoch 0
1.155479316732713
The running loss is:
22.872309029102325
The number of items in train is:
14
The loss for epoch 1
1.6337363592215948
The running loss is:
22.13676345348358
The number of items in train is:
14
The loss for epoch 2
1.5811973895345415
The running loss is:
19.3515884578228
The number of items in train is:
14
The loss for epoch 3
1.3822563184159142
The running loss is:
12.773187398910522
The number of items in train is:
14
The loss for epoch 4
0.9123705284936088
The running loss is:
11.72696629166603
The number of items in train is:
14
The loss for epoch 5
0.8376404494047165
The running loss is:
10.596563547849655
The number of items in train is:
14
The loss for epoch 6
0.7568973962749753
The running loss is:
10.482213720679283
The number of items in train is:
14
The loss for epoch 7
0.7487295514770916
The running loss is:
10.999816179275513
The number of items in train is:
14
The loss for epoch 8
0.7857011556625366
The running loss is:
8.992802858352661
The number of items in train is:
14
The loss for epoch 9
0.6423430613109044
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.652482
48 30755 ... 11.203905
49 30756 ... 9.210129
50 30757 ... 9.121360
51 30758 ... 7.296506
52 30759 ... 5.924037
53 30760 ... 3.844475
54 30761 ... 3.221498
55 30762 ... 6.493601
56 30763 ... 6.209036
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lm9loxi1 wandb: Agent Starting Run: 3mgs8xbf with config: batch_size: 3 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3mgs8xbf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.498512089252472
The number of items in train is:
13
The loss for epoch 0
1.0383470837886517
The running loss is:
25.564792200922966
The number of items in train is:
13
The loss for epoch 1
1.9665224769940743
The running loss is:
22.65778923034668
The number of items in train is:
13
The loss for epoch 2
1.7429068638728216
The running loss is:
14.94919142127037
The number of items in train is:
13
The loss for epoch 3
1.1499378016361823
The running loss is:
13.298549711704254
The number of items in train is:
13
The loss for epoch 4
1.0229653624387889
The running loss is:
10.945579677820206
The number of items in train is:
13
The loss for epoch 5
0.8419676675246313
The running loss is:
10.539850123226643
The number of items in train is:
13
The loss for epoch 6
0.8107577017866648
The running loss is:
10.23940223455429
The number of items in train is:
13
The loss for epoch 7
0.7876463257349454
The running loss is:
9.733535498380661
The number of items in train is:
13
The loss for epoch 8
0.7487334998754355
The running loss is:
8.944746106863022
The number of items in train is:
13
The loss for epoch 9
0.6880573928356171
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.021401
48 30755 ... 11.561892
49 30756 ... 12.308455
50 30757 ... 12.756186
51 30758 ... 12.854743
52 30759 ... 12.682150
53 30760 ... 12.287163
54 30761 ... 13.468019
55 30762 ... 14.454829
56 30763 ... 15.026141
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3mgs8xbf wandb: Agent Starting Run: nihnfer9 with config: batch_size: 3 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: nihnfer9
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.30401501059532
The number of items in train is:
14
The loss for epoch 0
3.6645725007568086
The running loss is:
28.13227316737175
The number of items in train is:
14
The loss for epoch 1
2.0094480833836963
The running loss is:
30.677978098392487
The number of items in train is:
14
The loss for epoch 2
2.1912841498851776
The running loss is:
25.798474550247192
The number of items in train is:
14
The loss for epoch 3
1.8427481821605138
The running loss is:
23.53739532828331
The number of items in train is:
14
The loss for epoch 4
1.6812425234488078
The running loss is:
12.46931640803814
The number of items in train is:
14
The loss for epoch 5
0.89066545771701
The running loss is:
14.836411327123642
The number of items in train is:
14
The loss for epoch 6
1.0597436662231172
The running loss is:
11.940000280737877
The number of items in train is:
14
The loss for epoch 7
0.8528571629098484
The running loss is:
9.431063748896122
The number of items in train is:
14
The loss for epoch 8
0.6736474106354373
The running loss is:
9.614306479692459
The number of items in train is:
14
The loss for epoch 9
0.68673617712089
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.500200
48 30755 ... 13.090182
49 30756 ... 12.382077
50 30757 ... 12.541276
51 30758 ... 11.883831
52 30759 ... 11.478168
53 30760 ... 10.748770
54 30761 ... 11.050783
55 30762 ... 12.022332
56 30763 ... 11.973404
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nihnfer9 wandb: Agent Starting Run: ionv873k with config: batch_size: 3 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ionv873k
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
33.80015930533409
The number of items in train is:
14
The loss for epoch 0
2.4142970932381496
The running loss is:
21.325599938631058
The number of items in train is:
14
The loss for epoch 1
1.523257138473647
The running loss is:
18.091121673583984
The number of items in train is:
14
The loss for epoch 2
1.2922229766845703
The running loss is:
27.904833287000656
The number of items in train is:
14
The loss for epoch 3
1.993202377642904
The running loss is:
19.25467175245285
The number of items in train is:
14
The loss for epoch 4
1.375333696603775
The running loss is:
17.12490466237068
The number of items in train is:
14
The loss for epoch 5
1.2232074758836202
The running loss is:
13.32920789718628
The number of items in train is:
14
The loss for epoch 6
0.9520862783704486
The running loss is:
13.500364929437637
The number of items in train is:
14
The loss for epoch 7
0.9643117806741169
The running loss is:
13.285066820681095
The number of items in train is:
14
The loss for epoch 8
0.9489333443343639
The running loss is:
12.104208245873451
The number of items in train is:
14
The loss for epoch 9
0.8645863032766751
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.968231
48 30755 ... 9.625219
49 30756 ... 9.401051
50 30757 ... 9.150497
51 30758 ... 8.870846
52 30759 ... 8.580363
53 30760 ... 8.285401
54 30761 ... 7.854644
55 30762 ... 9.419525
56 30763 ... 9.371837
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ionv873k wandb: Agent Starting Run: oe5h8j48 with config: batch_size: 3 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: oe5h8j48
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
36.88397306203842
The number of items in train is:
13
The loss for epoch 0
2.837228697079879
The running loss is:
23.387097895145416
The number of items in train is:
13
The loss for epoch 1
1.7990075303958013
The running loss is:
20.17457577586174
The number of items in train is:
13
The loss for epoch 2
1.551890444297057
The running loss is:
20.294566094875336
The number of items in train is:
13
The loss for epoch 3
1.5611204688365643
The running loss is:
18.586155623197556
The number of items in train is:
13
The loss for epoch 4
1.4297042787075043
The running loss is:
13.293670758605003
The number of items in train is:
13
The loss for epoch 5
1.0225900583542311
The running loss is:
13.621711760759354
The number of items in train is:
13
The loss for epoch 6
1.0478239815968733
The running loss is:
10.410593956708908
The number of items in train is:
13
The loss for epoch 7
0.800814919746839
The running loss is:
10.608880147337914
The number of items in train is:
13
The loss for epoch 8
0.8160677036413779
The running loss is:
9.719066202640533
The number of items in train is:
13
The loss for epoch 9
0.7476204771261948
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.146037
48 30755 ... 13.109223
49 30756 ... 13.432909
50 30757 ... 13.972692
51 30758 ... 13.988523
52 30759 ... 13.896473
53 30760 ... 13.568353
54 30761 ... 12.816897
55 30762 ... 14.419169
56 30763 ... 14.700335
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: oe5h8j48 wandb: Agent Starting Run: uz0dql7o with config: batch_size: 3 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: uz0dql7o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.755451019853354
The number of items in train is:
14
The loss for epoch 0
0.7682465014180967
The running loss is:
38.836746633052826
The number of items in train is:
14
The loss for epoch 1
2.7740533309323445
The running loss is:
11.501722127199173
The number of items in train is:
14
The loss for epoch 2
0.8215515805142266
The running loss is:
10.499587520956993
The number of items in train is:
14
The loss for epoch 3
0.7499705372112138
The running loss is:
8.515039145946503
The number of items in train is:
14
The loss for epoch 4
0.6082170818533216
The running loss is:
8.96797063946724
The number of items in train is:
14
The loss for epoch 5
0.6405693313905171
The running loss is:
7.806724339723587
The number of items in train is:
14
The loss for epoch 6
0.5576231671231133
The running loss is:
7.387755490839481
The number of items in train is:
14
The loss for epoch 7
0.5276968207742486
The running loss is:
7.427955038845539
The number of items in train is:
14
The loss for epoch 8
0.5305682170603957
The running loss is:
7.187168009579182
The number of items in train is:
14
The loss for epoch 9
0.5133691435413701
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.769258
48 30755 ... 10.274848
49 30756 ... 17.754297
50 30757 ... 16.682022
51 30758 ... 15.986617
52 30759 ... 15.547783
53 30760 ... 12.919273
54 30761 ... 15.504961
55 30762 ... 17.572283
56 30763 ... 21.066988
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: uz0dql7o wandb: Agent Starting Run: imlwhsva with config: batch_size: 3 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: imlwhsva
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.53025685250759
The number of items in train is:
13
The loss for epoch 0
1.2715582194236608
The running loss is:
16.255148097872734
The number of items in train is:
13
The loss for epoch 1
1.2503960075286717
The running loss is:
10.766040947288275
The number of items in train is:
13
The loss for epoch 2
0.8281569959452519
The running loss is:
9.744163434952497
The number of items in train is:
13
The loss for epoch 3
0.7495510334578844
The running loss is:
9.72730216011405
The number of items in train is:
13
The loss for epoch 4
0.7482540123164654
The running loss is:
9.620016269385815
The number of items in train is:
13
The loss for epoch 5
0.7400012514912165
The running loss is:
9.431224629282951
The number of items in train is:
13
The loss for epoch 6
0.72547881763715
The running loss is:
9.202248107641935
The number of items in train is:
13
The loss for epoch 7
0.7078652390493796
The running loss is:
9.111172825098038
The number of items in train is:
13
The loss for epoch 8
0.7008594480844644
The running loss is:
7.962752666324377
The number of items in train is:
13
The loss for epoch 9
0.6125194358711059
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.158216
48 30755 ... 10.707749
49 30756 ... 15.812157
50 30757 ... 15.918945
51 30758 ... 16.698002
52 30759 ... 17.599003
53 30760 ... 16.707861
54 30761 ... 19.135910
55 30762 ... 21.531374
56 30763 ... 25.614202
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: imlwhsva wandb: Agent Starting Run: 6s6mkjgq with config: batch_size: 3 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 6s6mkjgq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.457125097513199
The number of items in train is:
13
The loss for epoch 0
1.1120865459625537
The running loss is:
16.085287496447563
The number of items in train is:
13
The loss for epoch 1
1.2373298074190433
The running loss is:
10.15951931476593
The number of items in train is:
13
The loss for epoch 2
0.7815014857512254
The running loss is:
9.465455561876297
The number of items in train is:
13
The loss for epoch 3
0.7281119662981766
The running loss is:
9.188641458749771
The number of items in train is:
13
The loss for epoch 4
0.7068185737499824
The running loss is:
8.755524381995201
The number of items in train is:
13
The loss for epoch 5
0.6735018755380924
The running loss is:
8.427750319242477
The number of items in train is:
13
The loss for epoch 6
0.6482884860955752
wandb: Network error resolved after 0:00:11.182615, resuming normal operation.
The running loss is: 7.923837661743164 The number of items in train is: 13 The loss for epoch 7 0.6095259739802434 The running loss is: 8.0590850263834 The number of items in train is: 13 The loss for epoch 8 0.6199296174141077 The running loss is: 8.314335748553276 The number of items in train is: 13 The loss for epoch 9 0.639564288350252 interpolate should be below Now loading and scaling Colorado_Douglas County.csv CSV Path below Colorado_Douglas County.csv torch.Size([1, 3, 3]) Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.424254
48 30755 ... 7.630701
49 30756 ... 9.997432
50 30757 ... 9.401261
51 30758 ... 8.641278
52 30759 ... 7.329124
53 30760 ... 4.651038
54 30761 ... 5.290149
55 30762 ... 4.552412
56 30763 ... 5.032251
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6s6mkjgq wandb: Agent Starting Run: l03hgmub with config: batch_size: 3 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: l03hgmub
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.75971208512783
The number of items in train is:
14
The loss for epoch 0
0.7685508632234165
The running loss is:
36.87247994542122
The number of items in train is:
14
The loss for epoch 1
2.633748567530087
The running loss is:
17.486398860812187
The number of items in train is:
14
The loss for epoch 2
1.2490284900580133
The running loss is:
15.61052069067955
The number of items in train is:
14
The loss for epoch 3
1.1150371921913964
The running loss is:
11.076192826032639
The number of items in train is:
14
The loss for epoch 4
0.7911566304309028
The running loss is:
8.441155915148556
The number of items in train is:
14
The loss for epoch 5
0.6029397082248968
The running loss is:
7.802495114505291
The number of items in train is:
14
The loss for epoch 6
0.5573210796075208
The running loss is:
7.1354983150959015
The number of items in train is:
14
The loss for epoch 7
0.5096784510782787
The running loss is:
7.774059057235718
The number of items in train is:
14
The loss for epoch 8
0.5552899326596942
The running loss is:
6.861661870032549
The number of items in train is:
14
The loss for epoch 9
0.4901187050023249
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.290727
48 30755 ... 10.207885
49 30756 ... 18.020309
50 30757 ... 17.071165
51 30758 ... 16.314606
52 30759 ... 16.627880
53 30760 ... 14.441933
54 30761 ... 18.675493
55 30762 ... 21.162457
56 30763 ... 22.604240
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l03hgmub wandb: Agent Starting Run: c9c5e13j with config: batch_size: 3 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: c9c5e13j
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.687808863818645
The number of items in train is:
13
The loss for epoch 0
0.9759852972168189
The running loss is:
30.817717105150223
The number of items in train is:
13
The loss for epoch 1
2.370593623473094
The running loss is:
15.852080255746841
The number of items in train is:
13
The loss for epoch 2
1.219390788903603
The running loss is:
13.337770016863942
The number of items in train is:
13
The loss for epoch 3
1.025982308989534
The running loss is:
11.452782481908798
The number of items in train is:
13
The loss for epoch 4
0.8809832678391383
The running loss is:
10.242657408118248
The number of items in train is:
13
The loss for epoch 5
0.7878967237014037
The running loss is:
9.236272256821394
The number of items in train is:
13
The loss for epoch 6
0.7104824812939534
The running loss is:
9.14104574918747
The number of items in train is:
13
The loss for epoch 7
0.703157365322113
The running loss is:
8.3548953384161
The number of items in train is:
13
The loss for epoch 8
0.6426842568012384
The running loss is:
8.045029904693365
The number of items in train is:
13
The loss for epoch 9
0.6188484542071819
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.374634
48 30755 ... 8.578894
49 30756 ... 12.920104
50 30757 ... 13.142343
51 30758 ... 13.096810
52 30759 ... 13.633474
53 30760 ... 12.822398
54 30761 ... 13.097551
55 30762 ... 13.966360
56 30763 ... 17.648935
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c9c5e13j wandb: Agent Starting Run: axwlbwqd with config: batch_size: 3 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: axwlbwqd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.29591067135334
The number of items in train is:
13
The loss for epoch 0
0.8689162054887185
The running loss is:
31.16746847331524
The number of items in train is:
13
The loss for epoch 1
2.397497574870403
The running loss is:
13.213620707392693
The number of items in train is:
13
The loss for epoch 2
1.0164323621071303
The running loss is:
12.236616969108582
The number of items in train is:
13
The loss for epoch 3
0.9412782283929678
The running loss is:
10.079297959804535
The number of items in train is:
13
The loss for epoch 4
0.7753306122926565
The running loss is:
9.156161159276962
The number of items in train is:
13
The loss for epoch 5
0.704320089175151
The running loss is:
8.367442056536674
The number of items in train is:
13
The loss for epoch 6
0.6436493889643595
The running loss is:
7.782520815730095
The number of items in train is:
13
The loss for epoch 7
0.5986554473638535
The running loss is:
7.92472417652607
The number of items in train is:
13
The loss for epoch 8
0.6095941674250823
The running loss is:
7.543179780244827
The number of items in train is:
13
The loss for epoch 9
0.5802445984803714
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.698154
48 30755 ... 6.577190
49 30756 ... 7.777941
50 30757 ... 7.032951
51 30758 ... 5.768365
52 30759 ... 3.849137
53 30760 ... 0.948829
54 30761 ... 1.004140
55 30762 ... 0.095635
56 30763 ... -0.856214
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: axwlbwqd wandb: Agent Starting Run: bngef59s with config: batch_size: 3 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bngef59s
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.474827259778976
The number of items in train is:
14
The loss for epoch 0
1.605344804269927
The running loss is:
25.603744968771935
The number of items in train is:
14
The loss for epoch 1
1.8288389263408524
The running loss is:
23.369097493588924
The number of items in train is:
14
The loss for epoch 2
1.669221249542066
The running loss is:
17.44265967607498
The number of items in train is:
14
The loss for epoch 3
1.2459042625767844
The running loss is:
12.164395917207003
The number of items in train is:
14
The loss for epoch 4
0.868885422657643
The running loss is:
12.119173973798752
The number of items in train is:
14
The loss for epoch 5
0.865655283842768
The running loss is:
9.556369185447693
The number of items in train is:
14
The loss for epoch 6
0.6825977989605495
The running loss is:
9.649928107857704
The number of items in train is:
14
The loss for epoch 7
0.6892805791326931
The running loss is:
11.666721649467945
The number of items in train is:
14
The loss for epoch 8
0.8333372606762818
The running loss is:
8.00122594833374
The number of items in train is:
14
The loss for epoch 9
0.5715161391666957
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.312113
48 30755 ... 15.524620
49 30756 ... 21.541870
50 30757 ... 20.370146
51 30758 ... 19.467724
52 30759 ... 19.207888
53 30760 ... 16.430124
54 30761 ... 22.729057
55 30762 ... 23.434126
56 30763 ... 24.633392
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bngef59s wandb: Agent Starting Run: nsmc9ilv with config: batch_size: 3 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: nsmc9ilv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.707977592945099
The number of items in train is:
13
The loss for epoch 0
1.2083059686880846
The running loss is:
19.711661607492715
The number of items in train is:
13
The loss for epoch 1
1.5162816621148243
The running loss is:
20.035046309232712
The number of items in train is:
13
The loss for epoch 2
1.5411574084025164
The running loss is:
15.251697435975075
The number of items in train is:
13
The loss for epoch 3
1.1732074950750058
The running loss is:
11.459911532700062
The number of items in train is:
13
The loss for epoch 4
0.8815316563615432
The running loss is:
9.84505944699049
The number of items in train is:
13
The loss for epoch 5
0.7573122651531146
The running loss is:
9.718630462884903
The number of items in train is:
13
The loss for epoch 6
0.747586958683454
The running loss is:
8.777115888893604
The number of items in train is:
13
The loss for epoch 7
0.6751627606841234
The running loss is:
9.399527624249458
The number of items in train is:
13
The loss for epoch 8
0.7230405864807276
The running loss is:
9.292045809328556
The number of items in train is:
13
The loss for epoch 9
0.7147727545637351
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.226769
48 30755 ... 9.470608
49 30756 ... 9.915501
50 30757 ... 9.908090
51 30758 ... 9.937128
52 30759 ... 10.003601
53 30760 ... 10.060073
54 30761 ... 9.755686
55 30762 ... 9.939466
56 30763 ... 10.018828
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nsmc9ilv wandb: Agent Starting Run: ifw0p83l with config: batch_size: 3 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ifw0p83l
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.531682252883911
The number of items in train is:
13
The loss for epoch 0
0.963975557914147
The running loss is:
20.678108781576157
The number of items in train is:
13
The loss for epoch 1
1.590623752428935
The running loss is:
20.66189543902874
The number of items in train is:
13
The loss for epoch 2
1.58937657223298
The running loss is:
15.72855657339096
The number of items in train is:
13
The loss for epoch 3
1.2098889671839201
The running loss is:
11.498915523290634
The number of items in train is:
13
The loss for epoch 4
0.8845319633300488
The running loss is:
10.46013493835926
The number of items in train is:
13
The loss for epoch 5
0.8046257644891739
The running loss is:
9.681835949420929
The number of items in train is:
13
The loss for epoch 6
0.7447566114939176
The running loss is:
8.949368417263031
The number of items in train is:
13
The loss for epoch 7
0.6884129551740793
The running loss is:
8.690906845033169
The number of items in train is:
13
The loss for epoch 8
0.6685312957717822
The running loss is:
9.19144169986248
The number of items in train is:
13
The loss for epoch 9
0.7070339769124985
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.390057
48 30755 ... 9.157915
49 30756 ... 11.250272
50 30757 ... 11.213902
51 30758 ... 10.737865
52 30759 ... 10.233933
53 30760 ... 9.121439
54 30761 ... 10.235040
55 30762 ... 9.953352
56 30763 ... 10.905466
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ifw0p83l wandb: Agent Starting Run: ipvidfam with config: batch_size: 3 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ipvidfam
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
119.7130461782217
The number of items in train is:
14
The loss for epoch 0
8.55093186987298
The running loss is:
55.55126856267452
The number of items in train is:
14
The loss for epoch 1
3.9679477544767514
The running loss is:
24.79954195022583
The number of items in train is:
14
The loss for epoch 2
1.7713958535875594
The running loss is:
29.550060272216797
The number of items in train is:
14
The loss for epoch 3
2.1107185908726285
The running loss is:
34.141096126288176
The number of items in train is:
14
The loss for epoch 4
2.4386497233062983
The running loss is:
19.86576085537672
The number of items in train is:
14
The loss for epoch 5
1.4189829182411944
The running loss is:
12.140714094042778
The number of items in train is:
14
The loss for epoch 6
0.8671938638601985
The running loss is:
10.807734534144402
The number of items in train is:
14
The loss for epoch 7
0.7719810381531715
The running loss is:
8.74726428091526
The number of items in train is:
14
The loss for epoch 8
0.6248045914939472
The running loss is:
8.744693741202354
The number of items in train is:
14
The loss for epoch 9
0.6246209815144539
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.098480
48 30755 ... 11.234056
49 30756 ... 16.740345
50 30757 ... 15.662832
51 30758 ... 13.948870
52 30759 ... 13.708152
53 30760 ... 11.351399
54 30761 ... 11.689322
55 30762 ... 11.627025
56 30763 ... 16.219433
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ipvidfam wandb: Agent Starting Run: vol92wf7 with config: batch_size: 3 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: vol92wf7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
60.953131318092346
The number of items in train is:
13
The loss for epoch 0
4.688702409084026
The running loss is:
35.30423188209534
The number of items in train is:
13
The loss for epoch 1
2.7157101447765646
The running loss is:
17.126852050423622
The number of items in train is:
13
The loss for epoch 2
1.317450157724894
The running loss is:
29.961639672517776
The number of items in train is:
13
The loss for epoch 3
2.3047415132705984
The running loss is:
28.83660078048706
The number of items in train is:
13
The loss for epoch 4
2.218200060037466
The running loss is:
13.997964818030596
The number of items in train is:
13
The loss for epoch 5
1.076766524463892
The running loss is:
13.703625090420246
The number of items in train is:
13
The loss for epoch 6
1.0541250069554036
The running loss is:
14.603826694190502
The number of items in train is:
13
The loss for epoch 7
1.1233712841685002
The running loss is:
12.683620244264603
The number of items in train is:
13
The loss for epoch 8
0.9756630957126617
The running loss is:
11.017892237752676
The number of items in train is:
13
The loss for epoch 9
0.8475301721348212
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.601355
48 30755 ... 8.784111
49 30756 ... 14.580492
50 30757 ... 13.166733
51 30758 ... 11.297988
52 30759 ... 10.419773
53 30760 ... 8.309337
54 30761 ... 8.855109
55 30762 ... 9.287474
56 30763 ... 13.585121
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vol92wf7 wandb: Agent Starting Run: ui1q5amn with config: batch_size: 3 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ui1q5amn
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
43.07047265768051
The number of items in train is:
13
The loss for epoch 0
3.3131132813600392
The running loss is:
24.968651235103607
The number of items in train is:
13
The loss for epoch 1
1.9206654796233544
The running loss is:
19.673025608062744
The number of items in train is:
13
The loss for epoch 2
1.5133096621586726
The running loss is:
15.400908634066582
The number of items in train is:
13
The loss for epoch 3
1.1846852795435832
The running loss is:
13.345179736614227
The number of items in train is:
13
The loss for epoch 4
1.0265522874318636
The running loss is:
12.23420536518097
The number of items in train is:
13
The loss for epoch 5
0.9410927203985361
The running loss is:
12.980785593390465
The number of items in train is:
13
The loss for epoch 6
0.9985219687223434
The running loss is:
11.168275743722916
The number of items in train is:
13
The loss for epoch 7
0.859098134132532
The running loss is:
10.740023881196976
The number of items in train is:
13
The loss for epoch 8
0.8261556831689981
The running loss is:
10.570404797792435
The number of items in train is:
13
The loss for epoch 9
0.8131080613686488
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.098559
48 30755 ... 10.974888
49 30756 ... 15.032891
50 30757 ... 14.901587
51 30758 ... 13.627957
52 30759 ... 13.362471
53 30760 ... 11.854248
54 30761 ... 13.219946
55 30762 ... 13.206392
56 30763 ... 15.721452
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ui1q5amn wandb: Agent Starting Run: 1godljqj with config: batch_size: 3 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1godljqj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.187944933772087
The number of items in train is:
13
The loss for epoch 0
1.1683034564440067
The running loss is:
12.53387589007616
The number of items in train is:
13
The loss for epoch 1
0.9641442992366277
The running loss is:
8.774933334439993
The number of items in train is:
13
The loss for epoch 2
0.6749948718799994
The running loss is:
7.201144218444824
The number of items in train is:
13
The loss for epoch 3
0.5539341706496018
The running loss is:
7.156394409015775
The number of items in train is:
13
The loss for epoch 4
0.550491877616598
The running loss is:
6.275515090674162
The number of items in train is:
13
The loss for epoch 5
0.4827319300518586
The running loss is:
6.67833286896348
The number of items in train is:
13
The loss for epoch 6
0.5137179129971907
The running loss is:
5.711407098919153
The number of items in train is:
13
The loss for epoch 7
0.4393390076091656
The running loss is:
5.9839532896876335
The number of items in train is:
13
The loss for epoch 8
0.46030409920674104
The running loss is:
6.153777305036783
The number of items in train is:
13
The loss for epoch 9
0.4733674850028295
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.458205
48 30755 ... 7.137259
49 30756 ... 8.528614
50 30757 ... 8.608210
51 30758 ... 8.303369
52 30759 ... 7.806078
53 30760 ... 7.328808
54 30761 ... 5.026564
55 30762 ... 6.488012
56 30763 ... 8.036192
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1godljqj wandb: Agent Starting Run: ptu5e09p with config: batch_size: 3 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ptu5e09p
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.338553577661514
The number of items in train is:
13
The loss for epoch 0
1.3337348905893474
The running loss is:
12.01589360833168
The number of items in train is:
13
The loss for epoch 1
0.9242995083332062
The running loss is:
9.383199691772461
The number of items in train is:
13
The loss for epoch 2
0.7217845916748047
The running loss is:
7.883500777184963
The number of items in train is:
13
The loss for epoch 3
0.6064231367065356
The running loss is:
7.181640453636646
The number of items in train is:
13
The loss for epoch 4
0.5524338810489728
The running loss is:
7.315292157232761
The number of items in train is:
13
The loss for epoch 5
0.562714781325597
The running loss is:
6.892123244702816
The number of items in train is:
13
The loss for epoch 6
0.5301633265156013
The running loss is:
6.666610881686211
The number of items in train is:
13
The loss for epoch 7
0.5128162216681701
The running loss is:
6.246898893266916
The number of items in train is:
13
The loss for epoch 8
0.4805306840974551
The running loss is:
6.445175599306822
The number of items in train is:
13
The loss for epoch 9
0.49578273840821707
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.591523
48 30755 ... 9.032697
49 30756 ... 9.293599
50 30757 ... 9.884513
51 30758 ... 10.124650
52 30759 ... 10.684422
53 30760 ... 11.456519
54 30761 ... 12.109084
55 30762 ... 12.055717
56 30763 ... 12.309025
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ptu5e09p wandb: Agent Starting Run: 1bn7u6ek with config: batch_size: 3 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1bn7u6ek
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.496125161647797
The number of items in train is:
13
The loss for epoch 0
1.2689327047421382
The running loss is:
14.214829742908478
The number of items in train is:
13
The loss for epoch 1
1.0934484417621906
The running loss is:
10.41348597407341
The number of items in train is:
13
The loss for epoch 2
0.8010373826210315
The running loss is:
9.035328388214111
The number of items in train is:
13
The loss for epoch 3
0.6950252606318548
The running loss is:
8.10020449757576
The number of items in train is:
13
The loss for epoch 4
0.6230926536596738
The running loss is:
8.421209901571274
The number of items in train is:
13
The loss for epoch 5
0.6477853770439441
The running loss is:
7.663483992218971
The number of items in train is:
13
The loss for epoch 6
0.5894987686322286
The running loss is:
8.22572796791792
The number of items in train is:
13
The loss for epoch 7
0.6327483052244554
The running loss is:
7.9032817631959915
The number of items in train is:
13
The loss for epoch 8
0.6079447510150763
The running loss is:
7.974031358957291
The number of items in train is:
13
The loss for epoch 9
0.6133870276120993
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.992487
48 30755 ... 12.461034
49 30756 ... 13.230320
50 30757 ... 13.786767
51 30758 ... 14.966878
52 30759 ... 16.526970
53 30760 ... 18.361691
54 30761 ... 18.917545
55 30762 ... 19.258251
56 30763 ... 19.971638
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1bn7u6ek wandb: Agent Starting Run: utturoc5 with config: batch_size: 3 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: utturoc5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.249525194987655
The number of items in train is:
13
The loss for epoch 0
0.8653480919221272
The running loss is:
30.46081379801035
The number of items in train is:
13
The loss for epoch 1
2.343139522923873
The running loss is:
9.777215026319027
The number of items in train is:
13
The loss for epoch 2
0.7520934635630021
The running loss is:
10.099652647972107
The number of items in train is:
13
The loss for epoch 3
0.7768963575363159
The running loss is:
7.714620653539896
The number of items in train is:
13
The loss for epoch 4
0.5934323579646074
The running loss is:
6.230708753690124
The number of items in train is:
13
The loss for epoch 5
0.4792852887453941
The running loss is:
6.548743784427643
The number of items in train is:
13
The loss for epoch 6
0.5037495218790494
The running loss is:
5.332755489274859
The number of items in train is:
13
The loss for epoch 7
0.41021196071345073
The running loss is:
5.4890450509265065
The number of items in train is:
13
The loss for epoch 8
0.42223423468665433
The running loss is:
6.13737740367651
The number of items in train is:
13
The loss for epoch 9
0.4721059541289623
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.758069
48 30755 ... 10.323517
49 30756 ... 11.307789
50 30757 ... 10.594126
51 30758 ... 10.666987
52 30759 ... 11.087155
53 30760 ... 11.666491
54 30761 ... 10.458287
55 30762 ... 12.071755
56 30763 ... 13.168046
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: utturoc5 wandb: Agent Starting Run: nvxoca53 with config: batch_size: 3 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: nvxoca53
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.307263173162937
The number of items in train is:
13
The loss for epoch 0
1.1005587056279182
The running loss is:
26.481370121240616
The number of items in train is:
13
The loss for epoch 1
2.0370284708646627
The running loss is:
10.21297961473465
The number of items in train is:
13
The loss for epoch 2
0.78561381651805
The running loss is:
9.383397921919823
The number of items in train is:
13
The loss for epoch 3
0.7217998401476786
The running loss is:
7.646930389106274
The number of items in train is:
13
The loss for epoch 4
0.5882254145466365
The running loss is:
7.441839635372162
The number of items in train is:
13
The loss for epoch 5
0.5724492027209356
The running loss is:
7.128525517880917
The number of items in train is:
13
The loss for epoch 6
0.5483481167600706
The running loss is:
6.7704630345106125
The number of items in train is:
13
The loss for epoch 7
0.5208048488085086
The running loss is:
6.290463771671057
The number of items in train is:
13
The loss for epoch 8
0.4838818285900813
The running loss is:
6.040915712714195
The number of items in train is:
13
The loss for epoch 9
0.4646858240549381
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.632046
48 30755 ... 10.507959
49 30756 ... 9.999850
50 30757 ... 11.279503
51 30758 ... 11.918778
52 30759 ... 12.729056
53 30760 ... 13.610320
54 30761 ... 15.292119
55 30762 ... 14.556417
56 30763 ... 14.570903
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nvxoca53 wandb: Agent Starting Run: bqts5xmo with config: batch_size: 3 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: bqts5xmo
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.725847855210304
The number of items in train is:
13
The loss for epoch 0
0.9789113734777157
The running loss is:
30.892170883715153
The number of items in train is:
13
The loss for epoch 1
2.376320837208858
The running loss is:
13.146855235099792
The number of items in train is:
13
The loss for epoch 2
1.0112965565461378
The running loss is:
12.148904085159302
The number of items in train is:
13
The loss for epoch 3
0.9345310834737924
The running loss is:
9.722107946872711
The number of items in train is:
13
The loss for epoch 4
0.7478544574517471
The running loss is:
9.249086931347847
The number of items in train is:
13
The loss for epoch 5
0.7114682254882959
The running loss is:
8.29569448530674
The number of items in train is:
13
The loss for epoch 6
0.6381303450235953
The running loss is:
8.795628726482391
The number of items in train is:
13
The loss for epoch 7
0.6765868251140301
The running loss is:
8.55500802397728
The number of items in train is:
13
The loss for epoch 8
0.6580775403059446
The running loss is:
8.533968634903431
The number of items in train is:
13
The loss for epoch 9
0.6564591257618024
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.248339
48 30755 ... 11.703672
49 30756 ... 12.366732
50 30757 ... 12.580591
51 30758 ... 13.153063
52 30759 ... 13.921073
53 30760 ... 14.727524
54 30761 ... 14.668133
55 30762 ... 15.302679
56 30763 ... 15.801561
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bqts5xmo wandb: Agent Starting Run: 97en7jps with config: batch_size: 3 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 97en7jps
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.382418245077133
The number of items in train is:
13
The loss for epoch 0
0.8755706342367026
The running loss is:
23.412592843174934
The number of items in train is:
13
The loss for epoch 1
1.8009686802442257
The running loss is:
17.038911778479815
The number of items in train is:
13
The loss for epoch 2
1.3106855214215243
The running loss is:
10.114607397466898
The number of items in train is:
13
The loss for epoch 3
0.7780467228820691
The running loss is:
9.873054258525372
The number of items in train is:
13
The loss for epoch 4
0.7594657121942594
The running loss is:
6.991059593856335
The number of items in train is:
13
The loss for epoch 5
0.5377738149120257
The running loss is:
7.195119507610798
The number of items in train is:
13
The loss for epoch 6
0.5534707313546767
The running loss is:
8.087266314774752
The number of items in train is:
13
The loss for epoch 7
0.622097408828827
The running loss is:
6.980310961604118
The number of items in train is:
13
The loss for epoch 8
0.5369469970464706
The running loss is:
8.746676992624998
The number of items in train is:
13
The loss for epoch 9
0.6728213071249999
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.572081
48 30755 ... 10.249009
49 30756 ... 9.171862
50 30757 ... 8.501332
51 30758 ... 8.400084
52 30759 ... 8.862746
53 30760 ... 8.692664
54 30761 ... 9.124661
55 30762 ... 9.978867
56 30763 ... 9.774427
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 97en7jps wandb: Agent Starting Run: mqseoc3o with config: batch_size: 3 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: mqseoc3o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.85589762032032
The number of items in train is:
13
The loss for epoch 0
0.9119921246400247
The running loss is:
23.438958287239075
The number of items in train is:
13
The loss for epoch 1
1.8029967913260827
The running loss is:
16.074821338057518
The number of items in train is:
13
The loss for epoch 2
1.2365247183121169
The running loss is:
10.657343104481697
The number of items in train is:
13
The loss for epoch 3
0.819795623421669
The running loss is:
11.378557436168194
The number of items in train is:
13
The loss for epoch 4
0.8752736489360149
The running loss is:
10.08240570127964
The number of items in train is:
13
The loss for epoch 5
0.7755696693292031
The running loss is:
9.281341701745987
The number of items in train is:
13
The loss for epoch 6
0.7139493616727682
The running loss is:
9.217081643640995
The number of items in train is:
13
The loss for epoch 7
0.7090062802800765
The running loss is:
8.837434470653534
The number of items in train is:
13
The loss for epoch 8
0.6798026515887334
The running loss is:
8.208003804087639
The number of items in train is:
13
The loss for epoch 9
0.6313849080067414
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.769919
48 30755 ... 11.215531
49 30756 ... 11.267628
50 30757 ... 12.318272
51 30758 ... 12.608529
52 30759 ... 13.034577
53 30760 ... 13.474689
54 30761 ... 14.320210
55 30762 ... 14.396397
56 30763 ... 14.574674
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mqseoc3o wandb: Agent Starting Run: pfd9jj82 with config: batch_size: 3 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: pfd9jj82
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.825587838888168
The number of items in train is:
13
The loss for epoch 0
0.8327375260683206
The running loss is:
28.150420397520065
The number of items in train is:
13
The loss for epoch 1
2.1654169536553898
The running loss is:
20.6149685382843
The number of items in train is:
13
The loss for epoch 2
1.585766810637254
The running loss is:
11.813875526189804
The number of items in train is:
13
The loss for epoch 3
0.9087596558607541
The running loss is:
12.213937133550644
The number of items in train is:
13
The loss for epoch 4
0.9395336256577418
The running loss is:
11.47781416773796
The number of items in train is:
13
The loss for epoch 5
0.8829087821336893
The running loss is:
10.867890685796738
The number of items in train is:
13
The loss for epoch 6
0.8359915912151337
The running loss is:
10.418911457061768
The number of items in train is:
13
The loss for epoch 7
0.8014547274662898
The running loss is:
9.896387428045273
The number of items in train is:
13
The loss for epoch 8
0.7612605713880979
The running loss is:
9.135141223669052
The number of items in train is:
13
The loss for epoch 9
0.7027031710514655
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 15.415048
48 30755 ... 9.452928
49 30756 ... 10.730062
50 30757 ... 10.066430
51 30758 ... 9.313263
52 30759 ... 9.942549
53 30760 ... 10.416265
54 30761 ... 6.991664
55 30762 ... 10.831858
56 30763 ... 9.746800
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pfd9jj82 wandb: Agent Starting Run: vz7xqs63 with config: batch_size: 3 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: vz7xqs63
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
46.30128153041005
The number of items in train is:
13
The loss for epoch 0
3.561637040800773
The running loss is:
24.802572248037905
The number of items in train is:
13
The loss for epoch 1
1.9078901729259927
The running loss is:
13.231589883565903
The number of items in train is:
13
The loss for epoch 2
1.0178146064281464
The running loss is:
7.9983332976698875
The number of items in train is:
13
The loss for epoch 3
0.6152564075130683
The running loss is:
10.238236993551254
The number of items in train is:
13
The loss for epoch 4
0.7875566918116349
The running loss is:
9.1368916220963
The number of items in train is:
13
The loss for epoch 5
0.7028378170843308
The running loss is:
8.546009212732315
The number of items in train is:
13
The loss for epoch 6
0.6573853240563319
The running loss is:
8.557626497000456
The number of items in train is:
13
The loss for epoch 7
0.6582789613077273
The running loss is:
8.405014142394066
The number of items in train is:
13
The loss for epoch 8
0.6465395494149282
The running loss is:
8.690803073346615
The number of items in train is:
13
The loss for epoch 9
0.668523313334355
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.108495
48 30755 ... 10.607700
49 30756 ... 10.552139
50 30757 ... 11.810363
51 30758 ... 11.965808
52 30759 ... 11.572226
53 30760 ... 11.432143
54 30761 ... 11.407201
55 30762 ... 11.625036
56 30763 ... 11.583269
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vz7xqs63 wandb: Agent Starting Run: vat0wthg with config: batch_size: 3 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: vat0wthg
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
38.69787164032459
The number of items in train is:
13
The loss for epoch 0
2.9767593569480457
The running loss is:
20.345289036631584
The number of items in train is:
13
The loss for epoch 1
1.565022233587045
The running loss is:
14.763616390526295
The number of items in train is:
13
The loss for epoch 2
1.1356627992712534
The running loss is:
10.519289702177048
The number of items in train is:
13
The loss for epoch 3
0.8091761309366959
The running loss is:
12.006632789969444
The number of items in train is:
13
The loss for epoch 4
0.9235871376899573
The running loss is:
10.068530097603798
The number of items in train is:
13
The loss for epoch 5
0.7745023152002921
The running loss is:
10.892198204994202
The number of items in train is:
13
The loss for epoch 6
0.8378614003841693
The running loss is:
9.449286311864853
The number of items in train is:
13
The loss for epoch 7
0.726868177835758
The running loss is:
8.240423366427422
The number of items in train is:
13
The loss for epoch 8
0.6338787204944171
The running loss is:
8.944622784852982
The number of items in train is:
13
The loss for epoch 9
0.6880479065271524
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.047753
48 30755 ... 11.163092
49 30756 ... 11.282596
50 30757 ... 12.519486
51 30758 ... 13.338696
52 30759 ... 14.516523
53 30760 ... 15.342272
54 30761 ... 15.626085
55 30762 ... 15.729576
56 30763 ... 15.897081
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vat0wthg wandb: Agent Starting Run: 7ympyi75 with config: batch_size: 3 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 7ympyi75
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
42.751119792461395
The number of items in train is:
13
The loss for epoch 0
3.2885476763431845
The running loss is:
22.814359664916992
The number of items in train is:
13
The loss for epoch 1
1.7549507434551532
The running loss is:
17.861228555440903
The number of items in train is:
13
The loss for epoch 2
1.3739406581108387
The running loss is:
13.160692304372787
The number of items in train is:
13
The loss for epoch 3
1.0123609464902144
The running loss is:
12.061859995126724
The number of items in train is:
13
The loss for epoch 4
0.9278353842405173
The running loss is:
11.913350507616997
The number of items in train is:
13
The loss for epoch 5
0.9164115775089997
The running loss is:
10.849895969033241
The number of items in train is:
13
The loss for epoch 6
0.8346073822333262
The running loss is:
11.268224865198135
The number of items in train is:
13
The loss for epoch 7
0.8667865280921643
The running loss is:
10.611917436122894
The number of items in train is:
13
The loss for epoch 8
0.8163013412402227
The running loss is:
9.465873330831528
The number of items in train is:
13
The loss for epoch 9
0.7281441023716559
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.687474
48 30755 ... 8.196827
49 30756 ... 8.605579
50 30757 ... 8.132575
51 30758 ... 7.834826
52 30759 ... 7.821600
53 30760 ... 8.354590
54 30761 ... 8.151829
55 30762 ... 8.153378
56 30763 ... 8.345223
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7ympyi75 wandb: Agent Starting Run: wlmcvsr7 with config: batch_size: 3 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: wlmcvsr7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.07284878194332
The number of items in train is:
13
The loss for epoch 0
1.2363729832264094
The running loss is:
11.393546909093857
The number of items in train is:
13
The loss for epoch 1
0.8764266853149121
The running loss is:
9.211045920848846
The number of items in train is:
13
The loss for epoch 2
0.7085419939114497
The running loss is:
8.046417102217674
The number of items in train is:
13
The loss for epoch 3
0.6189551617090518
The running loss is:
8.130555003881454
The number of items in train is:
13
The loss for epoch 4
0.6254273079908811
The running loss is:
7.790109492838383
The number of items in train is:
13
The loss for epoch 5
0.5992391917567986
The running loss is:
7.453979782760143
The number of items in train is:
13
The loss for epoch 6
0.5733830602123187
The running loss is:
7.104567661881447
The number of items in train is:
13
The loss for epoch 7
0.5465052047601113
The running loss is:
6.915351435542107
The number of items in train is:
13
The loss for epoch 8
0.5319501104263159
The running loss is:
7.459764987230301
The number of items in train is:
13
The loss for epoch 9
0.5738280759407923
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.308602
48 30755 ... 8.039572
49 30756 ... 8.126947
50 30757 ... 8.647640
51 30758 ... 8.920097
52 30759 ... 8.672168
53 30760 ... 8.654925
54 30761 ... 8.377190
55 30762 ... 7.938785
56 30763 ... 8.490222
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wlmcvsr7 wandb: Agent Starting Run: 4usoutte with config: batch_size: 3 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4usoutte
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.015090629458427
The number of items in train is:
13
The loss for epoch 0
1.308853125342956
The running loss is:
14.904403626918793
The number of items in train is:
13
The loss for epoch 1
1.146492586686061
The running loss is:
9.877731040120125
The number of items in train is:
13
The loss for epoch 2
0.759825464624625
The running loss is:
8.914640828967094
The number of items in train is:
13
The loss for epoch 3
0.685741602228238
The running loss is:
8.24161709845066
The number of items in train is:
13
The loss for epoch 4
0.6339705460346662
The running loss is:
7.48406345397234
The number of items in train is:
13
The loss for epoch 5
0.5756971887671031
The running loss is:
7.502739422023296
The number of items in train is:
13
The loss for epoch 6
0.5771338016940997
The running loss is:
7.524602979421616
The number of items in train is:
13
The loss for epoch 7
0.5788156138016627
The running loss is:
7.4196352288126945
The number of items in train is:
13
The loss for epoch 8
0.5707411714471303
The running loss is:
8.976969480514526
The number of items in train is:
13
The loss for epoch 9
0.6905361138857328
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.343148
48 30755 ... 7.248403
49 30756 ... 6.399437
50 30757 ... 6.592106
51 30758 ... 4.307819
52 30759 ... 3.254845
53 30760 ... 2.614995
54 30761 ... 2.333879
55 30762 ... 1.141000
56 30763 ... 0.928883
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4usoutte wandb: Agent Starting Run: qnbzxb65 with config: batch_size: 3 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qnbzxb65
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.061375049874187
The number of items in train is:
12
The loss for epoch 0
1.3384479208228488
The running loss is:
11.802918165922165
The number of items in train is:
12
The loss for epoch 1
0.9835765138268471
The running loss is:
9.635548263788223
The number of items in train is:
12
The loss for epoch 2
0.8029623553156853
The running loss is:
7.900071606040001
The number of items in train is:
12
The loss for epoch 3
0.6583393005033334
The running loss is:
7.308927018195391
The number of items in train is:
12
The loss for epoch 4
0.6090772515162826
The running loss is:
7.408294729888439
The number of items in train is:
12
The loss for epoch 5
0.61735789415737
The running loss is:
7.30912384018302
The number of items in train is:
12
The loss for epoch 6
0.609093653348585
The running loss is:
8.098075211048126
The number of items in train is:
12
The loss for epoch 7
0.6748396009206772
The running loss is:
8.676205836236477
The number of items in train is:
12
The loss for epoch 8
0.7230171530197064
The running loss is:
8.98013935610652
The number of items in train is:
12
The loss for epoch 9
0.7483449463422099
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.317636
48 30755 ... 8.713526
49 30756 ... 7.261724
50 30757 ... 7.391668
51 30758 ... 6.424718
52 30759 ... 6.508060
53 30760 ... 6.848399
54 30761 ... 6.814502
55 30762 ... 6.458637
56 30763 ... 6.546707
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qnbzxb65 wandb: Agent Starting Run: 6u98nj7v with config: batch_size: 3 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 6u98nj7v
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.765893511474133
The number of items in train is:
13
The loss for epoch 0
1.0589148854980102
The running loss is:
23.43887052498758
The number of items in train is:
13
The loss for epoch 1
1.8029900403836598
The running loss is:
10.36953791975975
The number of items in train is:
13
The loss for epoch 2
0.7976567630584424
The running loss is:
8.904323771595955
The number of items in train is:
13
The loss for epoch 3
0.6849479824304581
The running loss is:
7.417386781424284
The number of items in train is:
13
The loss for epoch 4
0.5705682139557141
The running loss is:
7.913604368921369
The number of items in train is:
13
The loss for epoch 5
0.6087387976093361
The running loss is:
6.859258336946368
The number of items in train is:
13
The loss for epoch 6
0.5276352566881821
The running loss is:
6.282172272214666
The number of items in train is:
13
The loss for epoch 7
0.4832440209395897
The running loss is:
6.116885121911764
The number of items in train is:
13
The loss for epoch 8
0.4705296247624434
The running loss is:
7.14730378985405
The number of items in train is:
13
The loss for epoch 9
0.5497925992195423
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.736671
48 30755 ... 11.564378
49 30756 ... 9.607123
50 30757 ... 10.786201
51 30758 ... 10.428370
52 30759 ... 11.004709
53 30760 ... 11.867481
54 30761 ... 11.287722
55 30762 ... 10.306524
56 30763 ... 11.843080
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6u98nj7v wandb: Agent Starting Run: x8y2ap84 with config: batch_size: 3 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: x8y2ap84
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.553385689854622
The number of items in train is:
13
The loss for epoch 0
0.9656450530657401
The running loss is:
32.152095057070255
The number of items in train is:
13
The loss for epoch 1
2.4732380813130965
The running loss is:
13.22272926568985
The number of items in train is:
13
The loss for epoch 2
1.0171330204376807
The running loss is:
12.398492097854614
The number of items in train is:
13
The loss for epoch 3
0.9537301613734319
The running loss is:
9.956698954105377
The number of items in train is:
13
The loss for epoch 4
0.7658999195465674
The running loss is:
8.292960315942764
The number of items in train is:
13
The loss for epoch 5
0.6379200243032895
The running loss is:
7.7905485183000565
The number of items in train is:
13
The loss for epoch 6
0.5992729629461582
The running loss is:
7.017962105572224
The number of items in train is:
13
The loss for epoch 7
0.539843238890171
The running loss is:
7.154788330197334
The number of items in train is:
13
The loss for epoch 8
0.5503683330921026
The running loss is:
6.995831839740276
The number of items in train is:
13
The loss for epoch 9
0.5381409107492521
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.034538
48 30755 ... 3.927094
49 30756 ... 3.308820
50 30757 ... 3.999937
51 30758 ... 1.726190
52 30759 ... 0.882484
53 30760 ... 0.202644
54 30761 ... -2.367896
55 30762 ... -4.971350
56 30763 ... -3.257763
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: x8y2ap84 wandb: Agent Starting Run: f4nlybf9 with config: batch_size: 3 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: f4nlybf9
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.682664819061756
The number of items in train is:
12
The loss for epoch 0
1.056888734921813
The running loss is:
26.245943874120712
The number of items in train is:
12
The loss for epoch 1
2.1871619895100594
The running loss is:
10.745129108428955
The number of items in train is:
12
The loss for epoch 2
0.895427425702413
The running loss is:
10.478202775120735
The number of items in train is:
12
The loss for epoch 3
0.8731835645933946
The running loss is:
8.926227048039436
The number of items in train is:
12
The loss for epoch 4
0.7438522540032864
The running loss is:
7.637079827487469
The number of items in train is:
12
The loss for epoch 5
0.6364233189572891
The running loss is:
7.005005210638046
The number of items in train is:
12
The loss for epoch 6
0.5837504342198372
The running loss is:
6.797870747745037
The number of items in train is:
12
The loss for epoch 7
0.5664892289787531
The running loss is:
7.502613537013531
The number of items in train is:
12
The loss for epoch 8
0.6252177947511276
The running loss is:
7.621904402971268
The number of items in train is:
12
The loss for epoch 9
0.6351587002476057
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.770882
48 30755 ... 8.434825
49 30756 ... 5.860340
50 30757 ... 6.031592
51 30758 ... 3.103240
52 30759 ... 1.140361
53 30760 ... -0.055734
54 30761 ... -0.050757
55 30762 ... -0.057389
56 30763 ... -0.524463
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f4nlybf9 wandb: Agent Starting Run: bxrcu8tu with config: batch_size: 3 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bxrcu8tu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.525801971554756
The number of items in train is:
13
The loss for epoch 0
0.963523228581135
The running loss is:
23.895836547017097
The number of items in train is:
13
The loss for epoch 1
1.838141272847469
The running loss is:
14.084609515964985
The number of items in train is:
13
The loss for epoch 2
1.0834315012280757
The running loss is:
10.381171528249979
The number of items in train is:
13
The loss for epoch 3
0.7985516560192292
The running loss is:
10.052995964884758
The number of items in train is:
13
The loss for epoch 4
0.7733073819142121
The running loss is:
10.303962796926498
The number of items in train is:
13
The loss for epoch 5
0.7926125228404999
The running loss is:
8.726175464689732
The number of items in train is:
13
The loss for epoch 6
0.6712442665145948
The running loss is:
9.212526094168425
The number of items in train is:
13
The loss for epoch 7
0.7086558533975711
The running loss is:
10.139194697141647
The number of items in train is:
13
The loss for epoch 8
0.7799380536262805
The running loss is:
10.184998378157616
The number of items in train is:
13
The loss for epoch 9
0.783461413704432
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.354187
48 30755 ... 13.430566
49 30756 ... 10.369150
50 30757 ... 10.154779
51 30758 ... 10.079480
52 30759 ... 10.377722
53 30760 ... 11.070954
54 30761 ... 9.903352
55 30762 ... 9.985621
56 30763 ... 9.941944
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bxrcu8tu wandb: Agent Starting Run: je2yahnk with config: batch_size: 3 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: je2yahnk
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.798818975687027
The number of items in train is:
13
The loss for epoch 0
0.8306783827451559
The running loss is:
28.490219056606293
The number of items in train is:
13
The loss for epoch 1
2.191555312046638
The running loss is:
19.000672325491905
The number of items in train is:
13
The loss for epoch 2
1.4615901788839927
The running loss is:
12.530485570430756
The number of items in train is:
13
The loss for epoch 3
0.9638835054177505
The running loss is:
11.969089105725288
The number of items in train is:
13
The loss for epoch 4
0.9206991619788684
The running loss is:
10.927263751626015
The number of items in train is:
13
The loss for epoch 5
0.8405587501250781
The running loss is:
10.749707907438278
The number of items in train is:
13
The loss for epoch 6
0.826900608264483
The running loss is:
8.986315917223692
The number of items in train is:
13
The loss for epoch 7
0.6912550705556686
The running loss is:
7.793350949883461
The number of items in train is:
13
The loss for epoch 8
0.59948853460642
The running loss is:
7.86865272372961
The number of items in train is:
13
The loss for epoch 9
0.6052809787484316
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.091916
48 30755 ... 11.852512
49 30756 ... 10.316889
50 30757 ... 11.192894
51 30758 ... 12.840643
52 30759 ... 13.993360
53 30760 ... 15.278111
54 30761 ... 12.534163
55 30762 ... 9.271551
56 30763 ... 11.861491
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: je2yahnk wandb: Agent Starting Run: pv154y7u with config: batch_size: 3 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: pv154y7u
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.802732415497303
The number of items in train is:
12
The loss for epoch 0
0.8168943679581085
The running loss is:
26.21215522289276
The number of items in train is:
12
The loss for epoch 1
2.1843462685743966
The running loss is:
17.116993874311447
The number of items in train is:
12
The loss for epoch 2
1.4264161561926205
The running loss is:
10.959399312734604
The number of items in train is:
12
The loss for epoch 3
0.913283276061217
The running loss is:
10.964498907327652
The number of items in train is:
12
The loss for epoch 4
0.9137082422773043
The running loss is:
9.913394719362259
The number of items in train is:
12
The loss for epoch 5
0.8261162266135216
The running loss is:
8.57229234278202
The number of items in train is:
12
The loss for epoch 6
0.714357695231835
The running loss is:
7.871752962470055
The number of items in train is:
12
The loss for epoch 7
0.6559794135391712
The running loss is:
7.458349071443081
The number of items in train is:
12
The loss for epoch 8
0.6215290892869234
The running loss is:
8.988392800092697
The number of items in train is:
12
The loss for epoch 9
0.7490327333410581
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.390130
48 30755 ... 11.972624
49 30756 ... 8.251997
50 30757 ... 8.524872
51 30758 ... 7.873636
52 30759 ... 6.769165
53 30760 ... 5.787257
54 30761 ... 4.192029
55 30762 ... 2.647506
56 30763 ... 3.688875
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pv154y7u wandb: Agent Starting Run: tfairxgi with config: batch_size: 3 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: tfairxgi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
37.44812400639057
The number of items in train is:
13
The loss for epoch 0
2.8806249235685053
The running loss is:
22.365391314029694
The number of items in train is:
13
The loss for epoch 1
1.7204147164638226
The running loss is:
14.247072592377663
The number of items in train is:
13
The loss for epoch 2
1.095928660952128
The running loss is:
12.75909799337387
The number of items in train is:
13
The loss for epoch 3
0.9814690764133747
The running loss is:
17.026127204298973
The number of items in train is:
13
The loss for epoch 4
1.3097020926383824
The running loss is:
12.31944526731968
The number of items in train is:
13
The loss for epoch 5
0.9476496359476676
The running loss is:
13.54552149027586
The number of items in train is:
13
The loss for epoch 6
1.0419631915596814
The running loss is:
12.44608373939991
The number of items in train is:
13
The loss for epoch 7
0.9573910568769162
The running loss is:
10.811461791396141
The number of items in train is:
13
The loss for epoch 8
0.8316509070304724
The running loss is:
13.428137093782425
The number of items in train is:
13
The loss for epoch 9
1.032933622598648
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.360991
48 30755 ... 12.424065
49 30756 ... 12.174776
50 30757 ... 11.980565
51 30758 ... 11.824924
52 30759 ... 12.332734
53 30760 ... 12.714437
54 30761 ... 13.116733
55 30762 ... 13.821445
56 30763 ... 13.117739
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tfairxgi wandb: Agent Starting Run: qaitrbya with config: batch_size: 3 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: qaitrbya
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
49.11082097887993
The number of items in train is:
13
The loss for epoch 0
3.7777554599138408
The running loss is:
25.69899582862854
The number of items in train is:
13
The loss for epoch 1
1.9768458329714262
The running loss is:
17.135295033454895
The number of items in train is:
13
The loss for epoch 2
1.3180996179580688
The running loss is:
11.379485577344894
The number of items in train is:
13
The loss for epoch 3
0.8753450444111457
The running loss is:
11.188541859388351
The number of items in train is:
13
The loss for epoch 4
0.8606570661067963
The running loss is:
11.069215461611748
The number of items in train is:
13
The loss for epoch 5
0.8514781124316729
The running loss is:
10.00205671787262
The number of items in train is:
13
The loss for epoch 6
0.7693889782978938
The running loss is:
10.64719857275486
The number of items in train is:
13
The loss for epoch 7
0.819015274827297
The running loss is:
10.02389670908451
The number of items in train is:
13
The loss for epoch 8
0.7710689776218854
The running loss is:
9.106609582901001
The number of items in train is:
13
The loss for epoch 9
0.7005084294539231
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.008989
48 30755 ... 9.304375
49 30756 ... 6.913957
50 30757 ... 6.941987
51 30758 ... 6.408734
52 30759 ... 5.711936
53 30760 ... 5.180847
54 30761 ... 4.393548
55 30762 ... 4.547277
56 30763 ... 4.002431
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qaitrbya wandb: Agent Starting Run: iouf2wvs with config: batch_size: 3 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: iouf2wvs
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
39.271602153778076
The number of items in train is:
12
The loss for epoch 0
3.27263351281484
The running loss is:
20.22679728269577
The number of items in train is:
12
The loss for epoch 1
1.6855664402246475
The running loss is:
12.615855321288109
The number of items in train is:
12
The loss for epoch 2
1.051321276774009
The running loss is:
11.286904752254486
The number of items in train is:
12
The loss for epoch 3
0.9405753960212072
The running loss is:
10.426268815994263
The number of items in train is:
12
The loss for epoch 4
0.8688557346661886
The running loss is:
10.909985393285751
The number of items in train is:
12
The loss for epoch 5
0.9091654494404793
The running loss is:
9.572229564189911
The number of items in train is:
12
The loss for epoch 6
0.7976857970158259
The running loss is:
10.429155349731445
The number of items in train is:
12
The loss for epoch 7
0.8690962791442871
The running loss is:
8.921477675437927
The number of items in train is:
12
The loss for epoch 8
0.7434564729531606
The running loss is:
10.159409493207932
The number of items in train is:
12
The loss for epoch 9
0.8466174577673277
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.940737
48 30755 ... 8.700059
49 30756 ... 7.716850
50 30757 ... 7.790635
51 30758 ... 7.375722
52 30759 ... 7.020612
53 30760 ... 7.071692
54 30761 ... 7.064066
55 30762 ... 7.515588
56 30763 ... 7.197381
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: iouf2wvs wandb: Agent Starting Run: hissdac6 with config: batch_size: 3 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: hissdac6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.642247676849365
The number of items in train is:
13
The loss for epoch 0
1.280172898219182
The running loss is:
16.28763623908162
The number of items in train is:
13
The loss for epoch 1
1.2528950953139708
The running loss is:
9.172755971550941
The number of items in train is:
13
The loss for epoch 2
0.7055966131962262
The running loss is:
7.831138916313648
The number of items in train is:
13
The loss for epoch 3
0.602395301254896
The running loss is:
7.456290934234858
The number of items in train is:
13
The loss for epoch 4
0.5735608410949891
The running loss is:
7.011703036725521
The number of items in train is:
13
The loss for epoch 5
0.5393617720558093
The running loss is:
6.7462056539952755
The number of items in train is:
13
The loss for epoch 6
0.5189388964611751
The running loss is:
6.409943629056215
The number of items in train is:
13
The loss for epoch 7
0.4930725868504781
The running loss is:
6.455305725336075
The number of items in train is:
13
The loss for epoch 8
0.49656197887200576
The running loss is:
5.876091826707125
The number of items in train is:
13
The loss for epoch 9
0.45200706359285575
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.442939
48 30755 ... 14.496378
49 30756 ... 20.103035
50 30757 ... 14.229822
51 30758 ... 14.765225
52 30759 ... 15.657488
53 30760 ... 19.752836
54 30761 ... 19.353802
55 30762 ... 20.783958
56 30763 ... 22.710882
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hissdac6 wandb: Agent Starting Run: sq780sr1 with config: batch_size: 3 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sq780sr1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.69208151102066
The number of items in train is:
12
The loss for epoch 0
1.2243401259183884
The running loss is:
13.725030314177275
The number of items in train is:
12
The loss for epoch 1
1.1437525261814396
The running loss is:
8.605534479022026
The number of items in train is:
12
The loss for epoch 2
0.7171278732518355
The running loss is:
7.257033374160528
The number of items in train is:
12
The loss for epoch 3
0.604752781180044
The running loss is:
6.742498558014631
The number of items in train is:
12
The loss for epoch 4
0.5618748798345526
The running loss is:
6.170779198408127
The number of items in train is:
12
The loss for epoch 5
0.5142315998673439
The running loss is:
5.943502962589264
The number of items in train is:
12
The loss for epoch 6
0.49529191354910534
The running loss is:
6.512494046241045
The number of items in train is:
12
The loss for epoch 7
0.5427078371867537
The running loss is:
5.600046152248979
The number of items in train is:
12
The loss for epoch 8
0.4666705126874149
The running loss is:
6.0191479958593845
The number of items in train is:
12
The loss for epoch 9
0.5015956663216153
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.703872
48 30755 ... 10.141007
49 30756 ... 11.051534
50 30757 ... 5.682369
51 30758 ... 5.453309
52 30759 ... 3.219275
53 30760 ... 1.562811
54 30761 ... 1.084062
55 30762 ... 0.619162
56 30763 ... -0.067193
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sq780sr1 wandb: Agent Starting Run: 3lkpbgj0 with config: batch_size: 3 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3lkpbgj0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.149451583623886
The number of items in train is:
12
The loss for epoch 0
1.2624542986353238
The running loss is:
12.484605565667152
The number of items in train is:
12
The loss for epoch 1
1.0403837971389294
The running loss is:
9.57485019415617
The number of items in train is:
12
The loss for epoch 2
0.7979041828463475
The running loss is:
8.463449150323868
The number of items in train is:
12
The loss for epoch 3
0.7052874291936556
The running loss is:
7.940030604600906
The number of items in train is:
12
The loss for epoch 4
0.6616692170500755
The running loss is:
7.351875007152557
The number of items in train is:
12
The loss for epoch 5
0.6126562505960464
The running loss is:
7.489130318164825
The number of items in train is:
12
The loss for epoch 6
0.6240941931804022
The running loss is:
6.787940315902233
The number of items in train is:
12
The loss for epoch 7
0.5656616929918528
The running loss is:
7.015684597194195
The number of items in train is:
12
The loss for epoch 8
0.5846403830995163
The running loss is:
6.8622966930270195
The number of items in train is:
12
The loss for epoch 9
0.5718580577522516
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.617135
48 30755 ... 8.451162
49 30756 ... 10.490123
50 30757 ... 3.936914
51 30758 ... 2.963327
52 30759 ... -1.098660
53 30760 ... -4.159821
54 30761 ... -6.189400
55 30762 ... -6.795932
56 30763 ... -6.658059
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3lkpbgj0 wandb: Agent Starting Run: 5v3ml29k with config: batch_size: 3 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5v3ml29k
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.161938413977623
The number of items in train is:
13
The loss for epoch 0
0.9355337241521249
The running loss is:
28.572343215346336
The number of items in train is:
13
The loss for epoch 1
2.1978725550266414
The running loss is:
12.400501441210508
The number of items in train is:
13
The loss for epoch 2
0.9538847262469622
The running loss is:
9.189391441643238
The number of items in train is:
13
The loss for epoch 3
0.7068762647417876
The running loss is:
7.397752322256565
The number of items in train is:
13
The loss for epoch 4
0.5690578709428127
The running loss is:
6.42874202132225
The number of items in train is:
13
The loss for epoch 5
0.4945186170247885
The running loss is:
6.827842012047768
The number of items in train is:
13
The loss for epoch 6
0.5252186163113668
The running loss is:
6.1493959575891495
The number of items in train is:
13
The loss for epoch 7
0.4730304582760884
The running loss is:
6.439127545803785
The number of items in train is:
13
The loss for epoch 8
0.4953175035233681
The running loss is:
8.07044368237257
The number of items in train is:
13
The loss for epoch 9
0.6208033601825054
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 4.922472
48 30755 ... 8.917814
49 30756 ... 18.689007
50 30757 ... 13.947339
51 30758 ... 11.741467
52 30759 ... 10.111837
53 30760 ... 11.390107
54 30761 ... 8.920159
55 30762 ... 10.996446
56 30763 ... 16.557650
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5v3ml29k wandb: Agent Starting Run: unibab00 with config: batch_size: 3 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: unibab00
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.454828664660454
The number of items in train is:
12
The loss for epoch 0
0.8712357220550379
The running loss is:
29.681454718112946
The number of items in train is:
12
The loss for epoch 1
2.4734545598427453
The running loss is:
10.859991066157818
The number of items in train is:
12
The loss for epoch 2
0.9049992555131515
The running loss is:
10.422705300152302
The number of items in train is:
12
The loss for epoch 3
0.8685587750126919
The running loss is:
8.322179265320301
The number of items in train is:
12
The loss for epoch 4
0.6935149387766918
The running loss is:
7.16530604660511
The number of items in train is:
12
The loss for epoch 5
0.5971088372170925
The running loss is:
6.654772460460663
The number of items in train is:
12
The loss for epoch 6
0.5545643717050552
The running loss is:
6.77964261546731
The number of items in train is:
12
The loss for epoch 7
0.5649702179556092
The running loss is:
6.088913932442665
The number of items in train is:
12
The loss for epoch 8
0.5074094943702221
The running loss is:
6.501669891178608
The number of items in train is:
12
The loss for epoch 9
0.541805824264884
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.519657
48 30755 ... 11.527104
49 30756 ... 14.025534
50 30757 ... 9.028507
51 30758 ... 9.338325
52 30759 ... 9.590857
53 30760 ... 10.613542
54 30761 ... 10.388042
55 30762 ... 10.484270
56 30763 ... 10.389216
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: unibab00 wandb: Agent Starting Run: ifp9eb1p with config: batch_size: 3 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ifp9eb1p
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.416129767894745
The number of items in train is:
12
The loss for epoch 0
1.0346774806578953
The running loss is:
24.20527493953705
The number of items in train is:
12
The loss for epoch 1
2.0171062449614205
The running loss is:
11.19543930888176
The number of items in train is:
12
The loss for epoch 2
0.9329532757401466
The running loss is:
10.788735710084438
The number of items in train is:
12
The loss for epoch 3
0.8990613091737032
The running loss is:
9.559967994689941
The number of items in train is:
12
The loss for epoch 4
0.7966639995574951
The running loss is:
8.618342891335487
The number of items in train is:
12
The loss for epoch 5
0.718195240944624
The running loss is:
7.969642907381058
The number of items in train is:
12
The loss for epoch 6
0.6641369089484215
The running loss is:
7.33133128285408
The number of items in train is:
12
The loss for epoch 7
0.6109442735711733
The running loss is:
6.842497617006302
The number of items in train is:
12
The loss for epoch 8
0.5702081347505251
The running loss is:
6.608101170510054
The number of items in train is:
12
The loss for epoch 9
0.5506750975425044
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.705063
48 30755 ... 9.075434
49 30756 ... 11.673032
50 30757 ... 6.914804
51 30758 ... 6.505346
52 30759 ... 4.965737
53 30760 ... 4.142810
54 30761 ... 3.150626
55 30762 ... 3.350169
56 30763 ... 4.398151
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ifp9eb1p wandb: Agent Starting Run: thts7qrs with config: batch_size: 3 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: thts7qrs
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.258691161870956
The number of items in train is:
13
The loss for epoch 0
1.0198993201439197
The running loss is:
23.489024937152863
The number of items in train is:
13
The loss for epoch 1
1.8068480720886817
The running loss is:
18.21075715869665
The number of items in train is:
13
The loss for epoch 2
1.4008274737458963
The running loss is:
10.906683094799519
The number of items in train is:
13
The loss for epoch 3
0.8389756226768861
The running loss is:
8.148265436291695
The number of items in train is:
13
The loss for epoch 4
0.6267896489455149
The running loss is:
7.965685077011585
The number of items in train is:
13
The loss for epoch 5
0.6127450059239681
The running loss is:
8.664709061384201
The number of items in train is:
13
The loss for epoch 6
0.6665160816449386
The running loss is:
7.032974503934383
The number of items in train is:
13
The loss for epoch 7
0.5409980387641833
The running loss is:
6.97207360714674
The number of items in train is:
13
The loss for epoch 8
0.5363133543959031
The running loss is:
7.017210938036442
The number of items in train is:
13
The loss for epoch 9
0.5397854567720339
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.510240
48 30755 ... 16.805296
49 30756 ... 21.841839
50 30757 ... 16.963865
51 30758 ... 17.538879
52 30759 ... 19.097288
53 30760 ... 21.089573
54 30761 ... 22.992525
55 30762 ... 22.120745
56 30763 ... 20.562706
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: thts7qrs wandb: Agent Starting Run: 47lg0nn6 with config: batch_size: 3 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 47lg0nn6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.835459772497416
The number of items in train is:
12
The loss for epoch 0
0.9029549810414513
The running loss is:
22.96461908519268
The number of items in train is:
12
The loss for epoch 1
1.91371825709939
The running loss is:
15.761415027081966
The number of items in train is:
12
The loss for epoch 2
1.3134512522568305
The running loss is:
10.180416569113731
The number of items in train is:
12
The loss for epoch 3
0.8483680474261442
The running loss is:
9.744838282465935
The number of items in train is:
12
The loss for epoch 4
0.8120698568721613
The running loss is:
8.362954512238503
The number of items in train is:
12
The loss for epoch 5
0.6969128760198752
The running loss is:
7.482268325984478
The number of items in train is:
12
The loss for epoch 6
0.6235223604987065
The running loss is:
7.62644924223423
The number of items in train is:
12
The loss for epoch 7
0.6355374368528525
The running loss is:
6.36828438937664
The number of items in train is:
12
The loss for epoch 8
0.5306903657813867
The running loss is:
6.734523329883814
The number of items in train is:
12
The loss for epoch 9
0.5612102774903178
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.622638
48 30755 ... 13.911704
49 30756 ... 16.839764
50 30757 ... 11.906046
51 30758 ... 12.192764
52 30759 ... 13.010283
53 30760 ... 14.609374
54 30761 ... 13.891782
55 30762 ... 13.932491
56 30763 ... 13.201247
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 47lg0nn6 wandb: Agent Starting Run: rf0uogu2 with config: batch_size: 3 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: rf0uogu2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.08357983827591
The number of items in train is:
12
The loss for epoch 0
0.9236316531896591
The running loss is:
22.382230758666992
The number of items in train is:
12
The loss for epoch 1
1.8651858965555828
The running loss is:
15.076354868710041
The number of items in train is:
12
The loss for epoch 2
1.2563629057258368
The running loss is:
10.64572124928236
The number of items in train is:
12
The loss for epoch 3
0.8871434374401966
The running loss is:
10.859172463417053
The number of items in train is:
12
The loss for epoch 4
0.9049310386180878
The running loss is:
9.866730868816376
The number of items in train is:
12
The loss for epoch 5
0.8222275724013647
The running loss is:
9.314311161637306
The number of items in train is:
12
The loss for epoch 6
0.7761925968031088
The running loss is:
8.16476234793663
The number of items in train is:
12
The loss for epoch 7
0.6803968623280525
The running loss is:
7.3978771567344666
The number of items in train is:
12
The loss for epoch 8
0.6164897630612055
The running loss is:
8.245596423745155
The number of items in train is:
12
The loss for epoch 9
0.6871330353120962
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.262431
48 30755 ... 7.172925
49 30756 ... 10.437560
50 30757 ... 8.788393
51 30758 ... 7.332535
52 30759 ... 4.802159
53 30760 ... 2.583888
54 30761 ... -1.306381
55 30762 ... 0.795288
56 30763 ... 2.912030
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rf0uogu2 wandb: Agent Starting Run: qeeauzm6 with config: batch_size: 3 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: qeeauzm6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
83.36189612746239
The number of items in train is:
13
The loss for epoch 0
6.412453548266337
The running loss is:
25.860291827470064
The number of items in train is:
13
The loss for epoch 1
1.9892532174976973
The running loss is:
19.907233595848083
The number of items in train is:
13
The loss for epoch 2
1.5313256612190833
The running loss is:
10.90076495707035
The number of items in train is:
13
The loss for epoch 3
0.8385203813131039
The running loss is:
10.626565247774124
The number of items in train is:
13
The loss for epoch 4
0.8174280959826249
The running loss is:
9.881012380123138
The number of items in train is:
13
The loss for epoch 5
0.7600778753940876
The running loss is:
11.910851925611496
The number of items in train is:
13
The loss for epoch 6
0.916219378893192
The running loss is:
7.531356927007437
The number of items in train is:
13
The loss for epoch 7
0.5793351482313412
The running loss is:
10.415256395936012
The number of items in train is:
13
The loss for epoch 8
0.8011735689181548
The running loss is:
9.927764600142837
The number of items in train is:
13
The loss for epoch 9
0.7636742000109874
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.916672
48 30755 ... 12.625881
49 30756 ... 12.626095
50 30757 ... 11.517555
51 30758 ... 11.598584
52 30759 ... 12.085279
53 30760 ... 12.707908
54 30761 ... 12.770116
55 30762 ... 12.778158
56 30763 ... 12.802703
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qeeauzm6 wandb: Agent Starting Run: pfx7ru7f with config: batch_size: 3 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: pfx7ru7f
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
59.03156542778015
The number of items in train is:
12
The loss for epoch 0
4.919297118981679
The running loss is:
20.912684738636017
The number of items in train is:
12
The loss for epoch 1
1.7427237282196681
The running loss is:
12.18588924407959
The number of items in train is:
12
The loss for epoch 2
1.0154907703399658
The running loss is:
10.648322485387325
The number of items in train is:
12
The loss for epoch 3
0.8873602071156105
The running loss is:
10.730297669768333
The number of items in train is:
12
The loss for epoch 4
0.8941914724806944
The running loss is:
9.87667851895094
The number of items in train is:
12
The loss for epoch 5
0.8230565432459116
The running loss is:
9.237145557999611
The number of items in train is:
12
The loss for epoch 6
0.769762129833301
The running loss is:
8.763213515281677
The number of items in train is:
12
The loss for epoch 7
0.7302677929401398
The running loss is:
9.106015630066395
The number of items in train is:
12
The loss for epoch 8
0.7588346358388662
The running loss is:
8.237487856298685
The number of items in train is:
12
The loss for epoch 9
0.6864573213582238
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.006688
48 30755 ... 10.999264
49 30756 ... 10.443715
50 30757 ... 7.849214
51 30758 ... 7.840856
52 30759 ... 7.540580
53 30760 ... 7.049789
54 30761 ... 6.162581
55 30762 ... 5.630850
56 30763 ... 5.403432
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pfx7ru7f wandb: Agent Starting Run: hf37aby9 with config: batch_size: 3 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hf37aby9
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
48.265553653240204
The number of items in train is:
12
The loss for epoch 0
4.022129471103351
The running loss is:
17.88239400088787
The number of items in train is:
12
The loss for epoch 1
1.4901995000739892
The running loss is:
13.118484437465668
The number of items in train is:
12
The loss for epoch 2
1.0932070364554722
The running loss is:
10.311319708824158
The number of items in train is:
12
The loss for epoch 3
0.8592766424020132
The running loss is:
10.934739962220192
The number of items in train is:
12
The loss for epoch 4
0.911228330185016
The running loss is:
10.6557736992836
The number of items in train is:
12
The loss for epoch 5
0.8879811416069666
The running loss is:
10.139354795217514
The number of items in train is:
12
The loss for epoch 6
0.8449462329347929
The running loss is:
8.855517655611038
The number of items in train is:
12
The loss for epoch 7
0.7379598046342531
wandb: Network error resolved after 0:00:11.468286, resuming normal operation.
The running loss is: 9.930634662508965 The number of items in train is: 12 The loss for epoch 8 0.8275528885424137 The running loss is: 10.618825137615204 The number of items in train is: 12 The loss for epoch 9 0.884902094801267 interpolate should be below Now loading and scaling Colorado_Douglas County.csv CSV Path below Colorado_Douglas County.csv torch.Size([1, 6, 3]) Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.986316
48 30755 ... 12.381465
49 30756 ... 12.193325
50 30757 ... 11.790490
51 30758 ... 11.937226
52 30759 ... 12.096951
53 30760 ... 11.761296
54 30761 ... 12.113394
55 30762 ... 11.901037
56 30763 ... 11.604386
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hf37aby9 wandb: Agent Starting Run: u316b39b with config: batch_size: 3 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: u316b39b
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.37902383506298
The number of items in train is:
12
The loss for epoch 0
1.0315853195885818
The running loss is:
24.790918722748756
The number of items in train is:
12
The loss for epoch 1
2.0659098935623965
The running loss is:
8.455985829234123
The number of items in train is:
12
The loss for epoch 2
0.7046654857695103
The running loss is:
7.967825371772051
The number of items in train is:
12
The loss for epoch 3
0.6639854476476709
The running loss is:
7.571539465337992
The number of items in train is:
12
The loss for epoch 4
0.6309616221114993
The running loss is:
7.022769663482904
The number of items in train is:
12
The loss for epoch 5
0.5852308052902421
The running loss is:
6.53892756998539
The number of items in train is:
12
The loss for epoch 6
0.5449106308321158
The running loss is:
6.44024109095335
The number of items in train is:
12
The loss for epoch 7
0.5366867575794458
The running loss is:
6.065792869776487
The number of items in train is:
12
The loss for epoch 8
0.5054827391480406
The running loss is:
6.28930689394474
The number of items in train is:
12
The loss for epoch 9
0.5241089078287283
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.100678
48 30755 ... 9.491867
49 30756 ... 9.838396
50 30757 ... 9.236635
51 30758 ... 6.406833
52 30759 ... 6.267855
53 30760 ... 5.421679
54 30761 ... 4.986398
55 30762 ... 4.994775
56 30763 ... 4.666442
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u316b39b wandb: Agent Starting Run: n6k80t2e with config: batch_size: 3 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: n6k80t2e
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.276512056589127
The number of items in train is:
12
The loss for epoch 0
1.1063760047157605
The running loss is:
18.049271062016487
The number of items in train is:
12
The loss for epoch 1
1.5041059218347073
The running loss is:
8.319267615675926
The number of items in train is:
12
The loss for epoch 2
0.6932723013063272
The running loss is:
7.965411841869354
The number of items in train is:
12
The loss for epoch 3
0.6637843201557795
The running loss is:
7.3311899825930595
The number of items in train is:
12
The loss for epoch 4
0.6109324985494217
The running loss is:
6.7873126193881035
The number of items in train is:
12
The loss for epoch 5
0.5656093849490086
The running loss is:
6.498296394944191
The number of items in train is:
12
The loss for epoch 6
0.5415246995786825
The running loss is:
6.533873878419399
The number of items in train is:
12
The loss for epoch 7
0.5444894898682833
The running loss is:
6.097821369767189
The number of items in train is:
12
The loss for epoch 8
0.5081517808139324
The running loss is:
6.265468001365662
The number of items in train is:
12
The loss for epoch 9
0.5221223334471384
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.011338
48 30755 ... 7.283821
49 30756 ... 8.066407
50 30757 ... 8.368803
51 30758 ... 2.633995
52 30759 ... 1.451626
53 30760 ... -2.860904
54 30761 ... -3.623986
55 30762 ... -4.194643
56 30763 ... -4.595941
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n6k80t2e wandb: Agent Starting Run: ynqfy2li with config: batch_size: 3 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ynqfy2li
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.121348142623901
The number of items in train is:
12
The loss for epoch 0
1.1767790118853252
The running loss is:
11.962568417191505
The number of items in train is:
12
The loss for epoch 1
0.9968807014326254
The running loss is:
8.415272369980812
The number of items in train is:
12
The loss for epoch 2
0.701272697498401
The running loss is:
7.760982871055603
The number of items in train is:
12
The loss for epoch 3
0.6467485725879669
The running loss is:
7.097700580954552
The number of items in train is:
12
The loss for epoch 4
0.5914750484128793
The running loss is:
6.845601633191109
The number of items in train is:
12
The loss for epoch 5
0.5704668027659258
The running loss is:
6.674819730222225
The number of items in train is:
12
The loss for epoch 6
0.5562349775185188
The running loss is:
6.4955049604177475
The number of items in train is:
12
The loss for epoch 7
0.5412920800348123
The running loss is:
5.942568197846413
The number of items in train is:
12
The loss for epoch 8
0.49521401648720104
The running loss is:
6.2821846306324005
The number of items in train is:
12
The loss for epoch 9
0.5235153858860334
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.118464
48 30755 ... 10.848496
49 30756 ... 11.825148
50 30757 ... 13.083958
51 30758 ... 8.418689
52 30759 ... 8.725552
53 30760 ... 9.016667
54 30761 ... 8.915531
55 30762 ... 8.878509
56 30763 ... 8.781803
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ynqfy2li wandb: Agent Starting Run: z3a45bpw with config: batch_size: 3 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: z3a45bpw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.900953810662031
The number of items in train is:
12
The loss for epoch 0
0.825079484221836
The running loss is:
30.638646006584167
The number of items in train is:
12
The loss for epoch 1
2.5532205005486808
The running loss is:
13.565400153398514
The number of items in train is:
12
The loss for epoch 2
1.1304500127832096
The running loss is:
12.18923476524651
The number of items in train is:
12
The loss for epoch 3
1.0157695637705426
The running loss is:
9.495965160429478
The number of items in train is:
12
The loss for epoch 4
0.7913304300357898
The running loss is:
8.144568987190723
The number of items in train is:
12
The loss for epoch 5
0.6787140822658936
The running loss is:
7.078736245632172
The number of items in train is:
12
The loss for epoch 6
0.5898946871360143
The running loss is:
6.726401956751943
The number of items in train is:
12
The loss for epoch 7
0.5605334963959953
The running loss is:
6.241230476647615
The number of items in train is:
12
The loss for epoch 8
0.5201025397206346
The running loss is:
6.079278342425823
The number of items in train is:
12
The loss for epoch 9
0.5066065285354853
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.471974
48 30755 ... 10.483409
49 30756 ... 10.175096
50 30757 ... 10.090322
51 30758 ... 6.847208
52 30759 ... 6.857956
53 30760 ... 6.441480
54 30761 ... 5.431954
55 30762 ... 5.906725
56 30763 ... 5.729991
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z3a45bpw wandb: Agent Starting Run: sqgiswkh with config: batch_size: 3 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sqgiswkh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.352339945733547
The number of items in train is:
12
The loss for epoch 0
0.8626949954777956
The running loss is:
27.420582100749016
The number of items in train is:
12
The loss for epoch 1
2.2850485083957515
The running loss is:
11.992324955761433
The number of items in train is:
12
The loss for epoch 2
0.9993604129801194
The running loss is:
11.289713278412819
The number of items in train is:
12
The loss for epoch 3
0.9408094398677349
The running loss is:
8.813286826014519
The number of items in train is:
12
The loss for epoch 4
0.7344405688345432
The running loss is:
7.834414124488831
The number of items in train is:
12
The loss for epoch 5
0.6528678437074026
The running loss is:
7.225820302963257
The number of items in train is:
12
The loss for epoch 6
0.6021516919136047
The running loss is:
6.88609754294157
The number of items in train is:
12
The loss for epoch 7
0.5738414619117975
The running loss is:
6.201435163617134
The number of items in train is:
12
The loss for epoch 8
0.5167862636347612
The running loss is:
6.14191147685051
The number of items in train is:
12
The loss for epoch 9
0.5118259564042091
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.614470
48 30755 ... 8.827579
49 30756 ... 9.241714
50 30757 ... 10.226584
51 30758 ... 5.223353
52 30759 ... 4.789123
53 30760 ... 2.735260
54 30761 ... 2.197710
55 30762 ... 2.011790
56 30763 ... 2.039282
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sqgiswkh wandb: Agent Starting Run: ihyxflsp with config: batch_size: 3 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ihyxflsp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.217051550745964
The number of items in train is:
12
The loss for epoch 0
0.934754295895497
The running loss is:
23.319495856761932
The number of items in train is:
12
The loss for epoch 1
1.9432913213968277
The running loss is:
10.772423923015594
The number of items in train is:
12
The loss for epoch 2
0.8977019935846329
The running loss is:
10.515882782638073
The number of items in train is:
12
The loss for epoch 3
0.8763235652198395
The running loss is:
8.058349311351776
The number of items in train is:
12
The loss for epoch 4
0.6715291092793146
The running loss is:
7.961005441844463
The number of items in train is:
12
The loss for epoch 5
0.6634171201537052
The running loss is:
7.059004873037338
The number of items in train is:
12
The loss for epoch 6
0.5882504060864449
The running loss is:
6.685458019375801
The number of items in train is:
12
The loss for epoch 7
0.5571215016146501
The running loss is:
6.883459039032459
The number of items in train is:
12
The loss for epoch 8
0.5736215865860382
The running loss is:
7.376760378479958
The number of items in train is:
12
The loss for epoch 9
0.6147300315399965
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.814974
48 30755 ... 11.210552
49 30756 ... 11.776529
50 30757 ... 12.432104
51 30758 ... 9.630356
52 30759 ... 9.944347
53 30760 ... 10.629821
54 30761 ... 10.653158
55 30762 ... 11.109354
56 30763 ... 10.805975
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ihyxflsp wandb: Agent Starting Run: 3b2n88ri with config: batch_size: 3 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3b2n88ri
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.48319063708186
The number of items in train is:
12
The loss for epoch 0
1.5402658864234884
The running loss is:
18.761643692851067
The number of items in train is:
12
The loss for epoch 1
1.5634703077375889
The running loss is:
21.986995615065098
The number of items in train is:
12
The loss for epoch 2
1.8322496345887582
The running loss is:
9.689714223146439
The number of items in train is:
12
The loss for epoch 3
0.8074761852622032
The running loss is:
9.407272886484861
The number of items in train is:
12
The loss for epoch 4
0.7839394072070718
The running loss is:
8.005861973389983
The number of items in train is:
12
The loss for epoch 5
0.6671551644491652
The running loss is:
7.884846691042185
The number of items in train is:
12
The loss for epoch 6
0.6570705575868487
The running loss is:
7.528995893895626
The number of items in train is:
12
The loss for epoch 7
0.6274163244913021
The running loss is:
8.065547659993172
The number of items in train is:
12
The loss for epoch 8
0.6721289716660976
The running loss is:
6.982815816998482
The number of items in train is:
12
The loss for epoch 9
0.5819013180832068
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.516898
48 30755 ... 11.084952
49 30756 ... 10.106272
50 30757 ... 10.063417
51 30758 ... 8.037376
52 30759 ... 8.120486
53 30760 ... 8.132099
54 30761 ... 7.003942
55 30762 ... 6.952409
56 30763 ... 6.685895
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3b2n88ri wandb: Agent Starting Run: no85t7az with config: batch_size: 3 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: no85t7az
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.000954568386078
The number of items in train is:
12
The loss for epoch 0
1.2500795473655064
The running loss is:
21.221872463822365
The number of items in train is:
12
The loss for epoch 1
1.768489371985197
The running loss is:
19.358168706297874
The number of items in train is:
12
The loss for epoch 2
1.613180725524823
The running loss is:
9.955740116536617
The number of items in train is:
12
The loss for epoch 3
0.8296450097113848
The running loss is:
9.47061137482524
The number of items in train is:
12
The loss for epoch 4
0.7892176145687699
The running loss is:
8.324287980794907
The number of items in train is:
12
The loss for epoch 5
0.6936906650662422
The running loss is:
7.854575924575329
The number of items in train is:
12
The loss for epoch 6
0.6545479937146107
The running loss is:
7.608733028173447
The number of items in train is:
12
The loss for epoch 7
0.6340610856811205
The running loss is:
6.9321389347314835
The number of items in train is:
12
The loss for epoch 8
0.577678244560957
The running loss is:
6.323972467333078
The number of items in train is:
12
The loss for epoch 9
0.5269977056110898
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.542080
48 30755 ... 8.818997
49 30756 ... 8.390926
50 30757 ... 10.149011
51 30758 ... 5.601892
52 30759 ... 4.554304
53 30760 ... 2.250141
54 30761 ... -1.074027
55 30762 ... 1.474841
56 30763 ... -1.939803
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: no85t7az wandb: Agent Starting Run: qrike4wt with config: batch_size: 3 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qrike4wt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.473877847194672
The number of items in train is:
12
The loss for epoch 0
0.9561564872662226
The running loss is:
17.159127980470657
The number of items in train is:
12
The loss for epoch 1
1.429927331705888
The running loss is:
13.055007100105286
The number of items in train is:
12
The loss for epoch 2
1.087917258342107
The running loss is:
9.946389883756638
The number of items in train is:
12
The loss for epoch 3
0.8288658236463865
The running loss is:
8.777176484465599
The number of items in train is:
12
The loss for epoch 4
0.7314313737054666
The running loss is:
8.020771831274033
The number of items in train is:
12
The loss for epoch 5
0.6683976526061693
The running loss is:
7.233478561043739
The number of items in train is:
12
The loss for epoch 6
0.6027898800869783
The running loss is:
6.712913706898689
The number of items in train is:
12
The loss for epoch 7
0.5594094755748907
The running loss is:
5.935887351632118
The number of items in train is:
12
The loss for epoch 8
0.4946572793026765
The running loss is:
6.456776849925518
The number of items in train is:
12
The loss for epoch 9
0.5380647374937931
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.739307
48 30755 ... 15.164424
49 30756 ... 14.982607
50 30757 ... 12.120775
51 30758 ... 6.994554
52 30759 ... 6.006286
53 30760 ... 5.992099
54 30761 ... 7.558724
55 30762 ... 7.050504
56 30763 ... 6.311695
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qrike4wt wandb: Agent Starting Run: p21rcgtl with config: batch_size: 3 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: p21rcgtl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
106.6566134095192
The number of items in train is:
12
The loss for epoch 0
8.888051117459932
The running loss is:
24.606463849544525
The number of items in train is:
12
The loss for epoch 1
2.0505386541287103
The running loss is:
21.61753984540701
The number of items in train is:
12
The loss for epoch 2
1.8014616537839174
The running loss is:
23.79516276717186
The number of items in train is:
12
The loss for epoch 3
1.982930230597655
The running loss is:
11.609253287315369
The number of items in train is:
12
The loss for epoch 4
0.9674377739429474
The running loss is:
11.628214344382286
The number of items in train is:
12
The loss for epoch 5
0.9690178620318571
The running loss is:
9.073524564504623
The number of items in train is:
12
The loss for epoch 6
0.7561270470420519
The running loss is:
9.348070994019508
The number of items in train is:
12
The loss for epoch 7
0.7790059161682924
The running loss is:
9.628808468580246
The number of items in train is:
12
The loss for epoch 8
0.8024007057150205
The running loss is:
9.66310379654169
The number of items in train is:
12
The loss for epoch 9
0.8052586497118076
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.878821
48 30755 ... 14.621321
49 30756 ... 13.972424
50 30757 ... 12.111570
51 30758 ... 10.287642
52 30759 ... 10.387918
53 30760 ... 10.812337
54 30761 ... 9.955990
55 30762 ... 11.362534
56 30763 ... 12.467662
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: p21rcgtl wandb: Agent Starting Run: k6byrhpo with config: batch_size: 3 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: k6byrhpo
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
81.6181215941906
The number of items in train is:
12
The loss for epoch 0
6.8015101328492165
The running loss is:
22.043223172426224
The number of items in train is:
12
The loss for epoch 1
1.836935264368852
The running loss is:
14.447735771536827
The number of items in train is:
12
The loss for epoch 2
1.2039779809614022
The running loss is:
15.471910580992699
The number of items in train is:
12
The loss for epoch 3
1.2893258817493916
The running loss is:
11.04138045758009
The number of items in train is:
12
The loss for epoch 4
0.9201150381316742
The running loss is:
12.106047950685024
The number of items in train is:
12
The loss for epoch 5
1.008837329223752
The running loss is:
10.577641814947128
The number of items in train is:
12
The loss for epoch 6
0.881470151245594
The running loss is:
9.409645445644855
The number of items in train is:
12
The loss for epoch 7
0.7841371204704046
The running loss is:
8.933936536312103
The number of items in train is:
12
The loss for epoch 8
0.744494711359342
The running loss is:
8.221374459564686
The number of items in train is:
12
The loss for epoch 9
0.6851145382970572
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.061282
48 30755 ... 8.249587
49 30756 ... 9.267735
50 30757 ... 11.273976
51 30758 ... 9.497227
52 30759 ... 8.919030
53 30760 ... 7.004339
54 30761 ... 4.377275
55 30762 ... 3.087500
56 30763 ... 4.338648
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: k6byrhpo wandb: Agent Starting Run: 52seuqzl with config: batch_size: 3 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 52seuqzl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
56.113191187381744
The number of items in train is:
12
The loss for epoch 0
4.676099265615146
The running loss is:
18.30052262544632
The number of items in train is:
12
The loss for epoch 1
1.5250435521205266
The running loss is:
11.604714661836624
The number of items in train is:
12
The loss for epoch 2
0.967059555153052
The running loss is:
14.872128278017044
The number of items in train is:
12
The loss for epoch 3
1.239344023168087
The running loss is:
10.402111932635307
The number of items in train is:
12
The loss for epoch 4
0.8668426610529423
The running loss is:
10.397299006581306
The number of items in train is:
12
The loss for epoch 5
0.8664415838817755
The running loss is:
9.851659432053566
The number of items in train is:
12
The loss for epoch 6
0.8209716193377972
The running loss is:
9.47095012664795
The number of items in train is:
12
The loss for epoch 7
0.7892458438873291
The running loss is:
8.210800468921661
The number of items in train is:
12
The loss for epoch 8
0.6842333724101385
The running loss is:
8.250100195407867
The number of items in train is:
12
The loss for epoch 9
0.6875083496173223
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.827257
48 30755 ... 13.631978
49 30756 ... 11.137757
50 30757 ... 6.047119
51 30758 ... 6.934722
52 30759 ... 6.921974
53 30760 ... 6.659066
54 30761 ... 6.745699
55 30762 ... 8.320328
56 30763 ... 4.086565
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 52seuqzl wandb: Agent Starting Run: 4i7r4tc9 with config: batch_size: 3 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 4i7r4tc9
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.96486447751522
The number of items in train is:
12
The loss for epoch 0
1.2470720397929351
The running loss is:
12.224298192188144
The number of items in train is:
12
The loss for epoch 1
1.0186915160156786
The running loss is:
8.319845624268055
The number of items in train is:
12
The loss for epoch 2
0.6933204686890045
The running loss is:
7.175463631749153
The number of items in train is:
12
The loss for epoch 3
0.5979553026457628
The running loss is:
6.868135239928961
The number of items in train is:
12
The loss for epoch 4
0.5723446033274134
The running loss is:
6.5902868285775185
The number of items in train is:
12
The loss for epoch 5
0.5491905690481266
The running loss is:
5.774220548570156
The number of items in train is:
12
The loss for epoch 6
0.4811850457141797
The running loss is:
5.966882690787315
The number of items in train is:
12
The loss for epoch 7
0.49724022423227626
The running loss is:
6.034196428954601
The number of items in train is:
12
The loss for epoch 8
0.5028497024128834
The running loss is:
5.637171816080809
The number of items in train is:
12
The loss for epoch 9
0.46976431800673407
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.883840
48 30755 ... 11.236866
49 30756 ... 15.306927
50 30757 ... 14.193745
51 30758 ... 10.605540
52 30759 ... 10.219217
53 30760 ... 11.046711
54 30761 ... 10.211071
55 30762 ... 10.935491
56 30763 ... 12.956865
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4i7r4tc9 wandb: Agent Starting Run: ik2lbrgv with config: batch_size: 3 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ik2lbrgv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.35646590590477
The number of items in train is:
12
The loss for epoch 0
1.3630388254920642
The running loss is:
13.501704521477222
The number of items in train is:
12
The loss for epoch 1
1.1251420434564352
The running loss is:
10.06986141204834
The number of items in train is:
12
The loss for epoch 2
0.839155117670695
The running loss is:
9.339474618434906
The number of items in train is:
12
The loss for epoch 3
0.7782895515362421
The running loss is:
8.55732698738575
The number of items in train is:
12
The loss for epoch 4
0.7131105822821459
The running loss is:
7.9432243257761
The number of items in train is:
12
The loss for epoch 5
0.6619353604813417
The running loss is:
7.743864074349403
The number of items in train is:
12
The loss for epoch 6
0.6453220061957836
The running loss is:
8.010289520025253
The number of items in train is:
12
The loss for epoch 7
0.6675241266687711
The running loss is:
8.142023041844368
The number of items in train is:
12
The loss for epoch 8
0.6785019201536974
The running loss is:
7.777196206152439
The number of items in train is:
12
The loss for epoch 9
0.6480996838460366
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.629007
48 30755 ... 12.902403
49 30756 ... 13.270831
50 30757 ... 14.083817
51 30758 ... 15.179794
52 30759 ... 12.242359
53 30760 ... 13.066635
54 30761 ... 13.783864
55 30762 ... 13.845278
56 30763 ... 13.984291
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ik2lbrgv wandb: Agent Starting Run: 7774hcks with config: batch_size: 3 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 7774hcks
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.757839009165764
The number of items in train is:
11
The loss for epoch 0
1.2507126371968875
The running loss is:
12.586623467504978
The number of items in train is:
11
The loss for epoch 1
1.1442384970459072
The running loss is:
7.428445756435394
The number of items in train is:
11
The loss for epoch 2
0.6753132505850359
The running loss is:
7.001081258058548
The number of items in train is:
11
The loss for epoch 3
0.6364619325507771
The running loss is:
6.894729509949684
The number of items in train is:
11
The loss for epoch 4
0.6267935918136076
The running loss is:
6.393982410430908
The number of items in train is:
11
The loss for epoch 5
0.5812711282209917
The running loss is:
6.316303074359894
The number of items in train is:
11
The loss for epoch 6
0.574209370396354
The running loss is:
6.03164541721344
The number of items in train is:
11
The loss for epoch 7
0.5483314015648582
The running loss is:
6.234783947467804
The number of items in train is:
11
The loss for epoch 8
0.5667985406788912
The running loss is:
5.846083365380764
The number of items in train is:
11
The loss for epoch 9
0.531462124125524
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.596305
48 30755 ... 8.830587
49 30756 ... 10.474157
50 30757 ... 9.988824
51 30758 ... 8.092268
52 30759 ... 5.362512
53 30760 ... 4.972435
54 30761 ... 4.711842
55 30762 ... 4.008645
56 30763 ... 4.052268
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7774hcks wandb: Agent Starting Run: fazaiyk7 with config: batch_size: 3 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fazaiyk7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.830055439844728
The number of items in train is:
12
The loss for epoch 0
1.0691712866537273
The running loss is:
24.132599594071507
The number of items in train is:
12
The loss for epoch 1
2.0110499661726258
The running loss is:
10.497571967542171
The number of items in train is:
12
The loss for epoch 2
0.8747976639618477
The running loss is:
9.687794238328934
The number of items in train is:
12
The loss for epoch 3
0.8073161865274111
The running loss is:
7.763237036764622
The number of items in train is:
12
The loss for epoch 4
0.6469364197303852
The running loss is:
6.961419679224491
The number of items in train is:
12
The loss for epoch 5
0.5801183066020409
The running loss is:
6.35853485763073
The number of items in train is:
12
The loss for epoch 6
0.5298779048025608
The running loss is:
6.827462054789066
The number of items in train is:
12
The loss for epoch 7
0.5689551712324222
The running loss is:
6.0002028569579124
The number of items in train is:
12
The loss for epoch 8
0.5000169047464927
The running loss is:
5.485427591949701
The number of items in train is:
12
The loss for epoch 9
0.4571189659958084
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.419744
48 30755 ... 10.394965
49 30756 ... 12.905848
50 30757 ... 12.309278
51 30758 ... 10.093750
52 30759 ... 9.698062
53 30760 ... 9.674794
54 30761 ... 9.306669
55 30762 ... 9.657249
56 30763 ... 11.260552
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fazaiyk7 wandb: Agent Starting Run: 1n7vdt7z with config: batch_size: 3 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 1n7vdt7z
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.794403530657291
The number of items in train is:
12
The loss for epoch 0
1.1495336275547743
The running loss is:
24.844410978257656
The number of items in train is:
12
The loss for epoch 1
2.0703675815214715
The running loss is:
12.776588022708893
The number of items in train is:
12
The loss for epoch 2
1.0647156685590744
The running loss is:
11.807799771428108
The number of items in train is:
12
The loss for epoch 3
0.9839833142856756
The running loss is:
9.790398374199867
The number of items in train is:
12
The loss for epoch 4
0.8158665311833223
The running loss is:
8.584115162491798
The number of items in train is:
12
The loss for epoch 5
0.7153429302076498
The running loss is:
8.691331028938293
The number of items in train is:
12
The loss for epoch 6
0.7242775857448578
The running loss is:
8.91648381948471
The number of items in train is:
12
The loss for epoch 7
0.7430403182903925
The running loss is:
7.640511985868216
The number of items in train is:
12
The loss for epoch 8
0.6367093321556846
The running loss is:
7.013014301657677
The number of items in train is:
12
The loss for epoch 9
0.5844178584714731
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.307647
48 30755 ... 12.129790
49 30756 ... 12.597713
50 30757 ... 13.174250
51 30758 ... 13.365698
52 30759 ... 11.487959
53 30760 ... 11.916497
54 30761 ... 11.573297
55 30762 ... 12.028158
56 30763 ... 12.942216
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1n7vdt7z wandb: Agent Starting Run: mxzlg74h with config: batch_size: 3 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: mxzlg74h
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.668571203947067
The number of items in train is:
11
The loss for epoch 0
0.9698701094497334
The running loss is:
23.13605907559395
The number of items in train is:
11
The loss for epoch 1
2.103278097781268
The running loss is:
9.648351326584816
The number of items in train is:
11
The loss for epoch 2
0.8771228478713469
The running loss is:
8.99851730465889
The number of items in train is:
11
The loss for epoch 3
0.8180470276962627
The running loss is:
7.207675918936729
The number of items in train is:
11
The loss for epoch 4
0.6552432653578845
The running loss is:
6.6272143721580505
The number of items in train is:
11
The loss for epoch 5
0.60247403383255
The running loss is:
6.662739872932434
The number of items in train is:
11
The loss for epoch 6
0.6057036248120394
The running loss is:
6.596592366695404
The number of items in train is:
11
The loss for epoch 7
0.5996902151541277
The running loss is:
6.8548741936683655
The number of items in train is:
11
The loss for epoch 8
0.6231703812425787
The running loss is:
6.773262917995453
The number of items in train is:
11
The loss for epoch 9
0.615751174363223
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.957825
48 30755 ... 12.084987
49 30756 ... 13.182026
50 30757 ... 12.881509
51 30758 ... 11.651135
52 30759 ... 11.314957
53 30760 ... 11.726182
54 30761 ... 11.451635
55 30762 ... 11.618547
56 30763 ... 12.218330
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mxzlg74h wandb: Agent Starting Run: 2n0cdb0f with config: batch_size: 3 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 2n0cdb0f
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.547422602772713
The number of items in train is:
12
The loss for epoch 0
0.9622852168977261
The running loss is:
18.635728433728218
The number of items in train is:
12
The loss for epoch 1
1.5529773694773514
The running loss is:
13.359365157783031
The number of items in train is:
12
The loss for epoch 2
1.1132804298152525
The running loss is:
8.741095915436745
The number of items in train is:
12
The loss for epoch 3
0.7284246596197287
The running loss is:
7.996406886726618
The number of items in train is:
12
The loss for epoch 4
0.6663672405605515
The running loss is:
8.061928812414408
The number of items in train is:
12
The loss for epoch 5
0.671827401034534
The running loss is:
7.5982563234865665
The number of items in train is:
12
The loss for epoch 6
0.6331880269572139
The running loss is:
9.899934113025665
The number of items in train is:
12
The loss for epoch 7
0.8249945094188055
The running loss is:
9.39713741093874
The number of items in train is:
12
The loss for epoch 8
0.783094784244895
The running loss is:
7.772306106984615
The number of items in train is:
12
The loss for epoch 9
0.6476921755820513
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.623840
48 30755 ... 13.129992
49 30756 ... 15.464817
50 30757 ... 14.150119
51 30758 ... 11.621802
52 30759 ... 11.351404
53 30760 ... 11.836058
54 30761 ... 11.804684
55 30762 ... 12.114832
56 30763 ... 12.380978
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2n0cdb0f wandb: Agent Starting Run: 2l8cqkpb with config: batch_size: 3 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2l8cqkpb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.721733957529068
The number of items in train is:
12
The loss for epoch 0
0.9768111631274223
The running loss is:
20.882812559604645
The number of items in train is:
12
The loss for epoch 1
1.7402343799670537
The running loss is:
15.462991893291473
The number of items in train is:
12
The loss for epoch 2
1.2885826577742894
The running loss is:
10.39606124162674
The number of items in train is:
12
The loss for epoch 3
0.8663384368022283
The running loss is:
11.118731543421745
The number of items in train is:
12
The loss for epoch 4
0.9265609619518121
The running loss is:
9.71517413854599
The number of items in train is:
12
The loss for epoch 5
0.8095978448788325
The running loss is:
9.132946863770485
The number of items in train is:
12
The loss for epoch 6
0.7610789053142071
The running loss is:
8.82024759054184
The number of items in train is:
12
The loss for epoch 7
0.7350206325451533
The running loss is:
9.627787470817566
The number of items in train is:
12
The loss for epoch 8
0.8023156225681305
The running loss is:
9.905424669384956
The number of items in train is:
12
The loss for epoch 9
0.8254520557820797
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.262950
48 30755 ... 12.280198
49 30756 ... 12.347271
50 30757 ... 12.375588
51 30758 ... 12.327335
52 30759 ... 11.542714
53 30760 ... 11.688055
54 30761 ... 11.880280
55 30762 ... 11.786964
56 30763 ... 11.815796
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2l8cqkpb wandb: Agent Starting Run: gujj856e with config: batch_size: 3 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: gujj856e
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.164023727178574
The number of items in train is:
11
The loss for epoch 0
1.0149112479253248
The running loss is:
17.79230636358261
The number of items in train is:
11
The loss for epoch 1
1.6174823966893284
The running loss is:
17.12361752986908
The number of items in train is:
11
The loss for epoch 2
1.5566925027153709
The running loss is:
9.037766844034195
The number of items in train is:
11
The loss for epoch 3
0.8216151676394723
The running loss is:
8.182956509292126
The number of items in train is:
11
The loss for epoch 4
0.743905137208375
The running loss is:
7.224704436957836
The number of items in train is:
11
The loss for epoch 5
0.6567913124507124
The running loss is:
7.649267762899399
The number of items in train is:
11
The loss for epoch 6
0.6953879784453999
The running loss is:
8.003631204366684
The number of items in train is:
11
The loss for epoch 7
0.7276028367606077
The running loss is:
6.828029468655586
The number of items in train is:
11
The loss for epoch 8
0.6207299516959623
The running loss is:
6.247038394212723
The number of items in train is:
11
The loss for epoch 9
0.5679125812920657
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.589057
48 30755 ... 8.376153
49 30756 ... 12.800483
50 30757 ... 11.489994
51 30758 ... 6.177326
52 30759 ... 5.413992
53 30760 ... 5.787818
54 30761 ... 3.973889
55 30762 ... 4.382355
56 30763 ... 7.866238
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gujj856e wandb: Agent Starting Run: g7si3dxc with config: batch_size: 3 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: g7si3dxc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
61.024581253528595
The number of items in train is:
12
The loss for epoch 0
5.085381771127383
The running loss is:
19.56476752460003
The number of items in train is:
12
The loss for epoch 1
1.630397293716669
The running loss is:
13.355403766036034
The number of items in train is:
12
The loss for epoch 2
1.1129503138363361
The running loss is:
8.840511664748192
The number of items in train is:
12
The loss for epoch 3
0.7367093053956827
The running loss is:
11.761417895555496
The number of items in train is:
12
The loss for epoch 4
0.980118157962958
The running loss is:
7.811135046184063
The number of items in train is:
12
The loss for epoch 5
0.6509279205153385
The running loss is:
10.606959201395512
The number of items in train is:
12
The loss for epoch 6
0.8839132667829593
The running loss is:
10.005793422460556
The number of items in train is:
12
The loss for epoch 7
0.8338161185383797
The running loss is:
10.245696619153023
The number of items in train is:
12
The loss for epoch 8
0.8538080515960852
The running loss is:
8.148609265685081
The number of items in train is:
12
The loss for epoch 9
0.6790507721404234
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.476348
48 30755 ... 11.340790
49 30756 ... 10.125632
50 30757 ... 11.163449
51 30758 ... 11.226076
52 30759 ... 9.715280
53 30760 ... 9.543046
54 30761 ... 9.841347
55 30762 ... 8.556845
56 30763 ... 8.463352
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: g7si3dxc wandb: Agent Starting Run: v0u99efc with config: batch_size: 3 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: v0u99efc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.21212914586067
The number of items in train is:
12
The loss for epoch 0
4.267677428821723
The running loss is:
17.462961047887802
The number of items in train is:
12
The loss for epoch 1
1.4552467539906502
The running loss is:
11.688251674175262
The number of items in train is:
12
The loss for epoch 2
0.9740209728479385
The running loss is:
11.13100489974022
The number of items in train is:
12
The loss for epoch 3
0.9275837416450182
The running loss is:
13.137617707252502
The number of items in train is:
12
The loss for epoch 4
1.0948014756043751
The running loss is:
11.458725690841675
The number of items in train is:
12
The loss for epoch 5
0.9548938075701395
The running loss is:
11.170249596238136
The number of items in train is:
12
The loss for epoch 6
0.9308541330198447
The running loss is:
12.042376711964607
The number of items in train is:
12
The loss for epoch 7
1.0035313926637173
The running loss is:
11.790812149643898
The number of items in train is:
12
The loss for epoch 8
0.9825676791369915
The running loss is:
10.290245652198792
The number of items in train is:
12
The loss for epoch 9
0.8575204710165659
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.570718
48 30755 ... 9.376223
49 30756 ... 10.485181
50 30757 ... 9.978682
51 30758 ... 10.126886
52 30759 ... 9.919448
53 30760 ... 9.927864
54 30761 ... 9.905344
55 30762 ... 9.926155
56 30763 ... 9.923842
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v0u99efc wandb: Agent Starting Run: 1ly9p6oz with config: batch_size: 3 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1ly9p6oz
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
72.31613194942474
The number of items in train is:
11
The loss for epoch 0
6.574193813584068
The running loss is:
14.23465946316719
The number of items in train is:
11
The loss for epoch 1
1.2940599511970172
The running loss is:
15.22510826587677
The number of items in train is:
11
The loss for epoch 2
1.3841007514433428
The running loss is:
9.192183136940002
The number of items in train is:
11
The loss for epoch 3
0.8356530124490912
The running loss is:
13.560538858175278
The number of items in train is:
11
The loss for epoch 4
1.232776259834116
The running loss is:
9.145589001476765
The number of items in train is:
11
The loss for epoch 5
0.8314171819524332
The running loss is:
9.26624071598053
The number of items in train is:
11
The loss for epoch 6
0.8423855196345936
The running loss is:
8.879170209169388
The number of items in train is:
11
The loss for epoch 7
0.8071972917426716
The running loss is:
8.084219574928284
The number of items in train is:
11
The loss for epoch 8
0.7349290522662076
The running loss is:
7.389895915985107
The number of items in train is:
11
The loss for epoch 9
0.6718087196350098
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.939209
48 30755 ... 12.250442
49 30756 ... 12.442574
50 30757 ... 12.579393
51 30758 ... 12.585279
52 30759 ... 10.368646
53 30760 ... 10.346539
54 30761 ... 9.573850
55 30762 ... 9.755535
56 30763 ... 10.039600
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1ly9p6oz wandb: Agent Starting Run: fpttgkw6 with config: batch_size: 3 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fpttgkw6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.689834764227271
The number of items in train is:
12
The loss for epoch 0
1.2241528970189393
The running loss is:
17.333957076072693
The number of items in train is:
12
The loss for epoch 1
1.4444964230060577
The running loss is:
8.697230853140354
The number of items in train is:
12
The loss for epoch 2
0.7247692377616962
The running loss is:
7.709598541259766
The number of items in train is:
12
The loss for epoch 3
0.6424665451049805
The running loss is:
7.4310178607702255
The number of items in train is:
12
The loss for epoch 4
0.6192514883975188
The running loss is:
7.121323108673096
The number of items in train is:
12
The loss for epoch 5
0.5934435923894247
The running loss is:
7.340858735144138
The number of items in train is:
12
The loss for epoch 6
0.6117382279286782
The running loss is:
6.431899104267359
The number of items in train is:
12
The loss for epoch 7
0.5359915920222799
The running loss is:
6.767576105892658
The number of items in train is:
12
The loss for epoch 8
0.5639646754910549
The running loss is:
5.908991951495409
The number of items in train is:
12
The loss for epoch 9
0.49241599595795077
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.737906
48 30755 ... 12.948818
49 30756 ... 13.574800
50 30757 ... 15.269091
51 30758 ... 14.614594
52 30759 ... 12.398319
53 30760 ... 10.582185
54 30761 ... 11.137925
55 30762 ... 11.406140
56 30763 ... 11.445395
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fpttgkw6 wandb: Agent Starting Run: 8l1gnmez with config: batch_size: 3 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 8l1gnmez
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.333956763148308
The number of items in train is:
11
The loss for epoch 0
1.212177887558937
The running loss is:
10.76390040293336
The number of items in train is:
11
The loss for epoch 1
0.978536400266669
The running loss is:
7.724426813423634
The number of items in train is:
11
The loss for epoch 2
0.7022206194021485
The running loss is:
6.70024798065424
The number of items in train is:
11
The loss for epoch 3
0.6091134527867491
The running loss is:
6.150171548128128
The number of items in train is:
11
The loss for epoch 4
0.5591065043752844
The running loss is:
5.95460768789053
The number of items in train is:
11
The loss for epoch 5
0.5413279716264118
The running loss is:
5.616045318543911
The number of items in train is:
11
The loss for epoch 6
0.5105495744130828
The running loss is:
5.45828965306282
The number of items in train is:
11
The loss for epoch 7
0.49620815027843823
The running loss is:
5.082308158278465
The number of items in train is:
11
The loss for epoch 8
0.4620280143889514
The running loss is:
5.413075998425484
The number of items in train is:
11
The loss for epoch 9
0.49209781803868036
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.038165
48 30755 ... 10.608909
49 30756 ... 11.677846
50 30757 ... 13.408486
51 30758 ... 12.285883
52 30759 ... 8.894649
53 30760 ... 6.958979
54 30761 ... 7.109767
55 30762 ... 7.204705
56 30763 ... 7.257286
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8l1gnmez wandb: Agent Starting Run: r504iyh8 with config: batch_size: 3 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: r504iyh8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.602686673402786
The number of items in train is:
11
The loss for epoch 0
1.0547896975820714
The running loss is:
22.047383695840836
The number of items in train is:
11
The loss for epoch 1
2.004307608712803
The running loss is:
8.506498038768768
The number of items in train is:
11
The loss for epoch 2
0.7733180035244335
The running loss is:
7.987618550658226
The number of items in train is:
11
The loss for epoch 3
0.7261471409689296
The running loss is:
7.208950437605381
The number of items in train is:
11
The loss for epoch 4
0.6553591306913983
The running loss is:
6.687433920800686
The number of items in train is:
11
The loss for epoch 5
0.6079485382546078
The running loss is:
6.712285548448563
The number of items in train is:
11
The loss for epoch 6
0.6102077771316875
The running loss is:
6.500350695103407
The number of items in train is:
11
The loss for epoch 7
0.5909409722821279
The running loss is:
6.381061501801014
The number of items in train is:
11
The loss for epoch 8
0.5800965001637285
The running loss is:
6.392539195716381
The number of items in train is:
11
The loss for epoch 9
0.5811399268833074
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.245036
48 30755 ... 8.228024
49 30756 ... 8.517384
50 30757 ... 8.960963
51 30758 ... 8.680799
52 30759 ... 7.213123
53 30760 ... 4.665875
54 30761 ... 4.856624
55 30762 ... 4.900586
56 30763 ... 4.092776
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r504iyh8 wandb: Agent Starting Run: aw63m4rp with config: batch_size: 3 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: aw63m4rp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.29787865281105
The number of items in train is:
12
The loss for epoch 0
1.0248232210675876
The running loss is:
19.8064456731081
The number of items in train is:
12
The loss for epoch 1
1.6505371394256751
The running loss is:
11.618107497692108
The number of items in train is:
12
The loss for epoch 2
0.9681756248076757
The running loss is:
8.902291357517242
The number of items in train is:
12
The loss for epoch 3
0.7418576131264368
The running loss is:
7.879129042848945
The number of items in train is:
12
The loss for epoch 4
0.6565940869040787
The running loss is:
6.330558676272631
The number of items in train is:
12
The loss for epoch 5
0.5275465563560525
The running loss is:
7.807648062705994
The number of items in train is:
12
The loss for epoch 6
0.6506373385588328
The running loss is:
7.306606873869896
The number of items in train is:
12
The loss for epoch 7
0.6088839061558247
The running loss is:
6.763071320950985
The number of items in train is:
12
The loss for epoch 8
0.5635892767459154
The running loss is:
6.004747994244099
The number of items in train is:
12
The loss for epoch 9
0.5003956661870083
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.441623
48 30755 ... 11.198905
49 30756 ... 13.271868
50 30757 ... 16.523909
51 30758 ... 14.391433
52 30759 ... 9.663706
53 30760 ... 12.368917
54 30761 ... 15.554323
55 30762 ... 13.051601
56 30763 ... 13.088296
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: aw63m4rp wandb: Agent Starting Run: bv5gfbfq with config: batch_size: 3 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: bv5gfbfq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.102504268288612
The number of items in train is:
11
The loss for epoch 0
1.0093185698444194
The running loss is:
19.026846826076508
The number of items in train is:
11
The loss for epoch 1
1.729713347825137
The running loss is:
9.341200038790703
The number of items in train is:
11
The loss for epoch 2
0.8492000035264275
The running loss is:
8.422987721860409
The number of items in train is:
11
The loss for epoch 3
0.7657261565327644
The running loss is:
6.793850138783455
The number of items in train is:
11
The loss for epoch 4
0.617622739889405
The running loss is:
6.612731076776981
The number of items in train is:
11
The loss for epoch 5
0.6011573706160892
The running loss is:
6.01167730987072
The number of items in train is:
11
The loss for epoch 6
0.5465161190791563
The running loss is:
5.346388012170792
The number of items in train is:
11
The loss for epoch 7
0.4860352738337083
The running loss is:
5.20254971832037
The number of items in train is:
11
The loss for epoch 8
0.4729590653018518
The running loss is:
4.780299365520477
The number of items in train is:
11
The loss for epoch 9
0.4345726695927707
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.457406
48 30755 ... 5.955339
49 30756 ... 9.385489
50 30757 ... 12.424001
51 30758 ... 10.319823
52 30759 ... 4.360053
53 30760 ... 3.441776
54 30761 ... 3.458094
55 30762 ... 2.626965
56 30763 ... 2.748477
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bv5gfbfq wandb: Agent Starting Run: 4ui25iwt with config: batch_size: 3 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 4ui25iwt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.894896239042282
The number of items in train is:
11
The loss for epoch 0
0.9904451126402075
The running loss is:
24.960272923111916
The number of items in train is:
11
The loss for epoch 1
2.2691157202829015
The running loss is:
14.597070783376694
The number of items in train is:
11
The loss for epoch 2
1.3270064348524266
The running loss is:
10.560084193944931
The number of items in train is:
11
The loss for epoch 3
0.9600076539949938
The running loss is:
8.262078568339348
The number of items in train is:
11
The loss for epoch 4
0.7510980516672134
The running loss is:
7.327546648681164
The number of items in train is:
11
The loss for epoch 5
0.6661406044255603
The running loss is:
7.109338231384754
The number of items in train is:
11
The loss for epoch 6
0.6463034755804322
The running loss is:
6.8406630009412766
The number of items in train is:
11
The loss for epoch 7
0.6218784546310251
The running loss is:
6.650714844465256
The number of items in train is:
11
The loss for epoch 8
0.6046104404059324
The running loss is:
6.704959943890572
The number of items in train is:
11
The loss for epoch 9
0.609541813080961
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.342838
48 30755 ... 9.787096
49 30756 ... 10.617628
50 30757 ... 11.319128
51 30758 ... 11.079123
52 30759 ... 9.366017
53 30760 ... 7.191575
54 30761 ... 7.245820
55 30762 ... 7.157641
56 30763 ... 6.621591
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4ui25iwt wandb: Agent Starting Run: efkau42q with config: batch_size: 3 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: efkau42q
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.304110929369926
The number of items in train is:
12
The loss for epoch 0
1.2753425774474938
The running loss is:
19.57400969415903
The number of items in train is:
12
The loss for epoch 1
1.6311674745132525
The running loss is:
21.51656384766102
The number of items in train is:
12
The loss for epoch 2
1.793046987305085
The running loss is:
8.785913735628128
The number of items in train is:
12
The loss for epoch 3
0.7321594779690107
The running loss is:
9.513798125088215
The number of items in train is:
12
The loss for epoch 4
0.7928165104240179
The running loss is:
9.432423368096352
The number of items in train is:
12
The loss for epoch 5
0.786035280674696
The running loss is:
7.66383171826601
The number of items in train is:
12
The loss for epoch 6
0.6386526431888342
The running loss is:
7.818079452961683
The number of items in train is:
12
The loss for epoch 7
0.6515066210801402
The running loss is:
6.671020977199078
The number of items in train is:
12
The loss for epoch 8
0.5559184147665898
The running loss is:
6.739705860614777
The number of items in train is:
12
The loss for epoch 9
0.5616421550512314
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.775640
48 30755 ... 12.652183
49 30756 ... 15.949203
50 30757 ... 17.717743
51 30758 ... 16.192871
52 30759 ... 12.983944
53 30760 ... 12.847769
54 30761 ... 15.049444
55 30762 ... 13.526834
56 30763 ... 14.984063
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: efkau42q wandb: Agent Starting Run: yxy354fp with config: batch_size: 3 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: yxy354fp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.336272045969963
The number of items in train is:
11
The loss for epoch 0
0.9396610950881784
The running loss is:
18.13731163740158
The number of items in train is:
11
The loss for epoch 1
1.6488465124910527
The running loss is:
13.977685883641243
The number of items in train is:
11
The loss for epoch 2
1.2706987166946584
The running loss is:
9.119788710027933
The number of items in train is:
11
The loss for epoch 3
0.8290717009116303
The running loss is:
8.845211759209633
The number of items in train is:
11
The loss for epoch 4
0.8041101599281485
The running loss is:
7.916596710681915
The number of items in train is:
11
The loss for epoch 5
0.7196906100619923
The running loss is:
7.592547062784433
The number of items in train is:
11
The loss for epoch 6
0.6902315511622212
The running loss is:
6.01723700016737
The number of items in train is:
11
The loss for epoch 7
0.5470215454697609
The running loss is:
6.154241532087326
The number of items in train is:
11
The loss for epoch 8
0.5594765029170297
The running loss is:
6.210500963032246
The number of items in train is:
11
The loss for epoch 9
0.564590996639295
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.814771
48 30755 ... 12.536692
49 30756 ... 13.175877
50 30757 ... 12.439815
51 30758 ... 13.010987
52 30759 ... 12.134022
53 30760 ... 11.068122
54 30761 ... 12.273049
55 30762 ... 9.667723
56 30763 ... 8.891700
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yxy354fp wandb: Agent Starting Run: x068md6t with config: batch_size: 3 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: x068md6t
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.163715958595276
The number of items in train is:
11
The loss for epoch 0
1.742155996235934
The running loss is:
15.844000786542892
The number of items in train is:
11
The loss for epoch 1
1.4403637078675358
The running loss is:
27.519839078187943
The number of items in train is:
11
The loss for epoch 2
2.5018035525625404
The running loss is:
10.582634881138802
The number of items in train is:
11
The loss for epoch 3
0.9620577164671638
The running loss is:
11.661602854728699
The number of items in train is:
11
The loss for epoch 4
1.0601457140662454
The running loss is:
7.782229453325272
The number of items in train is:
11
The loss for epoch 5
0.707475404847752
The running loss is:
7.696709528565407
The number of items in train is:
11
The loss for epoch 6
0.6997008662332188
The running loss is:
7.128703862428665
The number of items in train is:
11
The loss for epoch 7
0.648063987493515
The running loss is:
6.206833004951477
The number of items in train is:
11
The loss for epoch 8
0.5642575459046797
The running loss is:
6.452411137521267
The number of items in train is:
11
The loss for epoch 9
0.5865828306837515
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.637244
48 30755 ... 10.699240
49 30756 ... 11.454589
50 30757 ... 11.937562
51 30758 ... 11.151837
52 30759 ... 8.948048
53 30760 ... 7.030075
54 30761 ... 7.186663
55 30762 ... 6.990386
56 30763 ... 6.843461
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: x068md6t wandb: Agent Starting Run: ya3scy4m with config: batch_size: 3 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ya3scy4m
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
88.53303991630673
The number of items in train is:
12
The loss for epoch 0
7.377753326358895
The running loss is:
15.117607243359089
The number of items in train is:
12
The loss for epoch 1
1.2598006036132574
The running loss is:
21.78238356113434
The number of items in train is:
12
The loss for epoch 2
1.8151986300945282
The running loss is:
9.938564524054527
The number of items in train is:
12
The loss for epoch 3
0.8282137103378773
The running loss is:
13.54171159863472
The number of items in train is:
12
The loss for epoch 4
1.1284759665528934
The running loss is:
11.289286583662033
The number of items in train is:
12
The loss for epoch 5
0.9407738819718361
The running loss is:
10.076805599033833
The number of items in train is:
12
The loss for epoch 6
0.839733799919486
The running loss is:
9.40070765465498
The number of items in train is:
12
The loss for epoch 7
0.7833923045545816
The running loss is:
9.233762472867966
The number of items in train is:
12
The loss for epoch 8
0.7694802060723305
The running loss is:
7.18392214179039
The number of items in train is:
12
The loss for epoch 9
0.5986601784825325
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 18.421427
48 30755 ... 11.026144
49 30756 ... 8.737643
50 30757 ... 17.112108
51 30758 ... 16.133114
52 30759 ... 14.757212
53 30760 ... 12.639726
54 30761 ... 13.369624
55 30762 ... 12.039531
56 30763 ... 11.453431
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ya3scy4m wandb: Agent Starting Run: fp8m3p5p with config: batch_size: 3 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fp8m3p5p
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
56.73506325483322
The number of items in train is:
11
The loss for epoch 0
5.1577330231666565
The running loss is:
14.081439599394798
The number of items in train is:
11
The loss for epoch 1
1.2801308726722544
The running loss is:
11.768588274717331
The number of items in train is:
11
The loss for epoch 2
1.069871661337939
The running loss is:
11.529130071401596
The number of items in train is:
11
The loss for epoch 3
1.0481027337637814
The running loss is:
8.909016866236925
The number of items in train is:
11
The loss for epoch 4
0.8099106242033568
The running loss is:
8.021973967552185
The number of items in train is:
11
The loss for epoch 5
0.7292703606865623
The running loss is:
7.132795467972755
The number of items in train is:
11
The loss for epoch 6
0.6484359516338869
The running loss is:
6.869528941810131
The number of items in train is:
11
The loss for epoch 7
0.6245026310736482
The running loss is:
7.365066081285477
The number of items in train is:
11
The loss for epoch 8
0.6695514619350433
The running loss is:
7.568959094583988
The number of items in train is:
11
The loss for epoch 9
0.6880871904167262
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.777973
48 30755 ... 10.313013
49 30756 ... 10.664633
50 30757 ... 11.374364
51 30758 ... 11.230084
52 30759 ... 11.073467
53 30760 ... 10.215710
54 30761 ... 10.222840
55 30762 ... 10.195326
56 30763 ... 10.036734
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fp8m3p5p wandb: Agent Starting Run: nl9f3zyh with config: batch_size: 3 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: nl9f3zyh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
119.16718634963036
The number of items in train is:
11
The loss for epoch 0
10.833380577239124
The running loss is:
14.289708197116852
The number of items in train is:
11
The loss for epoch 1
1.2990643815560774
The running loss is:
13.934945285320282
The number of items in train is:
11
The loss for epoch 2
1.2668132077563892
The running loss is:
16.21449938416481
The number of items in train is:
11
The loss for epoch 3
1.4740453985604374
The running loss is:
16.993614554405212
The number of items in train is:
11
The loss for epoch 4
1.5448740504004739
The running loss is:
14.635781586170197
The number of items in train is:
11
The loss for epoch 5
1.3305255987427451
The running loss is:
11.63321104645729
The number of items in train is:
11
The loss for epoch 6
1.0575646405870265
The running loss is:
8.882433205842972
The number of items in train is:
11
The loss for epoch 7
0.8074939278039065
The running loss is:
7.281253471970558
The number of items in train is:
11
The loss for epoch 8
0.6619321338155053
The running loss is:
7.735475331544876
The number of items in train is:
11
The loss for epoch 9
0.7032250301404432
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.217269
48 30755 ... 8.253767
49 30756 ... 8.526093
50 30757 ... 8.519957
51 30758 ... 8.564201
52 30759 ... 8.558195
53 30760 ... 8.048856
54 30761 ... 7.787209
55 30762 ... 7.811332
56 30763 ... 6.481368
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nl9f3zyh wandb: Agent Starting Run: egq37mix with config: batch_size: 3 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: egq37mix
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.937215354293585
The number of items in train is:
11
The loss for epoch 0
1.267019577663053
The running loss is:
12.927820309996605
The number of items in train is:
11
The loss for epoch 1
1.1752563918178731
The running loss is:
7.380629554390907
The number of items in train is:
11
The loss for epoch 2
0.6709663231264461
The running loss is:
7.143720369786024
The number of items in train is:
11
The loss for epoch 3
0.6494291245260022
The running loss is:
6.624908953905106
The number of items in train is:
11
The loss for epoch 4
0.6022644503550096
The running loss is:
6.404768772423267
The number of items in train is:
11
The loss for epoch 5
0.5822517065839334
The running loss is:
6.25363489612937
The number of items in train is:
11
The loss for epoch 6
0.5685122632844881
The running loss is:
5.978661727160215
The number of items in train is:
11
The loss for epoch 7
0.5435147024691105
The running loss is:
5.826105419546366
The number of items in train is:
11
The loss for epoch 8
0.5296459472314878
The running loss is:
5.398386839777231
The number of items in train is:
11
The loss for epoch 9
0.4907624399797483
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.602220
48 30755 ... 7.674791
49 30756 ... 9.680432
50 30757 ... 9.432722
51 30758 ... 8.631081
52 30759 ... 8.656858
53 30760 ... 7.497314
54 30761 ... 3.186903
55 30762 ... 3.427803
56 30763 ... 3.806885
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: egq37mix wandb: Agent Starting Run: 055yta4y with config: batch_size: 3 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 055yta4y
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.16464938223362
The number of items in train is:
11
The loss for epoch 0
1.1967863074757836
The running loss is:
14.236513704061508
The number of items in train is:
11
The loss for epoch 1
1.2942285185510463
The running loss is:
7.635823279619217
The number of items in train is:
11
The loss for epoch 2
0.6941657526926561
The running loss is:
6.894759684801102
The number of items in train is:
11
The loss for epoch 3
0.6267963349819183
The running loss is:
6.464241176843643
The number of items in train is:
11
The loss for epoch 4
0.5876582888039675
The running loss is:
6.639204442501068
The number of items in train is:
11
The loss for epoch 5
0.6035640402273699
The running loss is:
6.4581106305122375
The number of items in train is:
11
The loss for epoch 6
0.5871009664102034
The running loss is:
5.75249408185482
The number of items in train is:
11
The loss for epoch 7
0.5229540074413473
The running loss is:
6.132444128394127
The number of items in train is:
11
The loss for epoch 8
0.5574949207631025
The running loss is:
5.399658687412739
The number of items in train is:
11
The loss for epoch 9
0.49087806249206717
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.781346
48 30755 ... 6.443140
49 30756 ... 8.097566
50 30757 ... 7.652623
51 30758 ... 6.561896
52 30759 ... 6.862144
53 30760 ... 6.056333
54 30761 ... 1.668644
55 30762 ... 1.731342
56 30763 ... 1.537274
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 055yta4y wandb: Agent Starting Run: iybnn54g with config: batch_size: 3 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: iybnn54g
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.125202730298042
The number of items in train is:
11
The loss for epoch 0
1.193200248208913
The running loss is:
12.032076135277748
The number of items in train is:
11
The loss for epoch 1
1.093825103207068
The running loss is:
7.3690506517887115
The number of items in train is:
11
The loss for epoch 2
0.6699136956171556
The running loss is:
6.6424713134765625
The number of items in train is:
11
The loss for epoch 3
0.6038610284978693
The running loss is:
6.352311864495277
The number of items in train is:
11
The loss for epoch 4
0.5774828967722979
The running loss is:
6.089945591986179
The number of items in train is:
11
The loss for epoch 5
0.553631417453289
The running loss is:
6.11835578083992
The number of items in train is:
11
The loss for epoch 6
0.5562141618945382
The running loss is:
6.080555185675621
The number of items in train is:
11
The loss for epoch 7
0.5527777441523292
The running loss is:
5.575134560465813
The number of items in train is:
11
The loss for epoch 8
0.5068304145878012
The running loss is:
5.911937691271305
The number of items in train is:
11
The loss for epoch 9
0.5374488810246641
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.100501
48 30755 ... 6.447453
49 30756 ... 5.319932
50 30757 ... 5.754395
51 30758 ... 5.810476
52 30759 ... 5.998308
53 30760 ... 5.530815
54 30761 ... 0.845803
55 30762 ... 0.897836
56 30763 ... 0.437532
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: iybnn54g wandb: Agent Starting Run: 0c5rtc4t with config: batch_size: 3 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0c5rtc4t
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.56395823508501
The number of items in train is:
11
The loss for epoch 0
1.0512689304622738
The running loss is:
21.39585980027914
The number of items in train is:
11
The loss for epoch 1
1.94507816366174
The running loss is:
9.437215507030487
The number of items in train is:
11
The loss for epoch 2
0.857928682457317
The running loss is:
8.832013815641403
The number of items in train is:
11
The loss for epoch 3
0.8029103468764912
The running loss is:
7.06958132237196
The number of items in train is:
11
The loss for epoch 4
0.6426892111247237
The running loss is:
6.77753984183073
The number of items in train is:
11
The loss for epoch 5
0.6161399856209755
The running loss is:
6.557316467165947
The number of items in train is:
11
The loss for epoch 6
0.5961196788332679
The running loss is:
6.02478714287281
The number of items in train is:
11
The loss for epoch 7
0.5477079220793464
The running loss is:
5.408392807468772
The number of items in train is:
11
The loss for epoch 8
0.491672073406252
The running loss is:
4.902979908511043
The number of items in train is:
11
The loss for epoch 9
0.4457254462282766
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.421265
48 30755 ... 7.484463
49 30756 ... 9.594088
50 30757 ... 9.243134
51 30758 ... 7.143751
52 30759 ... 8.632397
53 30760 ... 9.842757
54 30761 ... 5.808178
55 30762 ... 5.270340
56 30763 ... 5.360891
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0c5rtc4t wandb: Agent Starting Run: dmof87c1 with config: batch_size: 3 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: dmof87c1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.552351400256157
The number of items in train is:
11
The loss for epoch 0
1.0502137636596507
The running loss is:
22.925799906253815
The number of items in train is:
11
The loss for epoch 1
2.084163627841256
The running loss is:
10.040516801178455
The number of items in train is:
11
The loss for epoch 2
0.9127742546525869
The running loss is:
8.72734984010458
The number of items in train is:
11
The loss for epoch 3
0.7933954400095072
The running loss is:
7.016648806631565
The number of items in train is:
11
The loss for epoch 4
0.6378771642392332
The running loss is:
7.162662923336029
The number of items in train is:
11
The loss for epoch 5
0.6511511748487299
The running loss is:
6.340226337313652
The number of items in train is:
11
The loss for epoch 6
0.5763842124830593
The running loss is:
6.102388359606266
The number of items in train is:
11
The loss for epoch 7
0.5547625781460241
The running loss is:
6.945028610527515
The number of items in train is:
11
The loss for epoch 8
0.6313662373206832
The running loss is:
6.08937419205904
The number of items in train is:
11
The loss for epoch 9
0.5535794720053673
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.671848
48 30755 ... 9.396304
49 30756 ... 9.288265
50 30757 ... 9.899469
51 30758 ... 9.928300
52 30759 ... 10.266774
53 30760 ... 9.928045
54 30761 ... 7.802100
55 30762 ... 8.361746
56 30763 ... 8.434018
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: dmof87c1 wandb: Agent Starting Run: a607o3ai with config: batch_size: 3 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: a607o3ai
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.085680603981018
The number of items in train is:
11
The loss for epoch 0
1.0077891458164563
The running loss is:
20.121261298656464
The number of items in train is:
11
The loss for epoch 1
1.829205572605133
The running loss is:
9.134558081626892
The number of items in train is:
11
The loss for epoch 2
0.8304143710569902
The running loss is:
8.571861386299133
The number of items in train is:
11
The loss for epoch 3
0.779260126027194
The running loss is:
7.1886313408613205
The number of items in train is:
11
The loss for epoch 4
0.6535119400783018
The running loss is:
6.905544355511665
The number of items in train is:
11
The loss for epoch 5
0.6277767595919695
The running loss is:
6.2731651067733765
The number of items in train is:
11
The loss for epoch 6
0.5702877369793978
The running loss is:
6.410836488008499
The number of items in train is:
11
The loss for epoch 7
0.5828033170916818
The running loss is:
5.631247833371162
The number of items in train is:
11
The loss for epoch 8
0.5119316212155602
The running loss is:
5.932000920176506
The number of items in train is:
11
The loss for epoch 9
0.5392728109251369
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.579858
48 30755 ... 7.775860
49 30756 ... 6.056839
50 30757 ... 7.616488
51 30758 ... 7.260682
52 30759 ... 7.825396
53 30760 ... 6.902719
54 30761 ... 3.999594
55 30762 ... 3.916414
56 30763 ... 4.020979
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: a607o3ai wandb: Agent Starting Run: s2l615c4 with config: batch_size: 3 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: s2l615c4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.919737175107002
The number of items in train is:
11
The loss for epoch 0
1.2654306522824548
The running loss is:
14.05555833876133
The number of items in train is:
11
The loss for epoch 1
1.2777780307964846
The running loss is:
15.306061759591103
The number of items in train is:
11
The loss for epoch 2
1.3914601599628276
The running loss is:
8.069633159786463
The number of items in train is:
11
The loss for epoch 3
0.733603014526042
The running loss is:
8.077630437910557
The number of items in train is:
11
The loss for epoch 4
0.7343300398100506
The running loss is:
7.786269728094339
The number of items in train is:
11
The loss for epoch 5
0.7078427025540308
The running loss is:
7.286909453570843
The number of items in train is:
11
The loss for epoch 6
0.6624463139609857
The running loss is:
6.560916505753994
The number of items in train is:
11
The loss for epoch 7
0.596446955068545
The running loss is:
6.199817832559347
The number of items in train is:
11
The loss for epoch 8
0.5636198029599406
The running loss is:
6.044604599475861
The number of items in train is:
11
The loss for epoch 9
0.54950950904326
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.586776
48 30755 ... 8.372278
49 30756 ... 10.883894
50 30757 ... 11.080786
51 30758 ... 7.882761
52 30759 ... 10.142594
53 30760 ... 11.976085
54 30761 ... 6.001824
55 30762 ... 5.632422
56 30763 ... 5.912739
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: s2l615c4 wandb: Agent Starting Run: 684gik0b with config: batch_size: 3 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 684gik0b
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.285382837057114
The number of items in train is:
11
The loss for epoch 0
1.2986711670051923
The running loss is:
15.524043463170528
The number of items in train is:
11
The loss for epoch 1
1.4112766784700481
The running loss is:
25.67881280183792
The number of items in train is:
11
The loss for epoch 2
2.334437527439811
The running loss is:
9.272457085549831
The number of items in train is:
11
The loss for epoch 3
0.8429506441408937
The running loss is:
8.30488908290863
The number of items in train is:
11
The loss for epoch 4
0.7549899166280573
The running loss is:
7.985045664012432
The number of items in train is:
11
The loss for epoch 5
0.7259132421829484
The running loss is:
7.957685396075249
The number of items in train is:
11
The loss for epoch 6
0.7234259450977499
The running loss is:
8.26042753458023
The number of items in train is:
11
The loss for epoch 7
0.7509479576891119
The running loss is:
8.252448678016663
The number of items in train is:
11
The loss for epoch 8
0.7502226070924238
The running loss is:
5.690807230770588
The number of items in train is:
11
The loss for epoch 9
0.5173461118882353
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.783648
48 30755 ... 10.360521
49 30756 ... 5.586550
50 30757 ... 10.668744
51 30758 ... 8.042665
52 30759 ... 13.113797
53 30760 ... 9.734967
54 30761 ... 9.209267
55 30762 ... 7.848692
56 30763 ... 10.805669
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 684gik0b wandb: Agent Starting Run: e8tpi7lb with config: batch_size: 3 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: e8tpi7lb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.106163665652275
The number of items in train is:
11
The loss for epoch 0
1.100560333241116
The running loss is:
15.11037127673626
The number of items in train is:
11
The loss for epoch 1
1.3736701160669327
The running loss is:
18.565093740820885
The number of items in train is:
11
The loss for epoch 2
1.6877357946200804
The running loss is:
8.801799945533276
The number of items in train is:
11
The loss for epoch 3
0.800163631412116
The running loss is:
8.399221360683441
The number of items in train is:
11
The loss for epoch 4
0.7635655782439492
The running loss is:
8.407545536756516
The number of items in train is:
11
The loss for epoch 5
0.7643223215233196
The running loss is:
6.584027715027332
The number of items in train is:
11
The loss for epoch 6
0.5985479740933939
The running loss is:
7.207642734050751
The number of items in train is:
11
The loss for epoch 7
0.6552402485500682
The running loss is:
6.850147262215614
The number of items in train is:
11
The loss for epoch 8
0.6227406602014195
The running loss is:
7.071139693260193
The number of items in train is:
11
The loss for epoch 9
0.642830881205472
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.616160
48 30755 ... 9.827299
49 30756 ... 3.027868
50 30757 ... 8.111265
51 30758 ... 10.138385
52 30759 ... 10.469387
53 30760 ... 8.697634
54 30761 ... 7.158179
55 30762 ... 7.428538
56 30763 ... 8.332012
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: e8tpi7lb wandb: Agent Starting Run: d3o40cfk with config: batch_size: 3 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: d3o40cfk
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
90.30369505286217
The number of items in train is:
11
The loss for epoch 0
8.209426822987469
The running loss is:
15.560469098389149
The number of items in train is:
11
The loss for epoch 1
1.414588099853559
The running loss is:
20.279406629502773
The number of items in train is:
11
The loss for epoch 2
1.8435824208638885
The running loss is:
13.721642754971981
The number of items in train is:
11
The loss for epoch 3
1.2474220686338164
The running loss is:
9.624975465238094
The number of items in train is:
11
The loss for epoch 4
0.8749977695670995
The running loss is:
9.650864725932479
The number of items in train is:
11
The loss for epoch 5
0.8773513387211345
The running loss is:
9.389308098703623
The number of items in train is:
11
The loss for epoch 6
0.8535734635185112
The running loss is:
8.569266445934772
The number of items in train is:
11
The loss for epoch 7
0.7790242223577066
The running loss is:
7.809198591858149
The number of items in train is:
11
The loss for epoch 8
0.7099271447143771
The running loss is:
9.43609918653965
The number of items in train is:
11
The loss for epoch 9
0.8578271987763318
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.029284
48 30755 ... 11.026073
49 30756 ... 11.041766
50 30757 ... 12.278847
51 30758 ... 12.294883
52 30759 ... 12.624520
53 30760 ... 13.053844
54 30761 ... 12.575034
55 30762 ... 12.675170
56 30763 ... 12.601731
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: d3o40cfk wandb: Agent Starting Run: fc1ir6hp with config: batch_size: 3 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fc1ir6hp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
84.87001064419746
The number of items in train is:
11
The loss for epoch 0
7.715455513108861
The running loss is:
11.632207192480564
The number of items in train is:
11
The loss for epoch 1
1.0574733811345967
The running loss is:
20.81926593184471
The number of items in train is:
11
The loss for epoch 2
1.8926605392586102
The running loss is:
9.084724470973015
The number of items in train is:
11
The loss for epoch 3
0.8258840428157286
The running loss is:
10.560272850096226
The number of items in train is:
11
The loss for epoch 4
0.9600248045542024
The running loss is:
10.19235224276781
The number of items in train is:
11
The loss for epoch 5
0.9265774766152556
The running loss is:
9.287791468203068
The number of items in train is:
11
The loss for epoch 6
0.8443446789275516
The running loss is:
7.80347640812397
The number of items in train is:
11
The loss for epoch 7
0.7094069461930882
The running loss is:
9.036721609532833
The number of items in train is:
11
The loss for epoch 8
0.8215201463211667
The running loss is:
8.998482886701822
The number of items in train is:
11
The loss for epoch 9
0.8180438987910748
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.811060
48 30755 ... 11.055724
49 30756 ... 7.466121
50 30757 ... 7.228861
51 30758 ... 12.189958
52 30759 ... 11.982655
53 30760 ... 10.075672
54 30761 ... 8.466732
55 30762 ... 9.425452
56 30763 ... 11.071779
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fc1ir6hp wandb: Agent Starting Run: f1mlp38o with config: batch_size: 3 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: f1mlp38o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
67.69290640950203
The number of items in train is:
11
The loss for epoch 0
6.153900582682002
The running loss is:
9.668513655662537
The number of items in train is:
11
The loss for epoch 1
0.8789557868784125
The running loss is:
9.981049299240112
The number of items in train is:
11
The loss for epoch 2
0.9073681181127374
The running loss is:
10.219359934329987
The number of items in train is:
11
The loss for epoch 3
0.9290327213027261
The running loss is:
11.357643961906433
The number of items in train is:
11
The loss for epoch 4
1.0325130874460393
The running loss is:
8.35865232348442
The number of items in train is:
11
The loss for epoch 5
0.7598774839531292
The running loss is:
7.621890068054199
The number of items in train is:
11
The loss for epoch 6
0.6928990970958363
The running loss is:
8.405842632055283
The number of items in train is:
11
The loss for epoch 7
0.7641675120050256
The running loss is:
7.759170785546303
The number of items in train is:
11
The loss for epoch 8
0.7053791623223912
The running loss is:
7.550814151763916
The number of items in train is:
11
The loss for epoch 9
0.686437650160356
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.754035
48 30755 ... 6.363925
49 30756 ... 6.710924
50 30757 ... 8.356108
51 30758 ... 8.733762
52 30759 ... 7.781654
53 30760 ... 7.346811
54 30761 ... 5.208549
55 30762 ... 5.471954
56 30763 ... 5.261775
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f1mlp38o wandb: Agent Starting Run: waidlena with config: batch_size: 4 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: waidlena
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.497929081320763
The number of items in train is:
11
The loss for epoch 0
1.227084461938251
The running loss is:
8.768787369132042
The number of items in train is:
11
The loss for epoch 1
0.7971624881029129
The running loss is:
8.496358714997768
The number of items in train is:
11
The loss for epoch 2
0.7723962468179789
The running loss is:
7.1095104441046715
The number of items in train is:
11
The loss for epoch 3
0.6463191312822428
The running loss is:
8.59556758403778
The number of items in train is:
11
The loss for epoch 4
0.7814152349125255
The running loss is:
7.4800353944301605
The number of items in train is:
11
The loss for epoch 5
0.6800032176754691
The running loss is:
7.584153085947037
The number of items in train is:
11
The loss for epoch 6
0.6894684623588215
The running loss is:
8.128714382648468
The number of items in train is:
11
The loss for epoch 7
0.7389740347862244
The running loss is:
8.35108682513237
The number of items in train is:
11
The loss for epoch 8
0.75918971137567
The running loss is:
8.158496677875519
The number of items in train is:
11
The loss for epoch 9
0.7416815161705017
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 12.112806
48 30755 ... 11.882335
49 30756 ... 11.945765
50 30757 ... 12.140722
51 30758 ... 12.394543
52 30759 ... 12.674706
53 30760 ... 12.966658
54 30761 ... 12.097885
55 30762 ... 11.875657
56 30763 ... 11.942776
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: waidlena wandb: Agent Starting Run: qjfpgo60 with config: batch_size: 4 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: qjfpgo60
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.39041042327881
The number of items in train is:
11
The loss for epoch 0
1.7627645839344372
The running loss is:
14.094916045665741
The number of items in train is:
11
The loss for epoch 1
1.281356004151431
The running loss is:
13.58062994480133
The number of items in train is:
11
The loss for epoch 2
1.2346027222546665
The running loss is:
13.59209805727005
The number of items in train is:
11
The loss for epoch 3
1.2356452779336409
The running loss is:
13.201426059007645
The number of items in train is:
11
The loss for epoch 4
1.2001296417279677
The running loss is:
12.879163593053818
The number of items in train is:
11
The loss for epoch 5
1.1708330539139835
The running loss is:
12.814834147691727
The number of items in train is:
11
The loss for epoch 6
1.1649849225174298
The running loss is:
12.698356926441193
The number of items in train is:
11
The loss for epoch 7
1.1543960842219265
The running loss is:
12.411805510520935
The number of items in train is:
11
The loss for epoch 8
1.128345955501903
The running loss is:
12.614239037036896
The number of items in train is:
11
The loss for epoch 9
1.1467490033669905
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 17.735096
48 30755 ... 21.072258
49 30756 ... 23.510662
50 30757 ... 25.371246
51 30758 ... 26.860338
52 30759 ... 28.110594
53 30760 ... 29.207296
54 30761 ... 28.155012
55 30762 ... 27.771378
56 30763 ... 27.817627
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qjfpgo60 wandb: Agent Starting Run: szcbpw5m with config: batch_size: 4 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: szcbpw5m
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.532336503267288
The number of items in train is:
10
The loss for epoch 0
1.6532336503267289
The running loss is:
11.091062128543854
The number of items in train is:
10
The loss for epoch 1
1.1091062128543854
The running loss is:
10.856420874595642
The number of items in train is:
10
The loss for epoch 2
1.0856420874595643
The running loss is:
10.523346066474915
The number of items in train is:
10
The loss for epoch 3
1.0523346066474915
The running loss is:
10.397574484348297
The number of items in train is:
10
The loss for epoch 4
1.0397574484348298
The running loss is:
10.013593643903732
The number of items in train is:
10
The loss for epoch 5
1.0013593643903733
The running loss is:
9.911922216415405
The number of items in train is:
10
The loss for epoch 6
0.9911922216415405
The running loss is:
10.10109493136406
The number of items in train is:
10
The loss for epoch 7
1.0101094931364059
The running loss is:
9.99822461605072
The number of items in train is:
10
The loss for epoch 8
0.999822461605072
The running loss is:
10.047543227672577
The number of items in train is:
10
The loss for epoch 9
1.0047543227672577
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 7.451673
48 30755 ... 4.557664
49 30756 ... 2.783484
50 30757 ... 1.481748
51 30758 ... 0.379330
52 30759 ... -0.638998
53 30760 ... -1.621848
54 30761 ... 1.282873
55 30762 ... 1.955114
56 30763 ... 1.685496
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: szcbpw5m wandb: Agent Starting Run: fqtu6656 with config: batch_size: 4 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fqtu6656
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.279194861650467
The number of items in train is:
11
The loss for epoch 0
1.1162904419682242
The running loss is:
16.839398562908173
The number of items in train is:
11
The loss for epoch 1
1.530854414809834
The running loss is:
8.657114937901497
The number of items in train is:
11
The loss for epoch 2
0.787010448900136
The running loss is:
8.566754624247551
The number of items in train is:
11
The loss for epoch 3
0.7787958749315955
The running loss is:
8.194050922989845
The number of items in train is:
11
The loss for epoch 4
0.7449137202718041
The running loss is:
7.402128949761391
The number of items in train is:
11
The loss for epoch 5
0.6729208136146719
The running loss is:
7.638427227735519
The number of items in train is:
11
The loss for epoch 6
0.6944024752486836
The running loss is:
7.960539147257805
The number of items in train is:
11
The loss for epoch 7
0.7236853770234368
The running loss is:
8.493246629834175
The number of items in train is:
11
The loss for epoch 8
0.772113329984925
The running loss is:
7.924744144082069
The number of items in train is:
11
The loss for epoch 9
0.7204312858256426
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.971193
48 30755 ... 11.706475
49 30756 ... 11.781940
50 30757 ... 12.008855
51 30758 ... 12.303199
52 30759 ... 12.627563
53 30760 ... 12.965292
54 30761 ... 11.955740
55 30762 ... 11.699595
56 30763 ... 11.778876
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fqtu6656 wandb: Agent Starting Run: 44l5rduh with config: batch_size: 4 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 44l5rduh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.85647228360176
The number of items in train is:
11
The loss for epoch 0
1.7142247530547055
The running loss is:
20.30205523967743
The number of items in train is:
11
The loss for epoch 1
1.845641385425221
The running loss is:
13.520971089601517
The number of items in train is:
11
The loss for epoch 2
1.2291791899637743
The running loss is:
13.447545528411865
The number of items in train is:
11
The loss for epoch 3
1.2225041389465332
The running loss is:
12.76877212524414
The number of items in train is:
11
The loss for epoch 4
1.1607974659312854
The running loss is:
12.522136121988297
The number of items in train is:
11
The loss for epoch 5
1.138376011089845
The running loss is:
12.232091456651688
The number of items in train is:
11
The loss for epoch 6
1.1120083142410626
The running loss is:
12.113570183515549
The number of items in train is:
11
The loss for epoch 7
1.101233653046868
The running loss is:
11.928546637296677
The number of items in train is:
11
The loss for epoch 8
1.0844133306633343
The running loss is:
11.618478044867516
The number of items in train is:
11
The loss for epoch 9
1.0562252768061378
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 16.801399
48 30755 ... 19.427036
49 30756 ... 21.332169
50 30757 ... 22.795780
51 30758 ... 23.988827
52 30759 ... 25.016071
53 30760 ... 25.941715
54 30761 ... 24.732052
55 30762 ... 24.286921
56 30763 ... 24.310295
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 44l5rduh wandb: Agent Starting Run: euxxg89q with config: batch_size: 4 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: euxxg89q
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.137496054172516
The number of items in train is:
10
The loss for epoch 0
1.5137496054172517
The running loss is:
19.171320110559464
The number of items in train is:
10
The loss for epoch 1
1.9171320110559464
The running loss is:
10.694960564374924
The number of items in train is:
10
The loss for epoch 2
1.0694960564374925
The running loss is:
10.60001027584076
The number of items in train is:
10
The loss for epoch 3
1.0600010275840759
The running loss is:
10.514416992664337
The number of items in train is:
10
The loss for epoch 4
1.0514416992664337
The running loss is:
9.992541253566742
The number of items in train is:
10
The loss for epoch 5
0.9992541253566742
The running loss is:
10.011631518602371
The number of items in train is:
10
The loss for epoch 6
1.001163151860237
The running loss is:
9.713776409626007
The number of items in train is:
10
The loss for epoch 7
0.9713776409626007
The running loss is:
9.765309482812881
The number of items in train is:
10
The loss for epoch 8
0.9765309482812882
The running loss is:
9.576499074697495
The number of items in train is:
10
The loss for epoch 9
0.9576499074697494
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 7.637028
48 30755 ... 5.024141
49 30756 ... 3.497705
50 30757 ... 2.400480
51 30758 ... 1.472821
52 30759 ... 0.612151
53 30760 ... -0.222054
54 30761 ... 2.413519
55 30762 ... 2.960541
56 30763 ... 2.682458
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: euxxg89q wandb: Agent Starting Run: 1bqhr29t with config: batch_size: 4 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1bqhr29t
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.885171070694923
The number of items in train is:
11
The loss for epoch 0
0.9895610064268112
The running loss is:
22.15847496688366
The number of items in train is:
11
The loss for epoch 1
2.0144068151712418
The running loss is:
15.519859187304974
The number of items in train is:
11
The loss for epoch 2
1.4108962897549977
The running loss is:
9.152763716876507
11
The number of items in train is:
The loss for epoch 3
0.8320694288069551
The running loss is:
8.221307665109634
The number of items in train is:
11
The loss for epoch 4
0.7473916059190576
The running loss is:
8.884836662560701
The number of items in train is:
11
The loss for epoch 5
0.8077124238691546
The running loss is:
8.030499786138535
The number of items in train is:
11
The loss for epoch 6
0.7300454351035032
The running loss is:
8.168342098593712
The number of items in train is:
11
The loss for epoch 7
0.7425765544176102
The running loss is:
8.518066614866257
The number of items in train is:
11
The loss for epoch 8
0.7743696922605688
The running loss is:
8.19113241136074
The number of items in train is:
11
The loss for epoch 9
0.7446484010327946
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.825364
48 30755 ... 11.594109
49 30756 ... 11.774220
50 30757 ... 12.133711
51 30758 ... 12.571421
52 30759 ... 13.043240
53 30760 ... 13.529931
54 30761 ... 12.056443
55 30762 ... 11.694873
56 30763 ... 11.818159
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1bqhr29t wandb: Agent Starting Run: 2mcqkbzi with config: batch_size: 4 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2mcqkbzi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.28933358192444
The number of items in train is:
11
The loss for epoch 0
1.4808485074476763
The running loss is:
31.518853425979614
The number of items in train is:
11
The loss for epoch 1
2.8653503114526924
The running loss is:
19.339537233114243
The number of items in train is:
11
The loss for epoch 2
1.758139748464931
The running loss is:
13.648087859153748
The number of items in train is:
11
The loss for epoch 3
1.2407352599230679
The running loss is:
12.581658080220222
The number of items in train is:
11
The loss for epoch 4
1.1437870982018383
The running loss is:
13.421542048454285
The number of items in train is:
11
The loss for epoch 5
1.2201401862231167
The running loss is:
12.218509554862976
The number of items in train is:
11
The loss for epoch 6
1.1107735958966343
The running loss is:
11.046258971095085
The number of items in train is:
11
The loss for epoch 7
1.004205361008644
The running loss is:
10.9622243642807
The number of items in train is:
11
The loss for epoch 8
0.9965658512982455
The running loss is:
10.555041283369064
The number of items in train is:
11
The loss for epoch 9
0.9595492075790059
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 16.295586
48 30755 ... 18.512218
49 30756 ... 20.077642
50 30757 ... 21.250025
51 30758 ... 22.185184
52 30759 ... 22.977167
53 30760 ... 23.682737
54 30761 ... 22.743214
55 30762 ... 22.403723
56 30763 ... 22.426382
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2mcqkbzi wandb: Agent Starting Run: xv0nyvna with config: batch_size: 4 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: xv0nyvna
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.87590116262436
The number of items in train is:
10
The loss for epoch 0
1.1875901162624358
The running loss is:
28.522132337093353
The number of items in train is:
10
The loss for epoch 1
2.8522132337093353
The running loss is:
15.147392272949219
The number of items in train is:
10
The loss for epoch 2
1.5147392272949218
The running loss is:
12.158874988555908
The number of items in train is:
10
The loss for epoch 3
1.2158874988555908
The running loss is:
12.22810235619545
The number of items in train is:
10
The loss for epoch 4
1.222810235619545
The running loss is:
10.145126044750214
The number of items in train is:
10
The loss for epoch 5
1.0145126044750215
The running loss is:
10.802199751138687
The number of items in train is:
10
The loss for epoch 6
1.0802199751138688
The running loss is:
9.540551364421844
The number of items in train is:
10
The loss for epoch 7
0.9540551364421844
The running loss is:
9.32604005932808
The number of items in train is:
10
The loss for epoch 8
0.9326040059328079
The running loss is:
8.828394114971161
The number of items in train is:
10
The loss for epoch 9
0.8828394114971161
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 8.527145
48 30755 ... 6.231841
49 30756 ... 4.828226
50 30757 ... 3.789749
51 30758 ... 2.900795
52 30759 ... 2.073069
53 30760 ... 1.270414
54 30761 ... 3.723977
55 30762 ... 4.264983
56 30763 ... 4.022814
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xv0nyvna wandb: Agent Starting Run: l8weyaf1 with config: batch_size: 4 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: l8weyaf1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
31.63803505897522
The number of items in train is:
11
The loss for epoch 0
2.8761850053613838
The running loss is:
18.769451931118965
The number of items in train is:
11
The loss for epoch 1
1.706313811919906
The running loss is:
11.642233811318874
The number of items in train is:
11
The loss for epoch 2
1.0583848919380794
The running loss is:
10.180661663413048
The number of items in train is:
11
The loss for epoch 3
0.9255146966739134
The running loss is:
11.987961947917938
The number of items in train is:
11
The loss for epoch 4
1.0898147225379944
The running loss is:
9.060462906956673
The number of items in train is:
11
The loss for epoch 5
0.8236784460869703
The running loss is:
9.576754912734032
The number of items in train is:
11
The loss for epoch 6
0.8706140829758211
The running loss is:
9.787697870284319
The number of items in train is:
11
The loss for epoch 7
0.8897907154803927
The running loss is:
11.934325933456421
The number of items in train is:
11
The loss for epoch 8
1.084938721223311
The running loss is:
9.142074868083
The number of items in train is:
11
The loss for epoch 9
0.8310977152802728
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 13.001091
48 30755 ... 12.799424
49 30756 ... 12.547743
50 30757 ... 12.283724
51 30758 ... 12.016661
52 30759 ... 11.748848
53 30760 ... 11.480849
54 30761 ... 12.626358
55 30762 ... 12.706987
56 30763 ... 12.524940
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l8weyaf1 wandb: Agent Starting Run: b15ovsca with config: batch_size: 4 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: b15ovsca
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
31.673054099082947
The number of items in train is:
11
The loss for epoch 0
2.879368554462086
The running loss is:
22.425230860710144
The number of items in train is:
11
The loss for epoch 1
2.0386573509736494
The running loss is:
16.475321352481842
The number of items in train is:
11
The loss for epoch 2
1.4977564865892583
The running loss is:
13.716146633028984
The number of items in train is:
11
The loss for epoch 3
1.2469224211844532
The running loss is:
14.30988696217537
The number of items in train is:
11
The loss for epoch 4
1.3008988147432154
The running loss is:
10.958332479000092
The number of items in train is:
11
The loss for epoch 5
0.9962120435454629
The running loss is:
10.916476994752884
The number of items in train is:
11
The loss for epoch 6
0.9924069995229895
The running loss is:
9.848691046237946
The number of items in train is:
11
The loss for epoch 7
0.895335549657995
The running loss is:
10.236702859401703
The number of items in train is:
11
The loss for epoch 8
0.9306093508547003
The running loss is:
9.222264111042023
The number of items in train is:
11
The loss for epoch 9
0.8383876464583657
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 13.620722
48 30755 ... 13.905069
49 30756 ... 14.085255
50 30757 ... 14.233186
51 30758 ... 14.371129
52 30759 ... 14.505979
53 30760 ... 14.639871
54 30761 ... 14.128526
55 30762 ... 14.062317
56 30763 ... 14.133948
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b15ovsca wandb: Agent Starting Run: 5ly0x251 with config: batch_size: 4 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 5ly0x251
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
32.99864113330841
The number of items in train is:
10
The loss for epoch 0
3.299864113330841
The running loss is:
17.60329395532608
The number of items in train is:
10
The loss for epoch 1
1.760329395532608
The running loss is:
11.215231776237488
The number of items in train is:
10
The loss for epoch 2
1.1215231776237489
The running loss is:
12.638816893100739
The number of items in train is:
10
The loss for epoch 3
1.263881689310074
The running loss is:
10.019712716341019
The number of items in train is:
10
The loss for epoch 4
1.0019712716341018
The running loss is:
9.607232719659805
The number of items in train is:
10
The loss for epoch 5
0.9607232719659805
The running loss is:
9.590596705675125
The number of items in train is:
10
The loss for epoch 6
0.9590596705675125
The running loss is:
8.71025364100933
The number of items in train is:
10
The loss for epoch 7
0.8710253641009331
The running loss is:
8.37963554263115
The number of items in train is:
10
The loss for epoch 8
0.837963554263115
The running loss is:
8.494551599025726
The number of items in train is:
10
The loss for epoch 9
0.8494551599025726
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 10.702608
48 30755 ... 9.330258
49 30756 ... 8.310846
50 30757 ... 7.426092
51 30758 ... 6.592715
52 30759 ... 5.778941
53 30760 ... 4.972645
54 30761 ... 7.639882
55 30762 ... 8.161717
56 30763 ... 7.865005
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5ly0x251 wandb: Agent Starting Run: 0atkj0td with config: batch_size: 4 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0atkj0td
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.96093699336052
The number of items in train is:
11
The loss for epoch 0
1.3600851812145927
The running loss is:
8.476144537329674
The number of items in train is:
11
The loss for epoch 1
0.7705585943026976
The running loss is:
7.245350956916809
The number of items in train is:
11
The loss for epoch 2
0.658668268810619
The running loss is:
6.171432768926024
The number of items in train is:
11
The loss for epoch 3
0.5610393426296386
The running loss is:
6.489634156227112
The number of items in train is:
11
The loss for epoch 4
0.589966741475192
The running loss is:
6.0105889942497015
The number of items in train is:
11
The loss for epoch 5
0.5464171812954274
The running loss is:
6.208764992654324
The number of items in train is:
11
The loss for epoch 6
0.5644331811503931
The running loss is:
6.286208868026733
The number of items in train is:
11
The loss for epoch 7
0.5714735334569757
The running loss is:
5.633164703845978
The number of items in train is:
11
The loss for epoch 8
0.5121058821678162
The running loss is:
5.67748536169529
The number of items in train is:
11
The loss for epoch 9
0.51613503288139
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 16.709024
48 30755 ... 21.198261
49 30756 ... 23.084475
50 30757 ... 24.721453
51 30758 ... 25.047770
52 30759 ... 24.897585
53 30760 ... 24.002348
54 30761 ... 27.997509
55 30762 ... 29.285919
56 30763 ... 30.621237
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0atkj0td wandb: Agent Starting Run: yr3r9v0z with config: batch_size: 4 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: yr3r9v0z
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.673433274030685
The number of items in train is:
10
The loss for epoch 0
1.3673433274030686
The running loss is:
9.724617719650269
The number of items in train is:
10
The loss for epoch 1
0.9724617719650268
The running loss is:
8.894245147705078
The number of items in train is:
10
The loss for epoch 2
0.8894245147705078
The running loss is:
8.056756377220154
The number of items in train is:
10
The loss for epoch 3
0.8056756377220153
The running loss is:
7.75899001955986
The number of items in train is:
10
The loss for epoch 4
0.775899001955986
The running loss is:
7.6932626366615295
The number of items in train is:
10
The loss for epoch 5
0.769326263666153
The running loss is:
7.423785865306854
The number of items in train is:
10
The loss for epoch 6
0.7423785865306854
The running loss is:
7.368699312210083
The number of items in train is:
10
The loss for epoch 7
0.7368699312210083
The running loss is:
7.208283305168152
The number of items in train is:
10
The loss for epoch 8
0.7208283305168152
The running loss is:
6.594608038663864
The number of items in train is:
10
The loss for epoch 9
0.6594608038663864
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.148539
48 30755 ... 17.949636
49 30756 ... 19.337902
50 30757 ... 21.656553
51 30758 ... 22.667198
52 30759 ... 23.891888
53 30760 ... 24.308977
54 30761 ... 29.522865
55 30762 ... 30.020037
56 30763 ... 33.703957
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yr3r9v0z wandb: Agent Starting Run: likqeqie with config: batch_size: 4 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: likqeqie
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.458408497273922
The number of items in train is:
10
The loss for epoch 0
1.3458408497273922
The running loss is:
8.387499928474426
The number of items in train is:
10
The loss for epoch 1
0.8387499928474427
The running loss is:
8.411725208163261
The number of items in train is:
10
The loss for epoch 2
0.8411725208163261
The running loss is:
7.547767452895641
The number of items in train is:
10
The loss for epoch 3
0.7547767452895642
The running loss is:
6.945795342326164
The number of items in train is:
10
The loss for epoch 4
0.6945795342326164
The running loss is:
7.231948897242546
The number of items in train is:
10
The loss for epoch 5
0.7231948897242546
The running loss is:
6.890873074531555
The number of items in train is:
10
The loss for epoch 6
0.6890873074531555
The running loss is:
6.782497234642506
The number of items in train is:
10
The loss for epoch 7
0.6782497234642506
The running loss is:
6.886941395699978
The number of items in train is:
10
The loss for epoch 8
0.6886941395699978
The running loss is:
6.84102863073349
The number of items in train is:
10
The loss for epoch 9
0.684102863073349
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.638868
48 30755 ... 15.248178
49 30756 ... 15.990419
50 30757 ... 17.082964
51 30758 ... 17.109074
52 30759 ... 16.817831
53 30760 ... 15.879253
54 30761 ... 19.300089
55 30762 ... 20.734055
56 30763 ... 22.122990
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: likqeqie wandb: Agent Starting Run: c3htrmch with config: batch_size: 4 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: c3htrmch
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.34802322089672
The number of items in train is:
11
The loss for epoch 0
1.2134566564451565
The running loss is:
20.381017327308655
The number of items in train is:
11
The loss for epoch 1
1.8528197570280596
The running loss is:
8.48755231499672
The number of items in train is:
11
The loss for epoch 2
0.7715956649997018
The running loss is:
7.347847249358892
The number of items in train is:
11
The loss for epoch 3
0.6679861135780811
The running loss is:
6.322733700275421
The number of items in train is:
11
The loss for epoch 4
0.574793972752311
The running loss is:
6.006848055869341
The number of items in train is:
11
The loss for epoch 5
0.5460770959881219
The running loss is:
5.8742464780807495
The number of items in train is:
11
The loss for epoch 6
0.53402240709825
The running loss is:
6.040382400155067
The number of items in train is:
11
The loss for epoch 7
0.5491256727413698
The running loss is:
5.12652325630188
The number of items in train is:
11
The loss for epoch 8
0.46604756875471637
The running loss is:
5.545659691095352
The number of items in train is:
11
The loss for epoch 9
0.5041508810086683
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 18.097548
48 30755 ... 21.679401
49 30756 ... 24.068140
50 30757 ... 25.589031
51 30758 ... 26.276314
52 30759 ... 26.265314
53 30760 ... 25.590273
54 30761 ... 30.015490
55 30762 ... 31.138529
56 30763 ... 33.173641
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c3htrmch wandb: Agent Starting Run: 8knvdyia with config: batch_size: 4 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 8knvdyia
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.671709895133972
The number of items in train is:
10
The loss for epoch 0
1.2671709895133971
The running loss is:
15.58467423915863
The number of items in train is:
10
The loss for epoch 1
1.5584674239158631
The running loss is:
8.86621218919754
The number of items in train is:
10
The loss for epoch 2
0.886621218919754
The running loss is:
8.211911827325821
The number of items in train is:
10
The loss for epoch 3
0.8211911827325821
The running loss is:
7.632152855396271
The number of items in train is:
10
The loss for epoch 4
0.763215285539627
The running loss is:
7.735361754894257
The number of items in train is:
10
The loss for epoch 5
0.7735361754894257
The running loss is:
7.110246509313583
The number of items in train is:
10
The loss for epoch 6
0.7110246509313584
The running loss is:
6.713372051715851
The number of items in train is:
10
The loss for epoch 7
0.6713372051715851
The running loss is:
6.79258930683136
The number of items in train is:
10
The loss for epoch 8
0.679258930683136
The running loss is:
5.895960241556168
The number of items in train is:
10
The loss for epoch 9
0.5895960241556167
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.023550
48 30755 ... 16.671810
49 30756 ... 16.646698
50 30757 ... 19.445019
51 30758 ... 19.573132
52 30759 ... 20.310709
53 30760 ... 19.657120
54 30761 ... 24.828531
55 30762 ... 25.687960
56 30763 ... 29.360603
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8knvdyia wandb: Agent Starting Run: tpfyv5ah with config: batch_size: 4 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: tpfyv5ah
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.119704440236092
The number of items in train is:
10
The loss for epoch 0
1.311970444023609
The running loss is:
15.15892705321312
The number of items in train is:
10
The loss for epoch 1
1.515892705321312
The running loss is:
8.269845277071
The number of items in train is:
10
The loss for epoch 2
0.8269845277071
The running loss is:
7.88303779065609
The number of items in train is:
10
The loss for epoch 3
0.788303779065609
The running loss is:
6.88837806135416
The number of items in train is:
10
The loss for epoch 4
0.688837806135416
The running loss is:
7.245162636041641
The number of items in train is:
10
The loss for epoch 5
0.7245162636041641
The running loss is:
6.730993062257767
The number of items in train is:
10
The loss for epoch 6
0.6730993062257766
The running loss is:
6.451875098049641
The number of items in train is:
10
The loss for epoch 7
0.6451875098049641
The running loss is:
6.440776079893112
The number of items in train is:
10
The loss for epoch 8
0.6440776079893112
The running loss is:
6.3287926241755486
The number of items in train is:
10
The loss for epoch 9
0.6328792624175549
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.329016
48 30755 ... 18.044563
49 30756 ... 19.793707
50 30757 ... 21.237078
51 30758 ... 21.749710
52 30759 ... 21.817234
53 30760 ... 21.214640
54 30761 ... 26.224243
55 30762 ... 27.728821
56 30763 ... 30.204544
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tpfyv5ah wandb: Agent Starting Run: 069lrx0s with config: batch_size: 4 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 069lrx0s
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.412841379642487
The number of items in train is:
11
The loss for epoch 0
1.0375310345129534
The running loss is:
25.99633625149727
The number of items in train is:
11
The loss for epoch 1
2.363303295590661
The running loss is:
16.070277526974678
The number of items in train is:
11
The loss for epoch 2
1.4609343206340617
The running loss is:
9.31078253686428
The number of items in train is:
11
The loss for epoch 3
0.846434776078571
The running loss is:
9.228860840201378
The number of items in train is:
11
The loss for epoch 4
0.8389873491092161
The running loss is:
7.060334699228406
The number of items in train is:
11
The loss for epoch 5
0.6418486090207641
The running loss is:
8.625365018844604
The number of items in train is:
11
The loss for epoch 6
0.7841240926222368
The running loss is:
6.593550542369485
The number of items in train is:
11
The loss for epoch 7
0.5994136856699531
The running loss is:
5.768903240561485
The number of items in train is:
11
The loss for epoch 8
0.5244457491419532
The running loss is:
5.97909389436245
The number of items in train is:
11
The loss for epoch 9
0.5435539903965864
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 17.675484
48 30755 ... 20.721533
49 30756 ... 22.798523
50 30757 ... 24.087915
51 30758 ... 24.757021
52 30759 ... 24.872627
53 30760 ... 24.516352
54 30761 ... 26.986809
55 30762 ... 28.829451
56 30763 ... 29.786718
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 069lrx0s wandb: Agent Starting Run: cnt3vzs0 with config: batch_size: 4 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: cnt3vzs0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.997970461845398
The number of items in train is:
10
The loss for epoch 0
1.0997970461845399
The running loss is:
21.985935747623444
The number of items in train is:
10
The loss for epoch 1
2.198593574762344
The running loss is:
12.202106922864914
The number of items in train is:
10
The loss for epoch 2
1.2202106922864915
The running loss is:
9.17008501291275
The number of items in train is:
10
The loss for epoch 3
0.917008501291275
The running loss is:
8.464543163776398
The number of items in train is:
10
The loss for epoch 4
0.8464543163776398
The running loss is:
8.57983085513115
The number of items in train is:
10
The loss for epoch 5
0.857983085513115
The running loss is:
8.02047947049141
The number of items in train is:
10
The loss for epoch 6
0.802047947049141
The running loss is:
7.290555238723755
The number of items in train is:
10
The loss for epoch 7
0.7290555238723755
The running loss is:
6.692835777997971
The number of items in train is:
10
The loss for epoch 8
0.6692835777997971
The running loss is:
6.110147446393967
The number of items in train is:
10
The loss for epoch 9
0.6110147446393966
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.224773
48 30755 ... 15.265686
49 30756 ... 15.022220
50 30757 ... 16.957497
51 30758 ... 16.836491
52 30759 ... 16.931461
53 30760 ... 15.981196
54 30761 ... 17.926718
55 30762 ... 19.954655
56 30763 ... 21.096838
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cnt3vzs0 wandb: Agent Starting Run: qocq3wae with config: batch_size: 4 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qocq3wae
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.904254585504532
The number of items in train is:
10
The loss for epoch 0
0.9904254585504532
The running loss is:
25.055099427700043
The number of items in train is:
10
The loss for epoch 1
2.5055099427700043
The running loss is:
12.711764395236969
The number of items in train is:
10
The loss for epoch 2
1.2711764395236969
The running loss is:
10.374877393245697
The number of items in train is:
10
The loss for epoch 3
1.0374877393245696
The running loss is:
8.679088652133942
The number of items in train is:
10
The loss for epoch 4
0.8679088652133942
The running loss is:
7.766414493322372
The number of items in train is:
10
The loss for epoch 5
0.7766414493322372
The running loss is:
7.597523421049118
The number of items in train is:
10
The loss for epoch 6
0.7597523421049118
The running loss is:
7.39857842028141
The number of items in train is:
10
The loss for epoch 7
0.739857842028141
The running loss is:
6.676791451871395
The number of items in train is:
10
The loss for epoch 8
0.6676791451871396
The running loss is:
6.837151870131493
The number of items in train is:
10
The loss for epoch 9
0.6837151870131493
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.726316
48 30755 ... 14.972114
49 30756 ... 16.001463
50 30757 ... 16.900673
51 30758 ... 17.000143
52 30759 ... 16.699017
53 30760 ... 15.903903
54 30761 ... 19.487146
55 30762 ... 20.715403
56 30763 ... 21.923807
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qocq3wae wandb: Agent Starting Run: fv3v4uho with config: batch_size: 4 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fv3v4uho
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
40.59835138916969
The number of items in train is:
11
The loss for epoch 0
3.690759217197245
The running loss is:
19.944113321602345
The number of items in train is:
11
The loss for epoch 1
1.8131012110547586
The running loss is:
11.857287377119064
The number of items in train is:
11
The loss for epoch 2
1.077935216101733
The running loss is:
12.013430297374725
The number of items in train is:
11
The loss for epoch 3
1.092130027034066
The running loss is:
12.344391658902168
The number of items in train is:
11
The loss for epoch 4
1.1222174235365607
The running loss is:
8.543003568425775
The number of items in train is:
11
The loss for epoch 5
0.7766366880387068
The running loss is:
12.394158691167831
The number of items in train is:
11
The loss for epoch 6
1.1267416991970756
The running loss is:
10.03352677822113
The number of items in train is:
11
The loss for epoch 7
0.9121387980201028
The running loss is:
7.597949281334877
The number of items in train is:
11
The loss for epoch 8
0.6907226619395342
The running loss is:
11.681423753499985
The number of items in train is:
11
The loss for epoch 9
1.061947613954544
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 18.578806
48 30755 ... 20.679152
49 30756 ... 23.081081
50 30757 ... 23.915461
51 30758 ... 24.671740
52 30759 ... 24.634520
53 30760 ... 24.390169
54 30761 ... 27.176733
55 30762 ... 27.554413
56 30763 ... 28.308208
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fv3v4uho wandb: Agent Starting Run: m9ue8zb4 with config: batch_size: 4 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: m9ue8zb4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
26.59406042098999
The number of items in train is:
10
The loss for epoch 0
2.659406042098999
The running loss is:
13.403459221124649
The number of items in train is:
10
The loss for epoch 1
1.340345922112465
The running loss is:
9.142663478851318
The number of items in train is:
10
The loss for epoch 2
0.9142663478851318
The running loss is:
11.032457649707794
The number of items in train is:
10
The loss for epoch 3
1.1032457649707794
The running loss is:
9.233210653066635
The number of items in train is:
10
The loss for epoch 4
0.9233210653066635
The running loss is:
11.626732230186462
The number of items in train is:
10
The loss for epoch 5
1.1626732230186463
The running loss is:
13.688178479671478
The number of items in train is:
10
The loss for epoch 6
1.3688178479671478
The running loss is:
9.463880628347397
The number of items in train is:
10
The loss for epoch 7
0.9463880628347396
The running loss is:
9.63527712225914
The number of items in train is:
10
The loss for epoch 8
0.963527712225914
The running loss is:
8.616059482097626
The number of items in train is:
10
The loss for epoch 9
0.8616059482097626
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.567437
48 30755 ... 6.328658
49 30756 ... 5.065443
50 30757 ... 4.457339
51 30758 ... 3.853146
52 30759 ... 3.379244
53 30760 ... 2.938148
54 30761 ... 2.664474
55 30762 ... 3.861934
56 30763 ... 3.986446
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: m9ue8zb4 wandb: Agent Starting Run: 8ljn4u6x with config: batch_size: 4 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8ljn4u6x
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.372302889823914
The number of items in train is:
10
The loss for epoch 0
2.8372302889823913
The running loss is:
12.347882062196732
The number of items in train is:
10
The loss for epoch 1
1.2347882062196731
The running loss is:
9.684420198202133
The number of items in train is:
10
The loss for epoch 2
0.9684420198202133
The running loss is:
9.461739972233772
The number of items in train is:
10
The loss for epoch 3
0.9461739972233772
The running loss is:
12.423586398363113
The number of items in train is:
10
The loss for epoch 4
1.2423586398363113
The running loss is:
9.940438836812973
The number of items in train is:
10
The loss for epoch 5
0.9940438836812973
The running loss is:
10.14803022146225
The number of items in train is:
10
The loss for epoch 6
1.014803022146225
The running loss is:
10.891903132200241
The number of items in train is:
10
The loss for epoch 7
1.089190313220024
The running loss is:
8.46597534418106
The number of items in train is:
10
The loss for epoch 8
0.846597534418106
The running loss is:
9.821460217237473
The number of items in train is:
10
The loss for epoch 9
0.9821460217237472
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.317070
48 30755 ... 12.904198
49 30756 ... 12.515239
50 30757 ... 12.116361
51 30758 ... 11.319300
52 30759 ... 10.415378
53 30760 ... 9.452648
54 30761 ... 10.703618
55 30762 ... 12.681755
56 30763 ... 12.554018
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8ljn4u6x wandb: Agent Starting Run: 9073m7jd with config: batch_size: 4 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 9073m7jd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.627537846565247
The number of items in train is:
10
The loss for epoch 0
0.9627537846565246
The running loss is:
17.363112449645996
The number of items in train is:
10
The loss for epoch 1
1.7363112449645997
The running loss is:
6.405838273465633
The number of items in train is:
10
The loss for epoch 2
0.6405838273465634
The running loss is:
5.693458579480648
The number of items in train is:
10
The loss for epoch 3
0.5693458579480648
The running loss is:
5.169158458709717
The number of items in train is:
10
The loss for epoch 4
0.5169158458709717
The running loss is:
5.052080765366554
The number of items in train is:
10
The loss for epoch 5
0.5052080765366554
The running loss is:
4.704639323055744
The number of items in train is:
10
The loss for epoch 6
0.47046393230557443
The running loss is:
4.387305963784456
The number of items in train is:
10
The loss for epoch 7
0.43873059637844564
The running loss is:
4.495713531970978
The number of items in train is:
10
The loss for epoch 8
0.4495713531970978
The running loss is:
4.703176259994507
The number of items in train is:
10
The loss for epoch 9
0.4703176259994507
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.808335
48 30755 ... 6.588649
49 30756 ... 12.238354
50 30757 ... 11.621011
51 30758 ... 10.989270
52 30759 ... 10.464103
53 30760 ... 8.492026
54 30761 ... 8.029394
55 30762 ... 7.711127
56 30763 ... 12.337846
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9073m7jd wandb: Agent Starting Run: ak3ddjcm with config: batch_size: 4 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ak3ddjcm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.51008079200983
The number of items in train is:
10
The loss for epoch 0
1.351008079200983
The running loss is:
9.150133788585663
The number of items in train is:
10
The loss for epoch 1
0.9150133788585663
The running loss is:
8.0506741553545
The number of items in train is:
10
The loss for epoch 2
0.80506741553545
The running loss is:
7.332058683037758
The number of items in train is:
10
The loss for epoch 3
0.7332058683037758
The running loss is:
7.43514696136117
The number of items in train is:
10
The loss for epoch 4
0.743514696136117
The running loss is:
6.992777206003666
The number of items in train is:
10
The loss for epoch 5
0.6992777206003666
The running loss is:
6.710105545818806
The number of items in train is:
10
The loss for epoch 6
0.6710105545818805
The running loss is:
7.016908168792725
The number of items in train is:
10
The loss for epoch 7
0.7016908168792725
The running loss is:
6.1487134620547295
The number of items in train is:
10
The loss for epoch 8
0.6148713462054729
The running loss is:
6.259711891412735
The number of items in train is:
10
The loss for epoch 9
0.6259711891412735
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.518709
48 30755 ... 9.676765
49 30756 ... 14.328287
50 30757 ... 14.434947
51 30758 ... 14.797523
52 30759 ... 15.179770
53 30760 ... 13.908753
54 30761 ... 16.497807
55 30762 ... 18.353893
56 30763 ... 22.759249
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ak3ddjcm wandb: Agent Starting Run: gkboykbz with config: batch_size: 4 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: gkboykbz
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.057014763355255
The number of items in train is:
10
The loss for epoch 0
1.2057014763355256
The running loss is:
9.196175366640091
The number of items in train is:
10
The loss for epoch 1
0.9196175366640091
The running loss is:
7.984934225678444
The number of items in train is:
10
The loss for epoch 2
0.7984934225678444
The running loss is:
7.211847752332687
The number of items in train is:
10
The loss for epoch 3
0.7211847752332687
The running loss is:
6.867999359965324
The number of items in train is:
10
The loss for epoch 4
0.6867999359965324
The running loss is:
6.554838925600052
The number of items in train is:
10
The loss for epoch 5
0.6554838925600052
The running loss is:
6.439648315310478
The number of items in train is:
10
The loss for epoch 6
0.6439648315310478
The running loss is:
6.144940108060837
The number of items in train is:
10
The loss for epoch 7
0.6144940108060837
The running loss is:
5.929564245045185
The number of items in train is:
10
The loss for epoch 8
0.5929564245045185
The running loss is:
5.835510566830635
The number of items in train is:
10
The loss for epoch 9
0.5835510566830635
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.744005
48 30755 ... 6.455384
49 30756 ... 7.808669
50 30757 ... 6.539020
51 30758 ... 4.805805
52 30759 ... 2.202368
53 30760 ... -1.791144
54 30761 ... -1.477443
55 30762 ... -3.113125
56 30763 ... -5.422577
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gkboykbz wandb: Agent Starting Run: fw7dwm15 with config: batch_size: 4 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fw7dwm15
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.429576203227043
The number of items in train is:
10
The loss for epoch 0
0.8429576203227043
The running loss is:
35.47298264503479
The number of items in train is:
10
The loss for epoch 1
3.547298264503479
The running loss is:
11.112188205122948
The number of items in train is:
10
The loss for epoch 2
1.1112188205122948
The running loss is:
13.196346916258335
The number of items in train is:
10
The loss for epoch 3
1.3196346916258335
The running loss is:
6.575393192470074
The number of items in train is:
10
The loss for epoch 4
0.6575393192470074
The running loss is:
5.8676954954862595
The number of items in train is:
10
The loss for epoch 5
0.5867695495486259
The running loss is:
5.116438694298267
The number of items in train is:
10
The loss for epoch 6
0.5116438694298268
The running loss is:
4.6275116093456745
The number of items in train is:
10
The loss for epoch 7
0.4627511609345675
The running loss is:
4.5346789956092834
The number of items in train is:
10
The loss for epoch 8
0.45346789956092837
The running loss is:
4.536572776734829
The number of items in train is:
10
The loss for epoch 9
0.4536572776734829
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.103466
48 30755 ... 6.257463
49 30756 ... 11.562319
50 30757 ... 10.523199
51 30758 ... 9.646112
52 30759 ... 8.691895
53 30760 ... 6.254402
54 30761 ... 6.156374
55 30762 ... 5.828930
56 30763 ... 10.276820
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fw7dwm15 wandb: Agent Starting Run: dpi51sw2 with config: batch_size: 4 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: dpi51sw2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.501193806529045
The number of items in train is:
10
The loss for epoch 0
1.2501193806529045
The running loss is:
20.099119901657104
The number of items in train is:
10
The loss for epoch 1
2.0099119901657105
The running loss is:
8.999961793422699
The number of items in train is:
10
The loss for epoch 2
0.8999961793422699
The running loss is:
8.48761773109436
The number of items in train is:
10
The loss for epoch 3
0.848761773109436
The running loss is:
7.359446678310633
The number of items in train is:
10
The loss for epoch 4
0.7359446678310633
The running loss is:
7.000715114176273
The number of items in train is:
10
The loss for epoch 5
0.7000715114176274
The running loss is:
6.593851193785667
The number of items in train is:
10
The loss for epoch 6
0.6593851193785667
The running loss is:
6.7040664702653885
The number of items in train is:
10
The loss for epoch 7
0.6704066470265388
The running loss is:
5.951735310256481
The number of items in train is:
10
The loss for epoch 8
0.5951735310256481
The running loss is:
5.534311920404434
The number of items in train is:
10
The loss for epoch 9
0.5534311920404434
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.366433
48 30755 ... 9.865753
49 30756 ... 13.617732
50 30757 ... 13.982615
51 30758 ... 14.094790
52 30759 ... 14.050801
53 30760 ... 12.748096
54 30761 ... 14.966385
55 30762 ... 17.125698
56 30763 ... 20.394379
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: dpi51sw2 wandb: Agent Starting Run: u80txo66 with config: batch_size: 4 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u80txo66
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.667285114526749
The number of items in train is:
10
The loss for epoch 0
1.0667285114526748
The running loss is:
20.265333622694016
The number of items in train is:
10
The loss for epoch 1
2.0265333622694017
The running loss is:
8.728106766939163
The number of items in train is:
10
The loss for epoch 2
0.8728106766939163
The running loss is:
8.550827756524086
The number of items in train is:
10
The loss for epoch 3
0.8550827756524086
The running loss is:
7.6918254643678665
The number of items in train is:
10
The loss for epoch 4
0.7691825464367866
The running loss is:
7.004032850265503
The number of items in train is:
10
The loss for epoch 5
0.7004032850265502
The running loss is:
6.4064972549676895
The number of items in train is:
10
The loss for epoch 6
0.6406497254967689
The running loss is:
6.222326099872589
The number of items in train is:
10
The loss for epoch 7
0.6222326099872589
The running loss is:
5.876827664673328
The number of items in train is:
10
The loss for epoch 8
0.5876827664673329
The running loss is:
5.46251180768013
The number of items in train is:
10
The loss for epoch 9
0.546251180768013
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.634794
48 30755 ... 5.956108
49 30756 ... 7.695518
50 30757 ... 6.790030
51 30758 ... 5.360010
52 30759 ... 3.331872
53 30760 ... 0.147778
54 30761 ... -0.868146
55 30762 ... -2.107802
56 30763 ... -3.228223
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u80txo66 wandb: Agent Starting Run: 4htpl5rr with config: batch_size: 4 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 4htpl5rr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.714561760425568
The number of items in train is:
10
The loss for epoch 0
1.4714561760425569
The running loss is:
21.01663726568222
The number of items in train is:
10
The loss for epoch 1
2.101663726568222
The running loss is:
15.515894889831543
The number of items in train is:
10
The loss for epoch 2
1.5515894889831543
The running loss is:
7.601687487214804
The number of items in train is:
10
The loss for epoch 3
0.7601687487214803
The running loss is:
6.936983227729797
The number of items in train is:
10
The loss for epoch 4
0.6936983227729797
The running loss is:
6.483203932642937
The number of items in train is:
10
The loss for epoch 5
0.6483203932642937
The running loss is:
5.312639720737934
The number of items in train is:
10
The loss for epoch 6
0.5312639720737934
The running loss is:
5.345114007592201
The number of items in train is:
10
The loss for epoch 7
0.5345114007592201
The running loss is:
5.2790632620453835
The number of items in train is:
10
The loss for epoch 8
0.5279063262045384
The running loss is:
5.034602418541908
The number of items in train is:
10
The loss for epoch 9
0.5034602418541908
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.954473
48 30755 ... 6.272552
49 30756 ... 11.065792
50 30757 ... 10.025171
51 30758 ... 8.285496
52 30759 ... 7.193275
53 30760 ... 4.804574
54 30761 ... 4.655031
55 30762 ... 4.361861
56 30763 ... 8.187953
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4htpl5rr wandb: Agent Starting Run: lo2ks8hs with config: batch_size: 4 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: lo2ks8hs
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.384419649839401
The number of items in train is:
10
The loss for epoch 0
1.1384419649839401
The running loss is:
18.25188379921019
The number of items in train is:
10
The loss for epoch 1
1.8251883799210191
The running loss is:
12.829950749874115
The number of items in train is:
10
The loss for epoch 2
1.2829950749874115
The running loss is:
7.982527822256088
The number of items in train is:
10
The loss for epoch 3
0.7982527822256088
The running loss is:
7.810066565871239
The number of items in train is:
10
The loss for epoch 4
0.7810066565871239
The running loss is:
6.684666350483894
The number of items in train is:
10
The loss for epoch 5
0.6684666350483894
The running loss is:
7.643584281206131
The number of items in train is:
10
The loss for epoch 6
0.764358428120613
The running loss is:
8.792829811573029
The number of items in train is:
10
The loss for epoch 7
0.8792829811573029
The running loss is:
6.99271997064352
The number of items in train is:
10
The loss for epoch 8
0.6992719970643521
The running loss is:
6.918453752994537
The number of items in train is:
10
The loss for epoch 9
0.6918453752994538
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.321559
48 30755 ... 9.187271
49 30756 ... 12.871760
50 30757 ... 12.650419
51 30758 ... 11.597202
52 30759 ... 9.462704
53 30760 ... 6.282671
54 30761 ... 5.563904
55 30762 ... 6.355840
56 30763 ... 9.107053
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lo2ks8hs wandb: Agent Starting Run: f7bdxdg5 with config: batch_size: 4 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: f7bdxdg5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.466510713100433
The number of items in train is:
10
The loss for epoch 0
0.9466510713100433
The running loss is:
19.481352478265762
The number of items in train is:
10
The loss for epoch 1
1.9481352478265763
The running loss is:
12.479926511645317
The number of items in train is:
10
The loss for epoch 2
1.2479926511645316
The running loss is:
8.340172469615936
The number of items in train is:
10
The loss for epoch 3
0.8340172469615936
The running loss is:
8.205783903598785
The number of items in train is:
10
The loss for epoch 4
0.8205783903598786
The running loss is:
7.630669295787811
The number of items in train is:
10
The loss for epoch 5
0.7630669295787811
The running loss is:
6.677744090557098
The number of items in train is:
10
The loss for epoch 6
0.6677744090557098
The running loss is:
6.896913185715675
The number of items in train is:
10
The loss for epoch 7
0.6896913185715675
The running loss is:
6.556647375226021
The number of items in train is:
10
The loss for epoch 8
0.6556647375226021
The running loss is:
6.700380817055702
The number of items in train is:
10
The loss for epoch 9
0.6700380817055702
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.198957
48 30755 ... 12.617393
49 30756 ... 12.954767
50 30757 ... 12.107231
51 30758 ... 11.026435
52 30759 ... 9.624288
53 30760 ... 7.724436
54 30761 ... 10.234614
55 30762 ... 10.804576
56 30763 ... 10.495942
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f7bdxdg5 wandb: Agent Starting Run: kyfny3j5 with config: batch_size: 4 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: kyfny3j5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
91.59792420268059
The number of items in train is:
10
The loss for epoch 0
9.159792420268058
The running loss is:
23.251791685819626
The number of items in train is:
10
The loss for epoch 1
2.3251791685819625
The running loss is:
11.11307579278946
The number of items in train is:
10
The loss for epoch 2
1.111307579278946
The running loss is:
6.939586728811264
The number of items in train is:
10
The loss for epoch 3
0.6939586728811264
The running loss is:
9.343335047364235
The number of items in train is:
10
The loss for epoch 4
0.9343335047364235
The running loss is:
6.820296868681908
The number of items in train is:
10
The loss for epoch 5
0.6820296868681908
The running loss is:
5.8018301874399185
The number of items in train is:
10
The loss for epoch 6
0.5801830187439918
The running loss is:
5.937199890613556
The number of items in train is:
10
The loss for epoch 7
0.5937199890613556
The running loss is:
6.757883593440056
The number of items in train is:
10
The loss for epoch 8
0.6757883593440056
The running loss is:
7.597961753606796
The number of items in train is:
10
The loss for epoch 9
0.7597961753606797
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.007220
48 30755 ... 4.571890
49 30756 ... 4.057703
50 30757 ... 1.964260
51 30758 ... -0.132805
52 30759 ... -2.333437
53 30760 ... -4.619548
54 30761 ... -4.016709
55 30762 ... -4.159013
56 30763 ... -3.811644
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: kyfny3j5 wandb: Agent Starting Run: scy00je1 with config: batch_size: 4 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: scy00je1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
49.56044429540634
The number of items in train is:
10
The loss for epoch 0
4.9560444295406345
The running loss is:
13.70760928094387
The number of items in train is:
10
The loss for epoch 1
1.370760928094387
The running loss is:
17.000253543257713
The number of items in train is:
10
The loss for epoch 2
1.7000253543257713
The running loss is:
13.842572450637817
The number of items in train is:
10
The loss for epoch 3
1.3842572450637818
The running loss is:
15.544250130653381
The number of items in train is:
10
The loss for epoch 4
1.554425013065338
The running loss is:
9.349140167236328
The number of items in train is:
10
The loss for epoch 5
0.9349140167236328
The running loss is:
10.090777337551117
The number of items in train is:
10
The loss for epoch 6
1.0090777337551118
The running loss is:
11.35200434923172
The number of items in train is:
10
The loss for epoch 7
1.135200434923172
The running loss is:
7.790517836809158
The number of items in train is:
10
The loss for epoch 8
0.7790517836809159
The running loss is:
8.42673248052597
The number of items in train is:
10
The loss for epoch 9
0.842673248052597
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.598314
48 30755 ... 7.377418
49 30756 ... 9.713764
50 30757 ... 8.512883
51 30758 ... 6.791293
52 30759 ... 5.252714
53 30760 ... 3.030388
54 30761 ... 3.328702
55 30762 ... 3.037323
56 30763 ... 3.389056
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: scy00je1 wandb: Agent Starting Run: iygt4rxi with config: batch_size: 4 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: iygt4rxi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
36.11813059449196
The number of items in train is:
10
The loss for epoch 0
3.611813059449196
The running loss is:
12.339976996183395
The number of items in train is:
10
The loss for epoch 1
1.2339976996183395
The running loss is:
9.668639838695526
The number of items in train is:
10
The loss for epoch 2
0.9668639838695526
The running loss is:
9.826381415128708
The number of items in train is:
10
The loss for epoch 3
0.9826381415128708
The running loss is:
15.76567393541336
The number of items in train is:
10
The loss for epoch 4
1.576567393541336
The running loss is:
10.812987506389618
The number of items in train is:
10
The loss for epoch 5
1.0812987506389617
The running loss is:
9.61716541647911
The number of items in train is:
10
The loss for epoch 6
0.9617165416479111
The running loss is:
9.290621802210808
The number of items in train is:
10
The loss for epoch 7
0.9290621802210808
The running loss is:
8.212620228528976
The number of items in train is:
10
The loss for epoch 8
0.8212620228528976
The running loss is:
9.537692248821259
The number of items in train is:
10
The loss for epoch 9
0.9537692248821259
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.728024
48 30755 ... 10.327018
49 30756 ... 12.556839
50 30757 ... 11.601530
51 30758 ... 10.465916
52 30759 ... 10.037251
53 30760 ... 8.805302
54 30761 ... 9.777656
55 30762 ... 9.648338
56 30763 ... 11.390595
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: iygt4rxi wandb: Agent Starting Run: u4p26qqe with config: batch_size: 4 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: u4p26qqe
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.139220284298062
The number of items in train is:
10
The loss for epoch 0
1.3139220284298063
The running loss is:
7.603810682892799
The number of items in train is:
10
The loss for epoch 1
0.76038106828928
The running loss is:
6.590954020619392
The number of items in train is:
10
The loss for epoch 2
0.6590954020619393
The running loss is:
5.3788275346159935
The number of items in train is:
10
The loss for epoch 3
0.5378827534615993
The running loss is:
4.933269586414099
The number of items in train is:
10
The loss for epoch 4
0.49332695864140985
The running loss is:
4.663033917546272
The number of items in train is:
10
The loss for epoch 5
0.4663033917546272
The running loss is:
4.390941029414535
The number of items in train is:
10
The loss for epoch 6
0.43909410294145346
The running loss is:
4.794956460595131
The number of items in train is:
10
The loss for epoch 7
0.4794956460595131
The running loss is:
4.561512395739555
The number of items in train is:
10
The loss for epoch 8
0.45615123957395554
The running loss is:
4.312907887622714
The number of items in train is:
10
The loss for epoch 9
0.4312907887622714
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.966106
48 30755 ... 7.026946
49 30756 ... 7.303446
50 30757 ... 6.005102
51 30758 ... 4.476109
52 30759 ... 3.117196
53 30760 ... 1.653447
54 30761 ... 1.438207
55 30762 ... 1.206806
56 30763 ... 1.003915
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u4p26qqe wandb: Agent Starting Run: oa112vdp with config: batch_size: 4 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: oa112vdp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.0843945145607
The number of items in train is:
10
The loss for epoch 0
1.30843945145607
The running loss is:
7.665140315890312
The number of items in train is:
10
The loss for epoch 1
0.7665140315890312
The running loss is:
6.743201792240143
The number of items in train is:
10
The loss for epoch 2
0.6743201792240143
The running loss is:
5.883106000721455
The number of items in train is:
10
The loss for epoch 3
0.5883106000721454
The running loss is:
5.515905536711216
The number of items in train is:
10
The loss for epoch 4
0.5515905536711216
The running loss is:
4.997781403362751
The number of items in train is:
10
The loss for epoch 5
0.4997781403362751
The running loss is:
4.992602676153183
The number of items in train is:
10
The loss for epoch 6
0.4992602676153183
The running loss is:
5.128393992781639
The number of items in train is:
10
The loss for epoch 7
0.5128393992781639
The running loss is:
4.745439916849136
The number of items in train is:
10
The loss for epoch 8
0.4745439916849136
The running loss is:
5.019068889319897
The number of items in train is:
10
The loss for epoch 9
0.5019068889319896
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.649288
48 30755 ... 7.107749
49 30756 ... 7.127906
50 30757 ... 5.951869
51 30758 ... 4.860780
52 30759 ... 4.058114
53 30760 ... 3.299357
54 30761 ... 3.037968
55 30762 ... 2.571593
56 30763 ... 1.843937
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: oa112vdp wandb: Agent Starting Run: lvob0bbe with config: batch_size: 4 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: lvob0bbe
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.67995372414589
The number of items in train is:
10
The loss for epoch 0
1.367995372414589
The running loss is:
8.989439904689789
The number of items in train is:
10
The loss for epoch 1
0.8989439904689789
The running loss is:
8.195689350366592
The number of items in train is:
10
The loss for epoch 2
0.8195689350366593
The running loss is:
6.894126743078232
The number of items in train is:
10
The loss for epoch 3
0.6894126743078232
The running loss is:
6.594148024916649
The number of items in train is:
10
The loss for epoch 4
0.6594148024916648
The running loss is:
6.3120845928788185
The number of items in train is:
10
The loss for epoch 5
0.6312084592878818
The running loss is:
6.1284110099077225
The number of items in train is:
10
The loss for epoch 6
0.6128411009907723
The running loss is:
6.259409077465534
The number of items in train is:
10
The loss for epoch 7
0.6259409077465534
The running loss is:
5.780759200453758
The number of items in train is:
10
The loss for epoch 8
0.5780759200453758
The running loss is:
5.695149905979633
The number of items in train is:
10
The loss for epoch 9
0.5695149905979633
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.292809
48 30755 ... 12.110656
49 30756 ... 13.091563
50 30757 ... 13.885511
51 30758 ... 15.185983
52 30759 ... 17.058050
53 30760 ... 19.260855
54 30761 ... 20.051224
55 30762 ... 20.744509
56 30763 ... 21.911655
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lvob0bbe wandb: Agent Starting Run: 35j8rkx7 with config: batch_size: 4 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 35j8rkx7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.55137413740158
The number of items in train is:
10
The loss for epoch 0
1.155137413740158
The running loss is:
16.014386296272278
The number of items in train is:
10
The loss for epoch 1
1.6014386296272278
The running loss is:
6.75588384270668
The number of items in train is:
10
The loss for epoch 2
0.675588384270668
The running loss is:
6.29716794192791
The number of items in train is:
10
The loss for epoch 3
0.629716794192791
The running loss is:
5.1970526948571205
The number of items in train is:
10
The loss for epoch 4
0.519705269485712
The running loss is:
5.025679625570774
The number of items in train is:
10
The loss for epoch 5
0.5025679625570774
The running loss is:
4.67264661937952
The number of items in train is:
10
The loss for epoch 6
0.467264661937952
The running loss is:
5.31112065166235
The number of items in train is:
10
The loss for epoch 7
0.531112065166235
The running loss is:
4.5775028094649315
The number of items in train is:
10
The loss for epoch 8
0.45775028094649317
The running loss is:
4.067775249481201
The number of items in train is:
10
The loss for epoch 9
0.40677752494812014
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.944151
48 30755 ... 8.560498
49 30756 ... 8.103656
50 30757 ... 6.687842
51 30758 ... 5.952302
52 30759 ... 5.573210
53 30760 ... 5.453351
54 30761 ... 5.476648
55 30762 ... 4.879870
56 30763 ... 4.252527
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 35j8rkx7 wandb: Agent Starting Run: sg71mruo with config: batch_size: 4 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sg71mruo
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.126236453652382
The number of items in train is:
10
The loss for epoch 0
1.3126236453652382
The running loss is:
14.40095217525959
The number of items in train is:
10
The loss for epoch 1
1.440095217525959
The running loss is:
7.083043187856674
The number of items in train is:
10
The loss for epoch 2
0.7083043187856675
The running loss is:
6.096744194626808
The number of items in train is:
10
The loss for epoch 3
0.6096744194626809
The running loss is:
5.1841307654976845
The number of items in train is:
10
The loss for epoch 4
0.5184130765497684
The running loss is:
5.177260473370552
The number of items in train is:
10
The loss for epoch 5
0.5177260473370552
The running loss is:
4.819695513695478
The number of items in train is:
10
The loss for epoch 6
0.48196955136954783
The running loss is:
5.148202821612358
The number of items in train is:
10
The loss for epoch 7
0.5148202821612358
The running loss is:
4.959500506520271
The number of items in train is:
10
The loss for epoch 8
0.49595005065202713
The running loss is:
5.563718307763338
The number of items in train is:
10
The loss for epoch 9
0.5563718307763338
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.187324
48 30755 ... 9.934227
49 30756 ... 10.304854
50 30757 ... 9.717361
51 30758 ... 10.074327
52 30759 ... 10.855839
53 30760 ... 11.962115
54 30761 ... 12.211823
55 30762 ... 12.268024
56 30763 ... 12.549157
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sg71mruo wandb: Agent Starting Run: n009dnk2 with config: batch_size: 4 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: n009dnk2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.769485369324684
The number of items in train is:
10
The loss for epoch 0
1.2769485369324685
The running loss is:
18.07359327375889
The number of items in train is:
10
The loss for epoch 1
1.8073593273758888
The running loss is:
8.222085058689117
The number of items in train is:
10
The loss for epoch 2
0.8222085058689117
The running loss is:
7.520764961838722
The number of items in train is:
10
The loss for epoch 3
0.7520764961838722
The running loss is:
6.81798791885376
The number of items in train is:
10
The loss for epoch 4
0.681798791885376
The running loss is:
6.529789224267006
The number of items in train is:
10
The loss for epoch 5
0.6529789224267006
The running loss is:
6.242193579673767
The number of items in train is:
10
The loss for epoch 6
0.6242193579673767
The running loss is:
6.023411050438881
The number of items in train is:
10
The loss for epoch 7
0.602341105043888
The running loss is:
5.495791830122471
The number of items in train is:
10
The loss for epoch 8
0.5495791830122471
The running loss is:
5.40959145501256
The number of items in train is:
10
The loss for epoch 9
0.540959145501256
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.513058
48 30755 ... 11.645679
49 30756 ... 13.005260
50 30757 ... 14.087539
51 30758 ... 15.303416
52 30759 ... 16.887409
53 30760 ... 18.930803
54 30761 ... 20.712101
55 30762 ... 21.618250
56 30763 ... 22.668322
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n009dnk2 wandb: Agent Starting Run: bphq6zit with config: batch_size: 4 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bphq6zit
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.001862179487944
The number of items in train is:
10
The loss for epoch 0
0.9001862179487944
The running loss is:
24.234292328357697
The number of items in train is:
10
The loss for epoch 1
2.42342923283577
The running loss is:
12.146701619029045
The number of items in train is:
10
The loss for epoch 2
1.2146701619029046
The running loss is:
8.325868934392929
The number of items in train is:
10
The loss for epoch 3
0.8325868934392929
The running loss is:
7.485300242900848
The number of items in train is:
10
The loss for epoch 4
0.7485300242900849
The running loss is:
6.788752064108849
The number of items in train is:
10
The loss for epoch 5
0.6788752064108848
The running loss is:
6.220466896891594
The number of items in train is:
10
The loss for epoch 6
0.6220466896891594
The running loss is:
5.8215655237436295
The number of items in train is:
10
The loss for epoch 7
0.5821565523743629
The running loss is:
5.489045836031437
The number of items in train is:
10
The loss for epoch 8
0.5489045836031436
The running loss is:
5.328197099268436
The number of items in train is:
10
The loss for epoch 9
0.5328197099268437
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.155974
48 30755 ... 10.577695
49 30756 ... 10.467627
50 30757 ... 11.085591
51 30758 ... 10.823718
52 30759 ... 10.074667
53 30760 ... 9.439847
54 30761 ... 10.096174
55 30762 ... 9.974174
56 30763 ... 10.144117
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bphq6zit wandb: Agent Starting Run: 0t6i24cz with config: batch_size: 4 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 0t6i24cz
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.483697727322578
The number of items in train is:
10
The loss for epoch 0
0.8483697727322579
The running loss is:
21.93063649535179
The number of items in train is:
10
The loss for epoch 1
2.193063649535179
The running loss is:
10.534606114029884
The number of items in train is:
10
The loss for epoch 2
1.0534606114029885
The running loss is:
9.683033972978592
The number of items in train is:
10
The loss for epoch 3
0.9683033972978592
The running loss is:
8.544187188148499
The number of items in train is:
10
The loss for epoch 4
0.8544187188148499
The running loss is:
7.527521088719368
The number of items in train is:
10
The loss for epoch 5
0.7527521088719368
The running loss is:
6.968377232551575
The number of items in train is:
10
The loss for epoch 6
0.6968377232551575
The running loss is:
6.07134684920311
The number of items in train is:
10
The loss for epoch 7
0.607134684920311
The running loss is:
5.064359068870544
The number of items in train is:
10
The loss for epoch 8
0.5064359068870544
The running loss is:
6.055943515151739
The number of items in train is:
10
The loss for epoch 9
0.6055943515151739
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.822945
48 30755 ... 6.611187
49 30756 ... 6.530975
50 30757 ... 4.915924
51 30758 ... 3.429251
52 30759 ... 2.679210
53 30760 ... 2.441298
54 30761 ... -1.963033
55 30762 ... -0.440692
56 30763 ... -0.592469
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0t6i24cz wandb: Agent Starting Run: u56nih5a with config: batch_size: 4 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u56nih5a
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
7.976818040013313
The number of items in train is:
10
The loss for epoch 0
0.7976818040013314
The running loss is:
33.770317524671555
The number of items in train is:
10
The loss for epoch 1
3.3770317524671554
The running loss is:
11.967144101858139
The number of items in train is:
10
The loss for epoch 2
1.1967144101858138
The running loss is:
9.863078862428665
The number of items in train is:
10
The loss for epoch 3
0.9863078862428665
The running loss is:
8.59804680943489
The number of items in train is:
10
The loss for epoch 4
0.859804680943489
The running loss is:
7.818701654672623
The number of items in train is:
10
The loss for epoch 5
0.7818701654672623
The running loss is:
7.778759300708771
The number of items in train is:
10
The loss for epoch 6
0.7778759300708771
The running loss is:
7.312741860747337
The number of items in train is:
10
The loss for epoch 7
0.7312741860747337
The running loss is:
6.312692016363144
The number of items in train is:
10
The loss for epoch 8
0.6312692016363144
The running loss is:
6.413540616631508
The number of items in train is:
10
The loss for epoch 9
0.6413540616631508
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.117382
48 30755 ... 10.954368
49 30756 ... 12.910322
50 30757 ... 12.665748
51 30758 ... 13.424576
52 30759 ... 14.412344
53 30760 ... 15.858442
54 30761 ... 12.063550
55 30762 ... 15.121051
56 30763 ... 15.554323
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u56nih5a wandb: Agent Starting Run: mxi4wxbt with config: batch_size: 4 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: mxi4wxbt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
39.859717562794685
The number of items in train is:
10
The loss for epoch 0
3.9859717562794685
The running loss is:
13.916883394122124
The number of items in train is:
10
The loss for epoch 1
1.3916883394122124
The running loss is:
14.028552146628499
The number of items in train is:
10
The loss for epoch 2
1.40285521466285
The running loss is:
12.02799230068922
The number of items in train is:
10
The loss for epoch 3
1.202799230068922
The running loss is:
9.812308438122272
The number of items in train is:
10
The loss for epoch 4
0.9812308438122272
The running loss is:
9.249479830265045
The number of items in train is:
10
The loss for epoch 5
0.9249479830265045
The running loss is:
8.068130537867546
The number of items in train is:
10
The loss for epoch 6
0.8068130537867546
The running loss is:
8.860792085528374
The number of items in train is:
10
The loss for epoch 7
0.8860792085528374
The running loss is:
7.412374511361122
The number of items in train is:
10
The loss for epoch 8
0.7412374511361122
The running loss is:
7.8305803835392
The number of items in train is:
10
The loss for epoch 9
0.78305803835392
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.818081
48 30755 ... 9.417191
49 30756 ... 9.138782
50 30757 ... 9.442849
51 30758 ... 8.466863
52 30759 ... 8.141625
53 30760 ... 8.005954
54 30761 ... 8.691431
55 30762 ... 7.704202
56 30763 ... 7.805756
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mxi4wxbt wandb: Agent Starting Run: fp70pn3z with config: batch_size: 4 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fp70pn3z
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
31.45028382539749
The number of items in train is:
10
The loss for epoch 0
3.145028382539749
The running loss is:
12.89564847946167
The number of items in train is:
10
The loss for epoch 1
1.289564847946167
The running loss is:
11.893807530403137
The number of items in train is:
10
The loss for epoch 2
1.1893807530403138
The running loss is:
8.323095485568047
The number of items in train is:
10
The loss for epoch 3
0.8323095485568046
The running loss is:
8.408325374126434
The number of items in train is:
10
The loss for epoch 4
0.8408325374126434
The running loss is:
7.324984163045883
The number of items in train is:
10
The loss for epoch 5
0.7324984163045883
The running loss is:
8.863726764917374
The number of items in train is:
10
The loss for epoch 6
0.8863726764917373
The running loss is:
8.59510800242424
The number of items in train is:
10
The loss for epoch 7
0.859510800242424
The running loss is:
7.816119492053986
The number of items in train is:
10
The loss for epoch 8
0.7816119492053986
The running loss is:
6.991639479994774
The number of items in train is:
10
The loss for epoch 9
0.6991639479994773
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.604881
48 30755 ... 10.088811
49 30756 ... 10.282960
50 30757 ... 10.789194
51 30758 ... 9.315967
52 30759 ... 8.543083
53 30760 ... 7.887885
54 30761 ... 9.119453
55 30762 ... 9.185229
56 30763 ... 9.172606
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fp70pn3z wandb: Agent Starting Run: n3wt2y70 with config: batch_size: 4 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: n3wt2y70
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
34.098082691431046
The number of items in train is:
10
The loss for epoch 0
3.4098082691431046
The running loss is:
14.255046874284744
The number of items in train is:
10
The loss for epoch 1
1.4255046874284745
The running loss is:
14.010826796293259
The number of items in train is:
10
The loss for epoch 2
1.4010826796293259
The running loss is:
8.812499105930328
The number of items in train is:
10
The loss for epoch 3
0.8812499105930328
The running loss is:
10.274688363075256
The number of items in train is:
10
The loss for epoch 4
1.0274688363075257
The running loss is:
8.562583446502686
The number of items in train is:
10
The loss for epoch 5
0.8562583446502685
The running loss is:
7.185037016868591
The number of items in train is:
10
The loss for epoch 6
0.7185037016868592
The running loss is:
6.902286410331726
The number of items in train is:
10
The loss for epoch 7
0.6902286410331726
The running loss is:
6.14476877823472
The number of items in train is:
10
The loss for epoch 8
0.614476877823472
The running loss is:
6.940630495548248
The number of items in train is:
10
The loss for epoch 9
0.6940630495548248
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 15.987806
48 30755 ... 14.906799
49 30756 ... 14.925628
50 30757 ... 15.739111
51 30758 ... 17.029638
52 30759 ... 17.821407
53 30760 ... 18.541513
54 30761 ... 21.510548
55 30762 ... 21.508347
56 30763 ... 21.507570
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n3wt2y70 wandb: Agent Starting Run: bcc38ycr with config: batch_size: 4 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bcc38ycr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.850830286741257
The number of items in train is:
10
The loss for epoch 0
1.2850830286741257
The running loss is:
7.531756274402142
The number of items in train is:
10
The loss for epoch 1
0.7531756274402142
The running loss is:
7.164153054356575
The number of items in train is:
10
The loss for epoch 2
0.7164153054356575
The running loss is:
6.104249902069569
The number of items in train is:
10
The loss for epoch 3
0.6104249902069568
The running loss is:
5.67718306183815
The number of items in train is:
10
The loss for epoch 4
0.567718306183815
The running loss is:
5.363151956349611
The number of items in train is:
10
The loss for epoch 5
0.5363151956349611
The running loss is:
5.421984151005745
The number of items in train is:
10
The loss for epoch 6
0.5421984151005745
The running loss is:
5.277610749006271
The number of items in train is:
10
The loss for epoch 7
0.5277610749006272
The running loss is:
5.469041176140308
The number of items in train is:
10
The loss for epoch 8
0.5469041176140308
The running loss is:
5.041734091937542
The number of items in train is:
10
The loss for epoch 9
0.5041734091937542
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.612688
48 30755 ... 9.810590
49 30756 ... 9.924997
50 30757 ... 10.803505
51 30758 ... 12.177807
52 30759 ... 12.428595
53 30760 ... 13.000287
54 30761 ... 12.871050
55 30762 ... 12.918545
56 30763 ... 13.982430
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bcc38ycr wandb: Agent Starting Run: gebuyenr with config: batch_size: 4 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: gebuyenr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.784172236919403
The number of items in train is:
10
The loss for epoch 0
1.3784172236919403
The running loss is:
8.965025827288628
The number of items in train is:
10
The loss for epoch 1
0.8965025827288627
The running loss is:
7.920389890670776
The number of items in train is:
10
The loss for epoch 2
0.7920389890670776
The running loss is:
6.930768981575966
The number of items in train is:
10
The loss for epoch 3
0.6930768981575965
The running loss is:
6.458241403102875
The number of items in train is:
10
The loss for epoch 4
0.6458241403102875
The running loss is:
5.874626487493515
The number of items in train is:
10
The loss for epoch 5
0.5874626487493515
The running loss is:
5.821754619479179
The number of items in train is:
10
The loss for epoch 6
0.5821754619479179
The running loss is:
5.629227995872498
The number of items in train is:
10
The loss for epoch 7
0.5629227995872498
The running loss is:
5.769639223814011
The number of items in train is:
10
The loss for epoch 8
0.576963922381401
The running loss is:
5.803562685847282
The number of items in train is:
10
The loss for epoch 9
0.5803562685847282
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.040811
48 30755 ... 12.388928
49 30756 ... 11.988900
50 30757 ... 13.375152
51 30758 ... 15.614386
52 30759 ... 17.559206
53 30760 ... 19.836933
54 30761 ... 20.253407
55 30762 ... 20.165487
56 30763 ... 21.959352
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gebuyenr wandb: Agent Starting Run: ifvuwc4s with config: batch_size: 4 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ifvuwc4s
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.077335000038147
The number of items in train is:
9
The loss for epoch 0
1.3419261111153498
The running loss is:
7.720571994781494
The number of items in train is:
9
The loss for epoch 1
0.8578413327534994
The running loss is:
7.231207340955734
The number of items in train is:
9
The loss for epoch 2
0.8034674823284149
The running loss is:
6.3102400451898575
The number of items in train is:
9
The loss for epoch 3
0.7011377827988731
The running loss is:
5.723727948963642
The number of items in train is:
9
The loss for epoch 4
0.6359697721070714
The running loss is:
5.507725924253464
The number of items in train is:
9
The loss for epoch 5
0.6119695471392738
The running loss is:
5.226244807243347
The number of items in train is:
9
The loss for epoch 6
0.580693867471483
The running loss is:
5.0174964517354965
The number of items in train is:
9
The loss for epoch 7
0.5574996057483885
The running loss is:
5.04413865506649
The number of items in train is:
9
The loss for epoch 8
0.5604598505629433
The running loss is:
4.887636784464121
The number of items in train is:
9
The loss for epoch 9
0.5430707538293468
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.133517
48 30755 ... 14.204868
49 30756 ... 8.201635
50 30757 ... 8.487048
51 30758 ... 8.313649
52 30759 ... 8.158344
53 30760 ... 8.212668
54 30761 ... 7.956340
55 30762 ... 7.777701
56 30763 ... 7.756563
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ifvuwc4s wandb: Agent Starting Run: gfkj4xmn with config: batch_size: 4 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: gfkj4xmn
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.208374172449112
The number of items in train is:
10
The loss for epoch 0
1.320837417244911
The running loss is:
14.000371232628822
The number of items in train is:
10
The loss for epoch 1
1.4000371232628823
The running loss is:
7.599640764296055
The number of items in train is:
10
The loss for epoch 2
0.7599640764296055
The running loss is:
6.7018884010612965
The number of items in train is:
10
The loss for epoch 3
0.6701888401061297
The running loss is:
5.82843029871583
The number of items in train is:
10
The loss for epoch 4
0.582843029871583
The running loss is:
5.561043694615364
The number of items in train is:
10
The loss for epoch 5
0.5561043694615364
The running loss is:
5.080736458301544
The number of items in train is:
10
The loss for epoch 6
0.5080736458301545
The running loss is:
4.953924670815468
The number of items in train is:
10
The loss for epoch 7
0.4953924670815468
The running loss is:
5.481087975203991
The number of items in train is:
10
The loss for epoch 8
0.5481087975203991
The running loss is:
4.529741728678346
The number of items in train is:
10
The loss for epoch 9
0.4529741728678346
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.652000
48 30755 ... 12.953487
49 30756 ... 12.495256
50 30757 ... 14.109031
51 30758 ... 15.218346
52 30759 ... 16.241440
53 30760 ... 17.719902
54 30761 ... 17.692379
55 30762 ... 16.954758
56 30763 ... 18.674665
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gfkj4xmn wandb: Agent Starting Run: p48n5h27 with config: batch_size: 4 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: p48n5h27
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.969248041510582
The number of items in train is:
10
The loss for epoch 0
1.2969248041510582
The running loss is:
18.971767611801624
The number of items in train is:
10
The loss for epoch 1
1.8971767611801624
The running loss is:
7.910560250282288
The number of items in train is:
10
The loss for epoch 2
0.7910560250282288
The running loss is:
8.072082966566086
The number of items in train is:
10
The loss for epoch 3
0.8072082966566085
The running loss is:
7.181809782981873
The number of items in train is:
10
The loss for epoch 4
0.7181809782981873
The running loss is:
5.9828749895095825
The number of items in train is:
10
The loss for epoch 5
0.5982874989509582
The running loss is:
5.653284996747971
The number of items in train is:
10
The loss for epoch 6
0.565328499674797
The running loss is:
5.712180733680725
The number of items in train is:
10
The loss for epoch 7
0.5712180733680725
The running loss is:
4.802202343940735
The number of items in train is:
10
The loss for epoch 8
0.48022023439407346
The running loss is:
4.912356749176979
The number of items in train is:
10
The loss for epoch 9
0.49123567491769793
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.621552
48 30755 ... 10.974742
49 30756 ... 12.895342
50 30757 ... 16.525156
51 30758 ... 19.239813
52 30759 ... 20.686008
53 30760 ... 22.838928
54 30761 ... 23.955635
55 30762 ... 23.857677
56 30763 ... 28.428850
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: p48n5h27 wandb: Agent Starting Run: 8nyyzakm with config: batch_size: 4 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8nyyzakm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.066332712769508
The number of items in train is:
9
The loss for epoch 0
1.3407036347521677
The running loss is:
13.345939487218857
The number of items in train is:
9
The loss for epoch 1
1.4828821652465396
The running loss is:
7.0621998608112335
The number of items in train is:
9
The loss for epoch 2
0.7846888734234704
The running loss is:
6.6326291263103485
The number of items in train is:
9
The loss for epoch 3
0.736958791812261
The running loss is:
6.007634565234184
The number of items in train is:
9
The loss for epoch 4
0.6675149516926872
The running loss is:
5.633084714412689
The number of items in train is:
9
The loss for epoch 5
0.6258983016014099
The running loss is:
5.117097146809101
The number of items in train is:
9
The loss for epoch 6
0.5685663496454557
The running loss is:
4.964767277240753
The number of items in train is:
9
The loss for epoch 7
0.5516408085823059
The running loss is:
4.961631417274475
The number of items in train is:
9
The loss for epoch 8
0.5512923796971639
The running loss is:
4.953397177159786
The number of items in train is:
9
The loss for epoch 9
0.5503774641288651
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.383920
48 30755 ... 15.534488
49 30756 ... 9.711837
50 30757 ... 9.893675
51 30758 ... 10.529510
52 30759 ... 11.202310
53 30760 ... 12.237284
54 30761 ... 12.017599
55 30762 ... 12.478189
56 30763 ... 12.300585
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8nyyzakm wandb: Agent Starting Run: ucaltidj with config: batch_size: 4 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ucaltidj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.098492935299873
The number of items in train is:
10
The loss for epoch 0
0.8098492935299874
The running loss is:
23.566280841827393
The number of items in train is:
10
The loss for epoch 1
2.356628084182739
The running loss is:
11.333626061677933
The number of items in train is:
10
The loss for epoch 2
1.1333626061677933
The running loss is:
9.972441203892231
The number of items in train is:
10
The loss for epoch 3
0.997244120389223
The running loss is:
8.263748623430729
The number of items in train is:
10
The loss for epoch 4
0.8263748623430729
The running loss is:
7.430231392383575
The number of items in train is:
10
The loss for epoch 5
0.7430231392383575
The running loss is:
7.192676857113838
The number of items in train is:
10
The loss for epoch 6
0.7192676857113838
The running loss is:
6.158903509378433
The number of items in train is:
10
The loss for epoch 7
0.6158903509378433
The running loss is:
6.380030982196331
The number of items in train is:
10
The loss for epoch 8
0.6380030982196331
The running loss is:
6.256686411798
The number of items in train is:
10
The loss for epoch 9
0.6256686411798
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.842103
48 30755 ... 9.856387
49 30756 ... 11.671286
50 30757 ... 11.879260
51 30758 ... 11.551217
52 30759 ... 12.265154
53 30760 ... 12.465170
54 30761 ... 12.783993
55 30762 ... 12.274730
56 30763 ... 13.479129
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ucaltidj wandb: Agent Starting Run: lch9dwmf with config: batch_size: 4 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: lch9dwmf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.695682540535927
The number of items in train is:
10
The loss for epoch 0
0.8695682540535927
The running loss is:
24.36949035525322
The number of items in train is:
10
The loss for epoch 1
2.436949035525322
The running loss is:
11.298262119293213
The number of items in train is:
10
The loss for epoch 2
1.1298262119293212
The running loss is:
10.062248289585114
The number of items in train is:
10
The loss for epoch 3
1.0062248289585114
The running loss is:
8.349945664405823
The number of items in train is:
10
The loss for epoch 4
0.8349945664405822
The running loss is:
7.397077739238739
The number of items in train is:
10
The loss for epoch 5
0.7397077739238739
The running loss is:
7.06380096077919
The number of items in train is:
10
The loss for epoch 6
0.706380096077919
The running loss is:
5.405614405870438
The number of items in train is:
10
The loss for epoch 7
0.5405614405870438
The running loss is:
6.062748953700066
The number of items in train is:
10
The loss for epoch 8
0.6062748953700066
The running loss is:
6.174377530813217
The number of items in train is:
10
The loss for epoch 9
0.6174377530813218
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 15.031854
48 30755 ... 10.359957
49 30756 ... 8.908915
50 30757 ... 11.616050
51 30758 ... 14.293598
52 30759 ... 13.883785
53 30760 ... 14.726389
54 30761 ... 14.138464
55 30762 ... 10.921678
56 30763 ... 14.764153
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lch9dwmf wandb: Agent Starting Run: hw10t2mp with config: batch_size: 4 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hw10t2mp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.075239360332489
The number of items in train is:
9
The loss for epoch 0
0.897248817814721
The running loss is:
21.2212555706501
The number of items in train is:
9
The loss for epoch 1
2.357917285627789
The running loss is:
9.465078294277191
The number of items in train is:
9
The loss for epoch 2
1.051675366030799
The running loss is:
9.448686242103577
The number of items in train is:
9
The loss for epoch 3
1.0498540269003973
The running loss is:
7.564092457294464
The number of items in train is:
9
The loss for epoch 4
0.8404547174771627
The running loss is:
6.826194107532501
The number of items in train is:
9
The loss for epoch 5
0.7584660119480557
The running loss is:
6.084612876176834
The number of items in train is:
9
The loss for epoch 6
0.6760680973529816
The running loss is:
5.682695642113686
The number of items in train is:
9
The loss for epoch 7
0.6314106269015206
The running loss is:
5.182469367980957
The number of items in train is:
9
The loss for epoch 8
0.5758299297756619
The running loss is:
5.210104294121265
The number of items in train is:
9
The loss for epoch 9
0.578900477124585
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.247068
48 30755 ... 14.380191
49 30756 ... 7.810470
50 30757 ... 7.876924
51 30758 ... 7.553281
52 30759 ... 8.155678
53 30760 ... 9.258459
54 30761 ... 6.550736
55 30762 ... 7.366041
56 30763 ... 6.780664
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hw10t2mp wandb: Agent Starting Run: lg5ngbrv with config: batch_size: 4 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: lg5ngbrv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
29.403677381575108
The number of items in train is:
10
The loss for epoch 0
2.940367738157511
The running loss is:
14.427762001752853
The number of items in train is:
10
The loss for epoch 1
1.4427762001752853
The running loss is:
9.362008228898048
The number of items in train is:
10
The loss for epoch 2
0.9362008228898049
The running loss is:
9.065472334623337
The number of items in train is:
10
The loss for epoch 3
0.9065472334623337
The running loss is:
8.686813779175282
The number of items in train is:
10
The loss for epoch 4
0.8686813779175282
The running loss is:
7.925582256168127
The number of items in train is:
10
The loss for epoch 5
0.7925582256168127
The running loss is:
8.436862831935287
The number of items in train is:
10
The loss for epoch 6
0.8436862831935287
The running loss is:
8.473329044878483
The number of items in train is:
10
The loss for epoch 7
0.8473329044878483
The running loss is:
8.727103762328625
The number of items in train is:
10
The loss for epoch 8
0.8727103762328625
The running loss is:
6.296208456158638
The number of items in train is:
10
The loss for epoch 9
0.6296208456158638
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.326419
48 30755 ... 9.670631
49 30756 ... 11.336937
50 30757 ... 16.110525
51 30758 ... 15.503344
52 30759 ... 14.850665
53 30760 ... 13.109945
54 30761 ... 13.666155
55 30762 ... 12.507251
56 30763 ... 13.980711
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lg5ngbrv wandb: Agent Starting Run: 3lup5gl4 with config: batch_size: 4 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 3lup5gl4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
39.57245537638664
The number of items in train is:
10
The loss for epoch 0
3.957245537638664
The running loss is:
10.280797213315964
The number of items in train is:
10
The loss for epoch 1
1.0280797213315964
The running loss is:
8.693240597844124
The number of items in train is:
10
The loss for epoch 2
0.8693240597844124
The running loss is:
7.663233906030655
The number of items in train is:
10
The loss for epoch 3
0.7663233906030655
The running loss is:
10.1103096306324
The number of items in train is:
10
The loss for epoch 4
1.0110309630632401
The running loss is:
18.52347093820572
The number of items in train is:
10
The loss for epoch 5
1.852347093820572
The running loss is:
10.631574869155884
The number of items in train is:
10
The loss for epoch 6
1.0631574869155884
The running loss is:
9.706002175807953
The number of items in train is:
10
The loss for epoch 7
0.9706002175807953
The running loss is:
8.629770785570145
The number of items in train is:
10
The loss for epoch 8
0.8629770785570144
The running loss is:
10.745264112949371
The number of items in train is:
10
The loss for epoch 9
1.074526411294937
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.510293
48 30755 ... 10.594899
49 30756 ... 10.696557
50 30757 ... 10.699605
51 30758 ... 10.587273
52 30759 ... 10.662291
53 30760 ... 10.781241
54 30761 ... 10.739531
55 30762 ... 10.732348
56 30763 ... 10.744804
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3lup5gl4 wandb: Agent Starting Run: jm38otv8 with config: batch_size: 4 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: jm38otv8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
30.17451411485672
The number of items in train is:
9
The loss for epoch 0
3.3527237905396357
The running loss is:
10.276994824409485
The number of items in train is:
9
The loss for epoch 1
1.141888313823276
The running loss is:
11.995807766914368
The number of items in train is:
9
The loss for epoch 2
1.332867529657152
The running loss is:
9.06753146648407
The number of items in train is:
9
The loss for epoch 3
1.0075034962760077
The running loss is:
8.199181139469147
The number of items in train is:
9
The loss for epoch 4
0.911020126607683
The running loss is:
6.896306037902832
The number of items in train is:
9
The loss for epoch 5
0.766256226433648
The running loss is:
6.741923570632935
The number of items in train is:
9
The loss for epoch 6
0.7491026189592149
The running loss is:
6.182898551225662
The number of items in train is:
9
The loss for epoch 7
0.6869887279139625
The running loss is:
7.065683364868164
The number of items in train is:
9
The loss for epoch 8
0.785075929429796
The running loss is:
6.285583019256592
The number of items in train is:
9
The loss for epoch 9
0.6983981132507324
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.558565
48 30755 ... 14.500316
49 30756 ... 11.803816
50 30757 ... 11.264889
51 30758 ... 11.637167
52 30759 ... 12.255816
53 30760 ... 13.166669
54 30761 ... 13.725646
55 30762 ... 13.694263
56 30763 ... 13.723823
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jm38otv8 wandb: Agent Starting Run: qz68dg80 with config: batch_size: 4 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: qz68dg80
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.469213277101517
The number of items in train is:
10
The loss for epoch 0
1.3469213277101517
The running loss is:
8.658868372440338
The number of items in train is:
10
The loss for epoch 1
0.8658868372440338
The running loss is:
6.475258469581604
The number of items in train is:
10
The loss for epoch 2
0.6475258469581604
The running loss is:
5.690110743045807
The number of items in train is:
10
The loss for epoch 3
0.5690110743045806
The running loss is:
5.235761940479279
The number of items in train is:
10
The loss for epoch 4
0.5235761940479279
The running loss is:
4.875370755791664
The number of items in train is:
10
The loss for epoch 5
0.4875370755791664
The running loss is:
4.801120638847351
The number of items in train is:
10
The loss for epoch 6
0.4801120638847351
The running loss is:
4.296569600701332
The number of items in train is:
10
The loss for epoch 7
0.4296569600701332
The running loss is:
3.9086484387516975
The number of items in train is:
10
The loss for epoch 8
0.39086484387516973
The running loss is:
4.612558275461197
The number of items in train is:
10
The loss for epoch 9
0.4612558275461197
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.746770
48 30755 ... 17.278393
49 30756 ... 20.268206
50 30757 ... 16.799969
51 30758 ... 18.261110
52 30759 ... 21.016077
53 30760 ... 25.866169
54 30761 ... 26.150158
55 30762 ... 27.741076
56 30763 ... 29.664261
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qz68dg80 wandb: Agent Starting Run: yc8vzk15 with config: batch_size: 4 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: yc8vzk15
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.648816645145416
The number of items in train is:
9
The loss for epoch 0
1.294312960571713
The running loss is:
7.589744657278061
The number of items in train is:
9
The loss for epoch 1
0.8433049619197845
The running loss is:
6.459843933582306
The number of items in train is:
9
The loss for epoch 2
0.7177604370647006
The running loss is:
5.186166860163212
The number of items in train is:
9
The loss for epoch 3
0.5762407622403569
The running loss is:
4.682988181710243
The number of items in train is:
9
The loss for epoch 4
0.520332020190027
The running loss is:
4.529887855052948
The number of items in train is:
9
The loss for epoch 5
0.5033208727836609
The running loss is:
4.174439802765846
The number of items in train is:
9
The loss for epoch 6
0.4638266447517607
The running loss is:
4.335402585566044
The number of items in train is:
9
The loss for epoch 7
0.4817113983962271
The running loss is:
4.026810601353645
The number of items in train is:
9
The loss for epoch 8
0.44742340015040505
The running loss is:
3.961600847542286
The number of items in train is:
9
The loss for epoch 9
0.4401778719491429
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.441639
48 30755 ... 10.630715
49 30756 ... 11.287188
50 30757 ... 6.068464
51 30758 ... 5.964826
52 30759 ... 4.343362
53 30760 ... 2.792007
54 30761 ... 2.465134
55 30762 ... 1.961774
56 30763 ... 1.201431
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yc8vzk15 wandb: Agent Starting Run: gb5pbrx8 with config: batch_size: 4 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: gb5pbrx8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.373695477843285
The number of items in train is:
9
The loss for epoch 0
1.263743941982587
The running loss is:
7.596046328544617
The number of items in train is:
9
The loss for epoch 1
0.8440051476160685
The running loss is:
7.026428073644638
The number of items in train is:
9
The loss for epoch 2
0.7807142304049598
The running loss is:
5.834165081381798
The number of items in train is:
9
The loss for epoch 3
0.6482405645979775
The running loss is:
5.792373478412628
The number of items in train is:
9
The loss for epoch 4
0.6435970531569587
The running loss is:
5.450645856559277
The number of items in train is:
9
The loss for epoch 5
0.6056273173954752
The running loss is:
5.28040973842144
The number of items in train is:
9
The loss for epoch 6
0.5867121931579378
The running loss is:
5.260490275919437
The number of items in train is:
9
The loss for epoch 7
0.5844989195466042
The running loss is:
5.06695993989706
The number of items in train is:
9
The loss for epoch 8
0.5629955488774512
The running loss is:
5.005925253033638
The number of items in train is:
9
The loss for epoch 9
0.5562139170037376
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.719934
48 30755 ... 10.537707
49 30756 ... 12.890726
50 30757 ... 5.602832
51 30758 ... 5.312798
52 30759 ... 3.378870
53 30760 ... 1.443442
54 30761 ... 0.235049
55 30762 ... -0.287667
56 30763 ... -0.960572
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gb5pbrx8 wandb: Agent Starting Run: 2ii41qnn with config: batch_size: 4 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 2ii41qnn
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.847636476159096
The number of items in train is:
10
The loss for epoch 0
1.1847636476159096
The running loss is:
19.28851977735758
The number of items in train is:
10
The loss for epoch 1
1.9288519777357578
The running loss is:
6.863035127520561
The number of items in train is:
10
The loss for epoch 2
0.6863035127520561
The running loss is:
6.861020892858505
The number of items in train is:
10
The loss for epoch 3
0.6861020892858505
The running loss is:
5.373749539256096
The number of items in train is:
10
The loss for epoch 4
0.5373749539256096
The running loss is:
4.984086461365223
The number of items in train is:
10
The loss for epoch 5
0.4984086461365223
The running loss is:
4.53009369969368
The number of items in train is:
10
The loss for epoch 6
0.45300936996936797
The running loss is:
4.434199392795563
The number of items in train is:
10
The loss for epoch 7
0.44341993927955625
The running loss is:
4.03824046254158
The number of items in train is:
10
The loss for epoch 8
0.403824046254158
The running loss is:
4.690671548247337
The number of items in train is:
10
The loss for epoch 9
0.4690671548247337
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.863157
48 30755 ... 16.795988
49 30756 ... 20.582083
50 30757 ... 17.093380
51 30758 ... 17.988306
52 30759 ... 20.010696
53 30760 ... 24.001680
54 30761 ... 24.718653
55 30762 ... 26.494963
56 30763 ... 28.380241
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2ii41qnn wandb: Agent Starting Run: 1wctf3h1 with config: batch_size: 4 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 1wctf3h1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.46183493733406
The number of items in train is:
9
The loss for epoch 0
1.162426104148229
The running loss is:
17.30639934539795
The number of items in train is:
9
The loss for epoch 1
1.9229332605997722
The running loss is:
6.3309420347213745
The number of items in train is:
9
The loss for epoch 2
0.7034380038579305
The running loss is:
6.377431869506836
The number of items in train is:
9
The loss for epoch 3
0.7086035410563151
The running loss is:
5.5489144921302795
The number of items in train is:
9
The loss for epoch 4
0.6165460546811422
The running loss is:
4.946435913443565
The number of items in train is:
9
The loss for epoch 5
0.5496039903826184
The running loss is:
4.314482182264328
The number of items in train is:
9
The loss for epoch 6
0.4793869091404809
The running loss is:
4.079594299197197
The number of items in train is:
9
The loss for epoch 7
0.4532882554663552
The running loss is:
4.3184704929590225
The number of items in train is:
9
The loss for epoch 8
0.4798300547732247
The running loss is:
3.7194052562117577
The number of items in train is:
9
The loss for epoch 9
0.4132672506901953
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.938203
48 30755 ... 10.590812
49 30756 ... 11.731659
50 30757 ... 7.816141
51 30758 ... 7.934283
52 30759 ... 7.898247
53 30760 ... 7.827030
54 30761 ... 7.770433
55 30762 ... 7.636737
56 30763 ... 7.446535
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1wctf3h1 wandb: Agent Starting Run: lnptcntk with config: batch_size: 4 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: lnptcntk
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.301906615495682
The number of items in train is:
9
The loss for epoch 0
1.2557674017217424
The running loss is:
13.34939444065094
The number of items in train is:
9
The loss for epoch 1
1.4832660489612155
The running loss is:
7.083951860666275
The number of items in train is:
9
The loss for epoch 2
0.7871057622962527
The running loss is:
6.721273362636566
The number of items in train is:
9
The loss for epoch 3
0.7468081514040629
The running loss is:
6.33242367208004
The number of items in train is:
9
The loss for epoch 4
0.7036026302311156
The running loss is:
5.559299543499947
The number of items in train is:
9
The loss for epoch 5
0.6176999492777718
The running loss is:
5.3248555809259415
The number of items in train is:
9
The loss for epoch 6
0.5916506201028824
The running loss is:
5.212460063397884
The number of items in train is:
9
The loss for epoch 7
0.5791622292664316
The running loss is:
5.161771774291992
The number of items in train is:
9
The loss for epoch 8
0.5735301971435547
The running loss is:
5.854519993066788
The number of items in train is:
9
The loss for epoch 9
0.6505022214518653
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.666964
48 30755 ... 7.844455
49 30756 ... 10.758030
50 30757 ... 4.357377
51 30758 ... 3.401670
52 30759 ... 0.159843
53 30760 ... -3.441156
54 30761 ... -5.457528
55 30762 ... -5.833113
56 30763 ... -5.806427
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lnptcntk wandb: Agent Starting Run: vt9wfc3i with config: batch_size: 4 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: vt9wfc3i
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.370520025491714
The number of items in train is:
10
The loss for epoch 0
0.9370520025491714
The running loss is:
24.28932160139084
The number of items in train is:
10
The loss for epoch 1
2.428932160139084
The running loss is:
11.215482264757156
The number of items in train is:
10
The loss for epoch 2
1.1215482264757157
The running loss is:
8.304980039596558
The number of items in train is:
10
The loss for epoch 3
0.8304980039596558
The running loss is:
5.969888746738434
The number of items in train is:
10
The loss for epoch 4
0.5969888746738434
The running loss is:
5.667651101946831
The number of items in train is:
10
The loss for epoch 5
0.5667651101946831
The running loss is:
5.531609956175089
The number of items in train is:
10
The loss for epoch 6
0.5531609956175089
The running loss is:
4.260201007127762
The number of items in train is:
10
The loss for epoch 7
0.4260201007127762
The running loss is:
4.308543294668198
The number of items in train is:
10
The loss for epoch 8
0.4308543294668198
The running loss is:
4.031116555444896
The number of items in train is:
10
The loss for epoch 9
0.40311165554448963
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.514585
48 30755 ... 13.957551
49 30756 ... 22.536795
50 30757 ... 19.147823
51 30758 ... 18.851774
52 30759 ... 16.785509
53 30760 ... 16.631109
54 30761 ... 14.371087
55 30762 ... 17.450026
56 30763 ... 23.144482
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vt9wfc3i wandb: Agent Starting Run: 79g5c2ih with config: batch_size: 4 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 79g5c2ih
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.218592584133148
The number of items in train is:
9
The loss for epoch 0
0.913176953792572
The running loss is:
22.594658076763153
The number of items in train is:
9
The loss for epoch 1
2.510517564084795
The running loss is:
8.755667477846146
The number of items in train is:
9
The loss for epoch 2
0.972851941982905
The running loss is:
7.895386904478073
The number of items in train is:
9
The loss for epoch 3
0.8772652116086748
The running loss is:
5.952311813831329
The number of items in train is:
9
The loss for epoch 4
0.6613679793145921
The running loss is:
5.395892843604088
The number of items in train is:
9
The loss for epoch 5
0.5995436492893431
The running loss is:
5.016872830688953
The number of items in train is:
9
The loss for epoch 6
0.5574303145209948
The running loss is:
4.522265180945396
The number of items in train is:
9
The loss for epoch 7
0.502473908993933
The running loss is:
4.903088375926018
The number of items in train is:
9
The loss for epoch 8
0.5447875973251131
The running loss is:
4.967217639088631
The number of items in train is:
9
The loss for epoch 9
0.5519130710098479
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.197464
48 30755 ... 14.589086
49 30756 ... 15.102975
50 30757 ... 11.490273
51 30758 ... 11.686521
52 30759 ... 12.958370
53 30760 ... 14.398232
54 30761 ... 14.449973
55 30762 ... 13.878452
56 30763 ... 13.028694
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 79g5c2ih wandb: Agent Starting Run: hun860ha with config: batch_size: 4 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hun860ha
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.466349959373474
The number of items in train is:
9
The loss for epoch 0
0.9407055510414971
The running loss is:
20.51015877723694
The number of items in train is:
9
The loss for epoch 1
2.2789065308041043
The running loss is:
9.455008566379547
The number of items in train is:
9
The loss for epoch 2
1.0505565073755052
The running loss is:
8.632069051265717
The number of items in train is:
9
The loss for epoch 3
0.9591187834739685
The running loss is:
7.387580871582031
The number of items in train is:
9
The loss for epoch 4
0.8208423190646701
The running loss is:
6.931646406650543
The number of items in train is:
9
The loss for epoch 5
0.7701829340722826
The running loss is:
6.353820636868477
The number of items in train is:
9
The loss for epoch 6
0.705980070763164
The running loss is:
6.147080808877945
The number of items in train is:
9
The loss for epoch 7
0.6830089787642161
The running loss is:
6.059936374425888
The number of items in train is:
9
The loss for epoch 8
0.6733262638250986
The running loss is:
5.553804494440556
The number of items in train is:
9
The loss for epoch 9
0.6170893882711729
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.846986
48 30755 ... 13.832122
49 30756 ... 14.052855
50 30757 ... 9.490732
51 30758 ... 9.761359
52 30759 ... 10.063552
53 30760 ... 10.918784
54 30761 ... 10.505589
55 30762 ... 10.037671
56 30763 ... 8.904584
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hun860ha wandb: Agent Starting Run: 56xnjmqw with config: batch_size: 4 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 56xnjmqw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
63.19029159843922
The number of items in train is:
10
The loss for epoch 0
6.319029159843922
The running loss is:
15.668059527873993
The number of items in train is:
10
The loss for epoch 1
1.5668059527873992
The running loss is:
6.7668338268995285
The number of items in train is:
10
The loss for epoch 2
0.6766833826899529
The running loss is:
10.653816670179367
The number of items in train is:
10
The loss for epoch 3
1.0653816670179368
The running loss is:
6.2057484947144985
The number of items in train is:
10
The loss for epoch 4
0.6205748494714498
The running loss is:
12.597524106502533
The number of items in train is:
10
The loss for epoch 5
1.2597524106502533
The running loss is:
8.133643388748169
The number of items in train is:
10
The loss for epoch 6
0.8133643388748169
The running loss is:
6.504064813256264
The number of items in train is:
10
The loss for epoch 7
0.6504064813256264
The running loss is:
7.600483626127243
The number of items in train is:
10
The loss for epoch 8
0.7600483626127243
The running loss is:
6.0942140482366085
The number of items in train is:
10
The loss for epoch 9
0.6094214048236608
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 17.412844
48 30755 ... 16.113131
49 30756 ... 17.652231
50 30757 ... 17.093540
51 30758 ... 17.538973
52 30759 ... 18.912992
53 30760 ... 22.012920
54 30761 ... 22.796741
55 30762 ... 23.825220
56 30763 ... 24.379248
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 56xnjmqw wandb: Agent Starting Run: rjlb3x25 with config: batch_size: 4 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: rjlb3x25
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
47.18400213122368
The number of items in train is:
9
The loss for epoch 0
5.242666903469297
The running loss is:
7.782240986824036
The number of items in train is:
9
The loss for epoch 1
0.8646934429804484
The running loss is:
13.350460350513458
The number of items in train is:
9
The loss for epoch 2
1.4833844833903842
The running loss is:
10.830940991640091
The number of items in train is:
9
The loss for epoch 3
1.20343788796001
The running loss is:
8.378268256783485
The number of items in train is:
9
The loss for epoch 4
0.9309186951981651
The running loss is:
7.522539705038071
The number of items in train is:
9
The loss for epoch 5
0.83583774500423
The running loss is:
7.092203080654144
The number of items in train is:
9
The loss for epoch 6
0.7880225645171272
The running loss is:
5.928473547101021
The number of items in train is:
9
The loss for epoch 7
0.6587192830112245
The running loss is:
5.759520620107651
The number of items in train is:
9
The loss for epoch 8
0.6399467355675168
The running loss is:
5.335961684584618
The number of items in train is:
9
The loss for epoch 9
0.5928846316205131
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.474265
48 30755 ... 14.597093
49 30756 ... 14.583648
50 30757 ... 10.177814
51 30758 ... 10.120189
52 30759 ... 9.762475
53 30760 ... 9.834273
54 30761 ... 9.889601
55 30762 ... 10.552725
56 30763 ... 8.368625
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rjlb3x25 wandb: Agent Starting Run: r1hloomg with config: batch_size: 4 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: r1hloomg
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
35.278807163238525
The number of items in train is:
9
The loss for epoch 0
3.9198674625820584
The running loss is:
9.09990394115448
The number of items in train is:
9
The loss for epoch 1
1.0111004379060533
The running loss is:
8.631413072347641
The number of items in train is:
9
The loss for epoch 2
0.9590458969275156
The running loss is:
13.801436424255371
The number of items in train is:
9
The loss for epoch 3
1.5334929360283747
The running loss is:
11.059120297431946
The number of items in train is:
9
The loss for epoch 4
1.228791144159105
The running loss is:
12.807693928480148
The number of items in train is:
9
The loss for epoch 5
1.423077103164461
The running loss is:
8.163722217082977
The number of items in train is:
9
The loss for epoch 6
0.907080246342553
The running loss is:
8.258003741502762
The number of items in train is:
9
The loss for epoch 7
0.9175559712780846
The running loss is:
7.6043756902217865
The number of items in train is:
9
The loss for epoch 8
0.8449306322468652
The running loss is:
7.030919551849365
The number of items in train is:
9
The loss for epoch 9
0.7812132835388184
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.151881
48 30755 ... 11.383740
49 30756 ... 11.417962
50 30757 ... 11.303598
51 30758 ... 11.302509
52 30759 ... 11.487692
53 30760 ... 11.680331
54 30761 ... 11.406602
55 30762 ... 11.407322
56 30763 ... 11.404839
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r1hloomg wandb: Agent Starting Run: y0bnlpuy with config: batch_size: 4 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: y0bnlpuy
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.633945550769567
The number of items in train is:
9
The loss for epoch 0
1.181549505641063
The running loss is:
12.043411642313004
The number of items in train is:
9
The loss for epoch 1
1.3381568491458893
The running loss is:
5.877998441457748
The number of items in train is:
9
The loss for epoch 2
0.6531109379397498
The running loss is:
5.546243727207184
The number of items in train is:
9
The loss for epoch 3
0.6162493030230204
The running loss is:
5.403127163648605
The number of items in train is:
9
The loss for epoch 4
0.6003474626276228
The running loss is:
4.643219918012619
The number of items in train is:
9
The loss for epoch 5
0.5159133242236243
The running loss is:
4.852768741548061
The number of items in train is:
9
The loss for epoch 6
0.5391965268386735
The running loss is:
4.382803924381733
The number of items in train is:
9
The loss for epoch 7
0.4869782138201926
The running loss is:
4.16484721750021
The number of items in train is:
9
The loss for epoch 8
0.4627608019444678
The running loss is:
4.4322224371135235
The number of items in train is:
9
The loss for epoch 9
0.4924691596792804
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.033802
48 30755 ... 9.551357
49 30756 ... 10.077868
50 30757 ... 9.963331
51 30758 ... 6.366199
52 30759 ... 6.216858
53 30760 ... 5.372510
54 30761 ... 4.884486
55 30762 ... 4.517594
56 30763 ... 4.314028
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y0bnlpuy wandb: Agent Starting Run: owmfh421 with config: batch_size: 4 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: owmfh421
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.215542949736118
The number of items in train is:
9
The loss for epoch 0
1.2461714388595686
The running loss is:
9.463058114051819
The number of items in train is:
9
The loss for epoch 1
1.0514509015613132
The running loss is:
6.107879787683487
The number of items in train is:
9
The loss for epoch 2
0.6786533097426096
The running loss is:
5.39974407851696
The number of items in train is:
9
The loss for epoch 3
0.5999715642796623
The running loss is:
5.072701074182987
The number of items in train is:
9
The loss for epoch 4
0.5636334526869986
The running loss is:
4.804857462644577
The number of items in train is:
9
The loss for epoch 5
0.533873051404953
The running loss is:
4.5060970187187195
The number of items in train is:
9
The loss for epoch 6
0.5006774465243021
The running loss is:
4.700375184416771
The number of items in train is:
9
The loss for epoch 7
0.5222639093796412
The running loss is:
4.428327962756157
The number of items in train is:
9
The loss for epoch 8
0.49203644030623966
The running loss is:
4.5398461520671844
The number of items in train is:
9
The loss for epoch 9
0.5044273502296872
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.511998
48 30755 ... 5.250092
49 30756 ... 5.816338
50 30757 ... 5.612596
51 30758 ... 0.421234
52 30759 ... -1.497605
53 30760 ... -7.030499
54 30761 ... -8.206348
55 30762 ... -9.200907
56 30763 ... -9.880840
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: owmfh421 wandb: Agent Starting Run: 9gl4dblh with config: batch_size: 4 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 9gl4dblh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.968374609947205
The number of items in train is:
9
The loss for epoch 0
1.218708289994134
The running loss is:
7.037350654602051
The number of items in train is:
9
The loss for epoch 1
0.781927850511339
The running loss is:
6.37801668047905
The number of items in train is:
9
The loss for epoch 2
0.7086685200532278
The running loss is:
5.6258958876132965
The number of items in train is:
9
The loss for epoch 3
0.6250995430681441
The running loss is:
5.45712573826313
The number of items in train is:
9
The loss for epoch 4
0.6063473042514589
The running loss is:
5.067378714680672
The number of items in train is:
9
The loss for epoch 5
0.5630420794089636
The running loss is:
4.6998710706830025
The number of items in train is:
9
The loss for epoch 6
0.5222078967425559
The running loss is:
4.821414604783058
The number of items in train is:
9
The loss for epoch 7
0.5357127338647842
The running loss is:
4.696104887872934
The number of items in train is:
9
The loss for epoch 8
0.5217894319858816
The running loss is:
4.9355600625276566
The number of items in train is:
9
The loss for epoch 9
0.548395562503073
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 4.753484
48 30755 ... 5.158859
49 30756 ... 5.436313
50 30757 ... 5.256255
51 30758 ... -0.213982
52 30759 ... -2.439097
53 30760 ... -8.436878
54 30761 ... -9.941109
55 30762 ... -11.239862
56 30763 ... -12.347157
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9gl4dblh wandb: Agent Starting Run: k8zdpd46 with config: batch_size: 4 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: k8zdpd46
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.622326582670212
The number of items in train is:
9
The loss for epoch 0
1.069147398074468
The running loss is:
27.29498302936554
The number of items in train is:
9
The loss for epoch 1
3.0327758921517267
The running loss is:
7.484041184186935
The number of items in train is:
9
The loss for epoch 2
0.8315601315763261
The running loss is:
8.233914986252785
The number of items in train is:
9
The loss for epoch 3
0.9148794429169761
The running loss is:
5.771057903766632
The number of items in train is:
9
The loss for epoch 4
0.6412286559740702
The running loss is:
5.484783336520195
The number of items in train is:
9
The loss for epoch 5
0.6094203707244661
The running loss is:
5.26647499576211
The number of items in train is:
9
The loss for epoch 6
0.5851638884180121
The running loss is:
4.466490536928177
The number of items in train is:
9
The loss for epoch 7
0.49627672632535297
The running loss is:
4.091578543186188
The number of items in train is:
9
The loss for epoch 8
0.4546198381317986
The running loss is:
4.385637752711773
The number of items in train is:
9
The loss for epoch 9
0.4872930836346414
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.332860
48 30755 ... 10.200597
49 30756 ... 10.226647
50 30757 ... 9.453783
51 30758 ... 7.146721
52 30759 ... 6.883693
53 30760 ... 6.543474
54 30761 ... 5.816170
55 30762 ... 5.922008
56 30763 ... 5.386109
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: k8zdpd46 wandb: Agent Starting Run: l1ctof91 with config: batch_size: 4 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: l1ctof91
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.580014735460281
The number of items in train is:
9
The loss for epoch 0
1.064446081717809
The running loss is:
21.697373241186142
The number of items in train is:
9
The loss for epoch 1
2.4108192490206823
The running loss is:
6.6545195281505585
The number of items in train is:
9
The loss for epoch 2
0.7393910586833954
The running loss is:
7.011622667312622
The number of items in train is:
9
The loss for epoch 3
0.779069185256958
The running loss is:
6.083614349365234
The number of items in train is:
9
The loss for epoch 4
0.6759571499294705
The running loss is:
5.649204224348068
The number of items in train is:
9
The loss for epoch 5
0.6276893582608964
The running loss is:
5.127370245754719
The number of items in train is:
9
The loss for epoch 6
0.5697078050838577
The running loss is:
4.944306641817093
The number of items in train is:
9
The loss for epoch 7
0.5493674046463437
The running loss is:
4.8338189907372
The number of items in train is:
9
The loss for epoch 8
0.5370909989707999
The running loss is:
4.484746187925339
The number of items in train is:
9
The loss for epoch 9
0.4983051319917043
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 4.635915
48 30755 ... 5.037758
49 30756 ... 5.179454
50 30757 ... 5.334713
51 30758 ... 1.140849
52 30759 ... -0.616794
53 30760 ... -5.523585
54 30761 ... -6.937500
55 30762 ... -7.549229
56 30763 ... -7.830435
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l1ctof91 wandb: Agent Starting Run: u10rjkpr with config: batch_size: 4 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u10rjkpr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.579345598816872
The number of items in train is:
9
The loss for epoch 0
1.1754828443129857
The running loss is:
13.758408069610596
The number of items in train is:
9
The loss for epoch 1
1.5287120077345107
The running loss is:
6.689704149961472
The number of items in train is:
9
The loss for epoch 2
0.7433004611068301
The running loss is:
6.441909082233906
The number of items in train is:
9
The loss for epoch 3
0.7157676758037673
The running loss is:
5.889819331467152
The number of items in train is:
9
The loss for epoch 4
0.6544243701630168
The running loss is:
5.225266307592392
The number of items in train is:
9
The loss for epoch 5
0.5805851452880435
The running loss is:
4.707424312829971
The number of items in train is:
9
The loss for epoch 6
0.5230471458699968
The running loss is:
4.644587963819504
The number of items in train is:
9
The loss for epoch 7
0.5160653293132782
The running loss is:
4.423424337059259
The number of items in train is:
9
The loss for epoch 8
0.4914915930065844
The running loss is:
4.801369518041611
The number of items in train is:
9
The loss for epoch 9
0.5334855020046234
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.572619
48 30755 ... 5.447958
49 30756 ... 5.573647
50 30757 ... 5.955884
51 30758 ... 1.513768
52 30759 ... -0.038620
53 30760 ... -4.731401
54 30761 ... -5.841568
55 30762 ... -6.382008
56 30763 ... -6.736419
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u10rjkpr wandb: Agent Starting Run: mhp5jf5e with config: batch_size: 4 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: mhp5jf5e
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.49449360370636
The number of items in train is:
9
The loss for epoch 0
1.6104992893007066
The running loss is:
19.521971058100462
The number of items in train is:
9
The loss for epoch 1
2.1691078953444958
The running loss is:
28.291439056396484
The number of items in train is:
9
The loss for epoch 2
3.143493228488498
The running loss is:
8.388818830251694
The number of items in train is:
9
The loss for epoch 3
0.9320909811390771
The running loss is:
8.282284513115883
The number of items in train is:
9
The loss for epoch 4
0.9202538347906537
The running loss is:
6.225587673485279
The number of items in train is:
9
The loss for epoch 5
0.6917319637205865
The running loss is:
5.497670985758305
The number of items in train is:
9
The loss for epoch 6
0.6108523317509227
The running loss is:
4.806649524718523
The number of items in train is:
9
The loss for epoch 7
0.5340721694131693
The running loss is:
4.585236996412277
The number of items in train is:
9
The loss for epoch 8
0.5094707773791419
The running loss is:
4.70761264488101
The number of items in train is:
9
The loss for epoch 9
0.5230680716534456
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.213211
48 30755 ... 6.962625
49 30756 ... 7.404693
50 30757 ... 8.399524
51 30758 ... 1.793925
52 30759 ... 0.937240
53 30760 ... -3.075130
54 30761 ... -4.972503
55 30762 ... -4.848470
56 30763 ... -5.870366
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mhp5jf5e wandb: Agent Starting Run: l26ko7a1 with config: batch_size: 4 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: l26ko7a1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.378090545535088
The number of items in train is:
9
The loss for epoch 0
1.2642322828372319
The running loss is:
20.013391137123108
The number of items in train is:
9
The loss for epoch 1
2.223710126347012
The running loss is:
19.87523329257965
The number of items in train is:
9
The loss for epoch 2
2.2083592547310724
The running loss is:
8.844613701105118
The number of items in train is:
9
The loss for epoch 3
0.9827348556783464
The running loss is:
7.205383747816086
The number of items in train is:
9
The loss for epoch 4
0.8005981942017873
The running loss is:
6.940165609121323
The number of items in train is:
9
The loss for epoch 5
0.7711295121245914
The running loss is:
6.24945005774498
The number of items in train is:
9
The loss for epoch 6
0.6943833397494422
The running loss is:
5.91395029425621
The number of items in train is:
9
The loss for epoch 7
0.65710558825069
The running loss is:
5.396865144371986
The number of items in train is:
9
The loss for epoch 8
0.5996516827079985
The running loss is:
5.062415450811386
The number of items in train is:
9
The loss for epoch 9
0.5624906056457095
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.514519
48 30755 ... 9.442804
49 30756 ... 8.812165
50 30757 ... 9.532930
51 30758 ... 6.297042
52 30759 ... 6.181820
53 30760 ... 5.386303
54 30761 ... 3.235852
55 30762 ... 3.117307
56 30763 ... 3.085574
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l26ko7a1 wandb: Agent Starting Run: zotbismr with config: batch_size: 4 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: zotbismr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.956711173057556
The number of items in train is:
9
The loss for epoch 0
0.9951901303397285
The running loss is:
20.03506526350975
The number of items in train is:
9
The loss for epoch 1
2.2261183626121945
The running loss is:
10.61062902212143
The number of items in train is:
9
The loss for epoch 2
1.1789587802357144
The running loss is:
7.9828891307115555
The number of items in train is:
9
The loss for epoch 3
0.8869876811901728
The running loss is:
7.088197961449623
The number of items in train is:
9
The loss for epoch 4
0.7875775512721803
The running loss is:
6.779843673110008
The number of items in train is:
9
The loss for epoch 5
0.7533159636788898
The running loss is:
6.002784684300423
The number of items in train is:
9
The loss for epoch 6
0.6669760760333803
The running loss is:
5.491729207336903
The number of items in train is:
9
The loss for epoch 7
0.6101921341485448
The running loss is:
5.527640491724014
The number of items in train is:
9
The loss for epoch 8
0.6141822768582238
The running loss is:
6.085138563066721
The number of items in train is:
9
The loss for epoch 9
0.6761265070074134
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.490681
48 30755 ... 13.582205
49 30756 ... 13.004211
50 30757 ... 12.755482
51 30758 ... 12.320765
52 30759 ... 12.612151
53 30760 ... 13.293688
54 30761 ... 13.494370
55 30762 ... 13.886261
56 30763 ... 13.653646
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zotbismr wandb: Agent Starting Run: dvll38mr with config: batch_size: 4 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: dvll38mr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
98.88792389631271
The number of items in train is:
9
The loss for epoch 0
10.987547099590302
The running loss is:
8.609584867954254
The number of items in train is:
9
The loss for epoch 1
0.956620540883806
The running loss is:
9.498519219458103
The number of items in train is:
9
The loss for epoch 2
1.0553910243842337
The running loss is:
49.756335735321045
The number of items in train is:
9
The loss for epoch 3
5.528481748369005
The running loss is:
15.944260041695088
The number of items in train is:
9
The loss for epoch 4
1.7715844490772321
The running loss is:
18.559796810150146
The number of items in train is:
9
The loss for epoch 5
2.0621996455722384
The running loss is:
7.868879586458206
The number of items in train is:
9
The loss for epoch 6
0.8743199540509118
The running loss is:
6.104154862463474
The number of items in train is:
9
The loss for epoch 7
0.6782394291626083
The running loss is:
7.538334250450134
The number of items in train is:
9
The loss for epoch 8
0.8375926944944594
The running loss is:
6.918812483549118
The number of items in train is:
9
The loss for epoch 9
0.7687569426165687
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.731135
48 30755 ... 9.728546
49 30756 ... 10.310928
50 30757 ... 10.316441
51 30758 ... 7.959233
52 30759 ... 7.956962
53 30760 ... 7.942179
54 30761 ... 6.841368
55 30762 ... 6.677052
56 30763 ... 6.692796
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: dvll38mr wandb: Agent Starting Run: rya2yy5p with config: batch_size: 4 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: rya2yy5p
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
67.89308589696884
The number of items in train is:
9
The loss for epoch 0
7.543676210774316
The running loss is:
9.431407779455185
The number of items in train is:
9
The loss for epoch 1
1.0479341977172427
The running loss is:
21.126766741275787
The number of items in train is:
9
The loss for epoch 2
2.3474185268084207
The running loss is:
14.993719905614853
The number of items in train is:
9
The loss for epoch 3
1.6659688784016504
The running loss is:
7.41693702340126
The number of items in train is:
9
The loss for epoch 4
0.8241041137112511
The running loss is:
8.626804292201996
The number of items in train is:
9
The loss for epoch 5
0.9585338102446662
The running loss is:
7.170477196574211
The number of items in train is:
9
The loss for epoch 6
0.7967196885082457
The running loss is:
7.380770206451416
The number of items in train is:
9
The loss for epoch 7
0.8200855784946017
The running loss is:
6.92872542142868
The number of items in train is:
9
The loss for epoch 8
0.7698583801587423
The running loss is:
6.632938742637634
The number of items in train is:
9
The loss for epoch 9
0.7369931936264038
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.066799
48 30755 ... 11.078013
49 30756 ... 11.082559
50 30757 ... 11.086118
51 30758 ... 10.130918
52 30759 ... 10.135627
53 30760 ... 10.872349
54 30761 ... 9.913726
55 30762 ... 9.913918
56 30763 ... 9.914637
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rya2yy5p wandb: Agent Starting Run: 8oqgctmv with config: batch_size: 4 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8oqgctmv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
46.47122222185135
The number of items in train is:
9
The loss for epoch 0
5.163469135761261
The running loss is:
8.845713376998901
The number of items in train is:
9
The loss for epoch 1
0.9828570418887668
The running loss is:
13.030948475003242
The number of items in train is:
9
The loss for epoch 2
1.447883163889249
The running loss is:
10.48940259218216
The number of items in train is:
9
The loss for epoch 3
1.165489176909129
The running loss is:
9.511059552431107
The number of items in train is:
9
The loss for epoch 4
1.0567843947145674
The running loss is:
8.09024153649807
The number of items in train is:
9
The loss for epoch 5
0.8989157262775633
The running loss is:
6.7674222737550735
The number of items in train is:
9
The loss for epoch 6
0.7519358081950082
The running loss is:
6.153109893202782
The number of items in train is:
9
The loss for epoch 7
0.6836788770225313
The running loss is:
6.054163038730621
The number of items in train is:
9
The loss for epoch 8
0.6726847820811801
The running loss is:
5.372741438448429
The number of items in train is:
9
The loss for epoch 9
0.5969712709387144
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.541071
48 30755 ... 12.220772
49 30756 ... 11.060917
50 30757 ... 10.666188
51 30758 ... 3.418077
52 30759 ... 3.772269
53 30760 ... 0.733020
54 30761 ... 1.369237
55 30762 ... 1.944399
56 30763 ... 1.421969
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8oqgctmv wandb: Agent Starting Run: vtgyuhtf with config: batch_size: 4 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: vtgyuhtf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.348638638854027
The number of items in train is:
9
The loss for epoch 0
1.2609598487615585
The running loss is:
6.918910779058933
The number of items in train is:
9
The loss for epoch 1
0.7687678643398814
The running loss is:
5.745432838797569
The number of items in train is:
9
The loss for epoch 2
0.6383814265330633
The running loss is:
4.999900542199612
The number of items in train is:
9
The loss for epoch 3
0.5555445046888458
The running loss is:
4.773765811696649
The number of items in train is:
9
The loss for epoch 4
0.5304184235218499
The running loss is:
4.680868253111839
The number of items in train is:
9
The loss for epoch 5
0.5200964725679822
The running loss is:
4.301170352846384
The number of items in train is:
9
The loss for epoch 6
0.47790781698293155
The running loss is:
4.601465173065662
The number of items in train is:
9
The loss for epoch 7
0.5112739081184069
The running loss is:
4.934664955362678
The number of items in train is:
9
The loss for epoch 8
0.5482961061514087
The running loss is:
4.621857643127441
The number of items in train is:
9
The loss for epoch 9
0.5135397381252713
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
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44 30751 ... 0.000000
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46 30753 ... 0.000000
47 30754 ... 6.836509
48 30755 ... 8.574735
49 30756 ... 11.337667
50 30757 ... 10.399076
51 30758 ... 6.875823
52 30759 ... 5.910570
53 30760 ... 5.708830
54 30761 ... 4.988645
55 30762 ... 4.351829
56 30763 ... 4.867961
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vtgyuhtf wandb: Agent Starting Run: qthc3jrw with config: batch_size: 4 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: qthc3jrw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.358599215745926
The number of items in train is:
9
The loss for epoch 0
1.3731776906384363
The running loss is:
8.195348471403122
The number of items in train is:
9
The loss for epoch 1
0.9105942746003469
The running loss is:
7.318853735923767
The number of items in train is:
9
The loss for epoch 2
0.8132059706581963
The running loss is:
6.295140668749809
The number of items in train is:
9
The loss for epoch 3
0.6994600743055344
The running loss is:
6.144186645746231
The number of items in train is:
9
The loss for epoch 4
0.6826874050829146
The running loss is:
5.869756370782852
The number of items in train is:
9
The loss for epoch 5
0.6521951523092058
The running loss is:
5.804843842983246
The number of items in train is:
9
The loss for epoch 6
0.6449826492203606
The running loss is:
5.551393002271652
The number of items in train is:
9
The loss for epoch 7
0.6168214446968503
The running loss is:
5.521760046482086
The number of items in train is:
9
The loss for epoch 8
0.6135288940535651
The running loss is:
5.504636391997337
The number of items in train is:
9
The loss for epoch 9
0.6116262657774819
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.424033
48 30755 ... 11.064072
49 30756 ... 11.643181
50 30757 ... 12.372051
51 30758 ... 12.407243
52 30759 ... 8.644774
53 30760 ... 8.674614
54 30761 ... 9.206502
55 30762 ... 8.878454
56 30763 ... 8.787256
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qthc3jrw wandb: Agent Starting Run: nudj0ttj with config: batch_size: 4 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: nudj0ttj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.974797561764717
The number of items in train is:
9
The loss for epoch 0
1.3305330624183018
The running loss is:
7.871524661779404
The number of items in train is:
9
The loss for epoch 1
0.8746138513088226
The running loss is:
6.378603428602219
The number of items in train is:
9
The loss for epoch 2
0.7087337142891355
The running loss is:
5.855801060795784
The number of items in train is:
9
The loss for epoch 3
0.6506445623106427
The running loss is:
5.593401655554771
The number of items in train is:
9
The loss for epoch 4
0.621489072839419
The running loss is:
5.430000275373459
The number of items in train is:
9
The loss for epoch 5
0.6033333639303843
The running loss is:
5.198335066437721
The number of items in train is:
9
The loss for epoch 6
0.5775927851597468
The running loss is:
5.2052818685770035
The number of items in train is:
9
The loss for epoch 7
0.5783646520641115
The running loss is:
5.29455591738224
The number of items in train is:
9
The loss for epoch 8
0.588283990820249
The running loss is:
5.005378872156143
The number of items in train is:
9
The loss for epoch 9
0.5561532080173492
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.795309
48 30755 ... 9.963115
49 30756 ... 11.581796
50 30757 ... 11.518932
51 30758 ... 10.245250
52 30759 ... 8.156085
53 30760 ... 8.071309
54 30761 ... 8.587109
55 30762 ... 8.115870
56 30763 ... 8.071095
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nudj0ttj wandb: Agent Starting Run: pqquxpyi with config: batch_size: 4 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: pqquxpyi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.936804950237274
The number of items in train is:
9
The loss for epoch 0
1.326311661137475
The running loss is:
13.103957504034042
The number of items in train is:
9
The loss for epoch 1
1.4559952782260046
The running loss is:
6.130839288234711
The number of items in train is:
9
The loss for epoch 2
0.6812043653594123
The running loss is:
5.423560082912445
The number of items in train is:
9
The loss for epoch 3
0.6026177869902717
The running loss is:
5.0311368107795715
The number of items in train is:
9
The loss for epoch 4
0.5590152011977302
The running loss is:
4.549448646605015
The number of items in train is:
9
The loss for epoch 5
0.5054942940672239
The running loss is:
4.158376228064299
The number of items in train is:
9
The loss for epoch 6
0.4620418031182554
The running loss is:
5.161359757184982
The number of items in train is:
9
The loss for epoch 7
0.573484417464998
The running loss is:
5.153440713882446
The number of items in train is:
9
The loss for epoch 8
0.5726045237647163
The running loss is:
3.981059141457081
The number of items in train is:
9
The loss for epoch 9
0.4423399046063423
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.477754
48 30755 ... 8.494497
49 30756 ... 12.196461
50 30757 ... 10.884727
51 30758 ... 7.412595
52 30759 ... 7.065908
53 30760 ... 7.101405
54 30761 ... 6.012889
55 30762 ... 5.877822
56 30763 ... 7.438658
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pqquxpyi wandb: Agent Starting Run: 68xo9ypq with config: batch_size: 4 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 68xo9ypq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.190880864858627
The number of items in train is:
9
The loss for epoch 0
1.3545423183176253
The running loss is:
13.892218500375748
The number of items in train is:
9
The loss for epoch 1
1.543579833375083
The running loss is:
6.900015220046043
The number of items in train is:
9
The loss for epoch 2
0.7666683577828937
The running loss is:
6.897568985819817
The number of items in train is:
9
The loss for epoch 3
0.7663965539799796
The running loss is:
6.506961166858673
The number of items in train is:
9
The loss for epoch 4
0.7229956852065192
The running loss is:
6.165369838476181
The number of items in train is:
9
The loss for epoch 5
0.6850410931640201
The running loss is:
5.86061418056488
The number of items in train is:
9
The loss for epoch 6
0.6511793533960978
The running loss is:
5.5902515053749084
The number of items in train is:
9
The loss for epoch 7
0.6211390561527677
The running loss is:
5.628728866577148
The number of items in train is:
9
The loss for epoch 8
0.6254143185085721
The running loss is:
5.315730541944504
The number of items in train is:
9
The loss for epoch 9
0.5906367268827226
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.205215
48 30755 ... 10.191205
49 30756 ... 10.337317
50 30757 ... 10.732488
51 30758 ... 11.198917
52 30759 ... 8.658087
53 30760 ... 8.819209
54 30761 ... 8.749974
55 30762 ... 8.259215
56 30763 ... 8.356953
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 68xo9ypq wandb: Agent Starting Run: fy82xr6x with config: batch_size: 4 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: fy82xr6x
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.067734479904175
The number of items in train is:
9
The loss for epoch 0
1.2297482755449083
The running loss is:
15.965270072221756
The number of items in train is:
9
The loss for epoch 1
1.7739188969135284
The running loss is:
6.704161122441292
The number of items in train is:
9
The loss for epoch 2
0.7449067913823657
The running loss is:
6.657948046922684
The number of items in train is:
9
The loss for epoch 3
0.7397720052136315
The running loss is:
6.264713495969772
The number of items in train is:
9
The loss for epoch 4
0.6960792773299747
The running loss is:
5.739080086350441
The number of items in train is:
9
The loss for epoch 5
0.637675565150049
The running loss is:
5.670556038618088
The number of items in train is:
9
The loss for epoch 6
0.6300617820686765
The running loss is:
5.386943072080612
The number of items in train is:
9
The loss for epoch 7
0.5985492302311791
The running loss is:
5.308087810873985
The number of items in train is:
9
The loss for epoch 8
0.589787534541554
The running loss is:
4.992166683077812
The number of items in train is:
9
The loss for epoch 9
0.5546851870086458
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.993382
48 30755 ... 10.131286
49 30756 ... 11.634473
50 30757 ... 11.604493
51 30758 ... 10.855100
52 30759 ... 9.658119
53 30760 ... 9.685330
54 30761 ... 9.968962
55 30762 ... 9.553234
56 30763 ... 9.550599
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fy82xr6x wandb: Agent Starting Run: 83h0wkh0 with config: batch_size: 4 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 83h0wkh0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.505407392978668
The number of items in train is:
9
The loss for epoch 0
1.0561563769976299
The running loss is:
21.379353791475296
The number of items in train is:
9
The loss for epoch 1
2.375483754608366
The running loss is:
8.969172284007072
The number of items in train is:
9
The loss for epoch 2
0.996574698223008
The running loss is:
8.166614294052124
The number of items in train is:
9
The loss for epoch 3
0.9074015882280138
The running loss is:
6.223415791988373
The number of items in train is:
9
The loss for epoch 4
0.6914906435542636
The running loss is:
6.225053533911705
The number of items in train is:
9
The loss for epoch 5
0.6916726148790784
The running loss is:
4.850820034742355
The number of items in train is:
9
The loss for epoch 6
0.5389800038602617
The running loss is:
6.047254383563995
The number of items in train is:
9
The loss for epoch 7
0.6719171537293328
The running loss is:
5.450169747695327
The number of items in train is:
9
The loss for epoch 8
0.6055744164105918
The running loss is:
5.5230641812086105
The number of items in train is:
9
The loss for epoch 9
0.6136737979120679
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 2.551796
48 30755 ... 9.289855
49 30756 ... 13.825897
50 30757 ... 10.026182
51 30758 ... 6.181005
52 30759 ... 6.497049
53 30760 ... 4.788657
54 30761 ... 3.555442
55 30762 ... 3.971375
56 30763 ... 6.380777
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 83h0wkh0 wandb: Agent Starting Run: lkat3a3t with config: batch_size: 4 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: lkat3a3t
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.228183835744858
The number of items in train is:
9
The loss for epoch 0
1.1364648706383176
The running loss is:
22.093879207968712
The number of items in train is:
9
The loss for epoch 1
2.454875467552079
The running loss is:
11.21305176615715
The number of items in train is:
9
The loss for epoch 2
1.2458946406841278
The running loss is:
8.938593842089176
The number of items in train is:
9
The loss for epoch 3
0.993177093565464
The running loss is:
7.865151785314083
The number of items in train is:
9
The loss for epoch 4
0.873905753923787
The running loss is:
7.342009246349335
The number of items in train is:
9
The loss for epoch 5
0.8157788051499261
The running loss is:
6.836678400635719
The number of items in train is:
9
The loss for epoch 6
0.7596309334039688
The running loss is:
6.812281683087349
The number of items in train is:
9
The loss for epoch 7
0.7569201870097054
The running loss is:
6.919483810663223
The number of items in train is:
9
The loss for epoch 8
0.7688315345181359
The running loss is:
6.063464671373367
The number of items in train is:
9
The loss for epoch 9
0.673718296819263
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.149070
48 30755 ... 12.772628
49 30756 ... 10.170836
50 30757 ... 12.094771
51 30758 ... 12.898168
52 30759 ... 11.223684
53 30760 ... 11.328439
54 30761 ... 11.660076
55 30762 ... 11.364662
56 30763 ... 11.240909
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lkat3a3t wandb: Agent Starting Run: 83qumktt with config: batch_size: 4 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 83qumktt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.269839070737362
The number of items in train is:
9
The loss for epoch 0
1.2522043411930401
The running loss is:
18.2245534658432
The number of items in train is:
9
The loss for epoch 1
2.024950385093689
The running loss is:
11.093135692179203
The number of items in train is:
9
The loss for epoch 2
1.232570632464356
The running loss is:
7.84151503443718
The number of items in train is:
9
The loss for epoch 3
0.8712794482707977
The running loss is:
7.130702927708626
The number of items in train is:
9
The loss for epoch 4
0.7923003253009584
The running loss is:
6.894553929567337
The number of items in train is:
9
The loss for epoch 5
0.7660615477297041
The running loss is:
6.550070330500603
The number of items in train is:
9
The loss for epoch 6
0.7277855922778448
The running loss is:
5.66788774728775
The number of items in train is:
9
The loss for epoch 7
0.6297653052541945
The running loss is:
5.8400644809007645
The number of items in train is:
9
The loss for epoch 8
0.6488960534334183
The running loss is:
5.484764613211155
The number of items in train is:
9
The loss for epoch 9
0.609418290356795
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.282831
48 30755 ... 10.786951
49 30756 ... 11.856423
50 30757 ... 11.354153
51 30758 ... 11.202002
52 30759 ... 11.278160
53 30760 ... 11.181666
54 30761 ... 11.049433
55 30762 ... 10.850035
56 30763 ... 11.016407
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 83qumktt wandb: Agent Starting Run: eaehlwpi with config: batch_size: 4 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: eaehlwpi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
50.12921614944935
The number of items in train is:
9
The loss for epoch 0
5.569912905494372
The running loss is:
8.785686165094376
The number of items in train is:
9
The loss for epoch 1
0.9761873516771529
The running loss is:
12.605510175228119
The number of items in train is:
9
The loss for epoch 2
1.4006122416920133
The running loss is:
21.619386926293373
The number of items in train is:
9
The loss for epoch 3
2.402154102921486
The running loss is:
8.039730727672577
The number of items in train is:
9
The loss for epoch 4
0.8933034141858419
The running loss is:
8.46184479445219
The number of items in train is:
9
The loss for epoch 5
0.9402049771613545
The running loss is:
8.858764350414276
The number of items in train is:
9
The loss for epoch 6
0.9843071500460306
The running loss is:
8.675993755459785
The number of items in train is:
9
The loss for epoch 7
0.9639993061621984
The running loss is:
10.160760685801506
The number of items in train is:
9
The loss for epoch 8
1.1289734095335007
The running loss is:
9.34771716594696
The number of items in train is:
9
The loss for epoch 9
1.0386352406607733
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.515077
48 30755 ... 10.698237
49 30756 ... 11.456429
50 30757 ... 11.007051
51 30758 ... 11.129147
52 30759 ... 10.843229
53 30760 ... 10.730742
54 30761 ... 11.280998
55 30762 ... 11.350057
56 30763 ... 10.585619
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: eaehlwpi wandb: Agent Starting Run: clw96b2s with config: batch_size: 4 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: clw96b2s
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
45.258555337786674
The number of items in train is:
9
The loss for epoch 0
5.028728370865186
The running loss is:
9.887949824333191
The number of items in train is:
9
The loss for epoch 1
1.0986610915925767
The running loss is:
14.993930101394653
The number of items in train is:
9
The loss for epoch 2
1.6659922334882948
The running loss is:
8.667252570390701
The number of items in train is:
9
The loss for epoch 3
0.9630280633767446
The running loss is:
9.43253342807293
The number of items in train is:
9
The loss for epoch 4
1.048059269785881
The running loss is:
8.472909659147263
The number of items in train is:
9
The loss for epoch 5
0.941434406571918
The running loss is:
8.426761694252491
The number of items in train is:
9
The loss for epoch 6
0.9363068549169434
The running loss is:
7.336565665900707
The number of items in train is:
9
The loss for epoch 7
0.8151739628778564
The running loss is:
7.057315722107887
The number of items in train is:
9
The loss for epoch 8
0.7841461913453208
The running loss is:
7.008694067597389
The number of items in train is:
9
The loss for epoch 9
0.7787437852885988
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.018428
48 30755 ... 11.246632
49 30756 ... 10.371849
50 30757 ... 11.048549
51 30758 ... 12.152980
52 30759 ... 10.506842
53 30760 ... 10.698140
54 30761 ... 11.106715
55 30762 ... 9.964753
56 30763 ... 9.393328
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: clw96b2s wandb: Agent Starting Run: cbu0v3vm with config: batch_size: 4 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: cbu0v3vm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
55.83113503456116
The number of items in train is:
9
The loss for epoch 0
6.203459448284573
The running loss is:
7.615257233381271
The number of items in train is:
9
The loss for epoch 1
0.846139692597919
The running loss is:
13.260914385318756
The number of items in train is:
9
The loss for epoch 2
1.473434931702084
The running loss is:
18.711096964776516
The number of items in train is:
9
The loss for epoch 3
2.0790107738640575
The running loss is:
9.84968450665474
The number of items in train is:
9
The loss for epoch 4
1.0944093896283045
The running loss is:
8.82070518285036
The number of items in train is:
9
The loss for epoch 5
0.9800783536500401
The running loss is:
7.753073289990425
The number of items in train is:
9
The loss for epoch 6
0.8614525877767139
The running loss is:
7.464309379458427
The number of items in train is:
9
The loss for epoch 7
0.8293677088287141
The running loss is:
7.830278053879738
The number of items in train is:
9
The loss for epoch 8
0.8700308948755264
The running loss is:
7.0657903999090195
The number of items in train is:
9
The loss for epoch 9
0.7850878222121133
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.494602
48 30755 ... 10.482347
49 30756 ... 10.473118
50 30757 ... 10.541009
51 30758 ... 10.541041
52 30759 ... 9.136126
53 30760 ... 8.867601
54 30761 ... 9.107225
55 30762 ... 8.831312
56 30763 ... 8.666946
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cbu0v3vm wandb: Agent Starting Run: p6pyaclx with config: batch_size: 4 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: p6pyaclx
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.472531259059906
The number of items in train is:
9
The loss for epoch 0
1.2747256954511006
The running loss is:
9.711678888648748
The number of items in train is:
9
The loss for epoch 1
1.0790754320720832
The running loss is:
6.233100436627865
The number of items in train is:
9
The loss for epoch 2
0.6925667151808739
The running loss is:
5.8241632133722305
The number of items in train is:
9
The loss for epoch 3
0.6471292459302478
The running loss is:
5.290510561317205
The number of items in train is:
9
The loss for epoch 4
0.5878345068130229
The running loss is:
5.006042655557394
The number of items in train is:
9
The loss for epoch 5
0.5562269617285993
The running loss is:
4.981331991031766
The number of items in train is:
9
The loss for epoch 6
0.5534813323368629
The running loss is:
4.4758083410561085
The number of items in train is:
9
The loss for epoch 7
0.4973120378951232
The running loss is:
4.3199992924928665
The number of items in train is:
9
The loss for epoch 8
0.4799999213880963
The running loss is:
4.310908626765013
The number of items in train is:
9
The loss for epoch 9
0.4789898474183347
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.323457
48 30755 ... 7.979432
49 30756 ... 8.822479
50 30757 ... 10.618973
51 30758 ... 10.024648
52 30759 ... 7.265971
53 30760 ... 5.206593
54 30761 ... 4.850113
55 30762 ... 4.195802
56 30763 ... 4.077375
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: p6pyaclx wandb: Agent Starting Run: q4e69gzs with config: batch_size: 4 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: q4e69gzs
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.337343990802765
The number of items in train is:
9
The loss for epoch 0
1.2597048878669739
The running loss is:
7.484142437577248
The number of items in train is:
9
The loss for epoch 1
0.8315713819530275
The running loss is:
6.609706312417984
The number of items in train is:
9
The loss for epoch 2
0.7344118124908872
The running loss is:
5.361370384693146
The number of items in train is:
9
The loss for epoch 3
0.5957078205214607
The running loss is:
5.242933452129364
The number of items in train is:
9
The loss for epoch 4
0.5825481613477071
The running loss is:
5.025114297866821
The number of items in train is:
9
The loss for epoch 5
0.5583460330963135
The running loss is:
4.582142144441605
The number of items in train is:
9
The loss for epoch 6
0.5091269049379561
The running loss is:
4.44568158686161
The number of items in train is:
9
The loss for epoch 7
0.49396462076240116
The running loss is:
4.307258158922195
The number of items in train is:
9
The loss for epoch 8
0.47858423988024396
The running loss is:
4.187428444623947
The number of items in train is:
9
The loss for epoch 9
0.4652698271804386
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.117650
48 30755 ... 7.928844
49 30756 ... 9.761184
50 30757 ... 13.123506
51 30758 ... 11.381822
52 30759 ... 6.784797
53 30760 ... 5.429676
54 30761 ... 5.440561
55 30762 ... 4.422199
56 30763 ... 4.445116
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: q4e69gzs wandb: Agent Starting Run: ji2nr6u1 with config: batch_size: 4 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ji2nr6u1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.389308661222458
The number of items in train is:
8
The loss for epoch 0
1.1736635826528072
The running loss is:
11.884019121527672
The number of items in train is:
8
The loss for epoch 1
1.485502390190959
The running loss is:
6.111610025167465
The number of items in train is:
8
The loss for epoch 2
0.7639512531459332
The running loss is:
5.661065757274628
The number of items in train is:
8
The loss for epoch 3
0.7076332196593285
The running loss is:
5.221550419926643
The number of items in train is:
8
The loss for epoch 4
0.6526938024908304
The running loss is:
4.935086935758591
The number of items in train is:
8
The loss for epoch 5
0.6168858669698238
The running loss is:
4.89002551138401
The number of items in train is:
8
The loss for epoch 6
0.6112531889230013
The running loss is:
4.821478247642517
The number of items in train is:
8
The loss for epoch 7
0.6026847809553146
The running loss is:
4.719222843647003
The number of items in train is:
8
The loss for epoch 8
0.5899028554558754
The running loss is:
4.442844241857529
The number of items in train is:
8
The loss for epoch 9
0.5553555302321911
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.830432
48 30755 ... 7.491436
49 30756 ... 7.830326
50 30757 ... 8.473710
51 30758 ... 8.261139
52 30759 ... 6.579417
53 30760 ... 4.488674
54 30761 ... 4.710826
55 30762 ... 4.869449
56 30763 ... 3.949037
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ji2nr6u1 wandb: Agent Starting Run: 4tgn3n63 with config: batch_size: 4 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 4tgn3n63
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.71286141872406
The number of items in train is:
9
The loss for epoch 0
1.1903179354137845
The running loss is:
21.590499818325043
The number of items in train is:
9
The loss for epoch 1
2.398944424258338
The running loss is:
7.400251135230064
The number of items in train is:
9
The loss for epoch 2
0.8222501261366738
The running loss is:
7.180257387459278
The number of items in train is:
9
The loss for epoch 3
0.7978063763843642
The running loss is:
5.999096572399139
The number of items in train is:
9
The loss for epoch 4
0.6665662858221266
The running loss is:
5.3636345863342285
The number of items in train is:
9
The loss for epoch 5
0.595959398481581
The running loss is:
4.844901656731963
The number of items in train is:
9
The loss for epoch 6
0.5383224063035514
The running loss is:
4.299406096339226
The number of items in train is:
9
The loss for epoch 7
0.4777117884821362
The running loss is:
3.937914729118347
The number of items in train is:
9
The loss for epoch 8
0.4375460810131497
The running loss is:
3.964134406298399
The number of items in train is:
9
The loss for epoch 9
0.44045937847759986
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.955766
48 30755 ... 9.095902
49 30756 ... 9.801540
50 30757 ... 12.133164
51 30758 ... 10.810966
52 30759 ... 8.204831
53 30760 ... 8.553889
54 30761 ... 7.950711
55 30762 ... 7.240780
56 30763 ... 6.987817
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4tgn3n63 wandb: Agent Starting Run: 19iqie21 with config: batch_size: 4 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 19iqie21
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.870292961597443
The number of items in train is:
9
The loss for epoch 0
1.2078103290663824
The running loss is:
13.46465790271759
The number of items in train is:
9
The loss for epoch 1
1.4960731003019545
The running loss is:
7.045529410243034
The number of items in train is:
9
The loss for epoch 2
0.7828366011381149
The running loss is:
6.129437237977982
The number of items in train is:
9
The loss for epoch 3
0.6810485819975535
The running loss is:
5.570417806506157
The number of items in train is:
9
The loss for epoch 4
0.6189353118340174
The running loss is:
5.336072877049446
The number of items in train is:
9
The loss for epoch 5
0.5928969863388274
The running loss is:
4.585846528410912
The number of items in train is:
9
The loss for epoch 6
0.509538503156768
The running loss is:
4.421219557523727
The number of items in train is:
9
The loss for epoch 7
0.4912466175026364
The running loss is:
4.118749655783176
The number of items in train is:
9
The loss for epoch 8
0.45763885064257515
The running loss is:
4.141455993056297
The number of items in train is:
9
The loss for epoch 9
0.46016177700625527
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.972950
48 30755 ... 8.010669
49 30756 ... 10.162770
50 30757 ... 13.685595
51 30758 ... 11.899075
52 30759 ... 7.380159
53 30760 ... 6.770110
54 30761 ... 6.820722
55 30762 ... 5.682702
56 30763 ... 5.836186
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 19iqie21 wandb: Agent Starting Run: 2wjn71cw with config: batch_size: 4 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 2wjn71cw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.224892944097519
The number of items in train is:
8
The loss for epoch 0
1.4031116180121899
The running loss is:
22.453463792800903
The number of items in train is:
8
The loss for epoch 1
2.806682974100113
The running loss is:
6.1356241554021835
The number of items in train is:
8
The loss for epoch 2
0.7669530194252729
The running loss is:
6.19755494594574
The number of items in train is:
8
The loss for epoch 3
0.7746943682432175
The running loss is:
5.850357830524445
The number of items in train is:
8
The loss for epoch 4
0.7312947288155556
The running loss is:
5.245521053671837
The number of items in train is:
8
The loss for epoch 5
0.6556901317089796
The running loss is:
5.032821208238602
The number of items in train is:
8
The loss for epoch 6
0.6291026510298252
The running loss is:
4.9136738032102585
The number of items in train is:
8
The loss for epoch 7
0.6142092254012823
The running loss is:
4.7698249369859695
The number of items in train is:
8
The loss for epoch 8
0.5962281171232462
The running loss is:
4.3794238567352295
The number of items in train is:
8
The loss for epoch 9
0.5474279820919037
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.586073
48 30755 ... 7.948225
49 30756 ... 8.597462
50 30757 ... 9.739484
51 30758 ... 9.282975
52 30759 ... 7.467255
53 30760 ... 6.273127
54 30761 ... 6.356297
55 30762 ... 6.291785
56 30763 ... 5.424063
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2wjn71cw wandb: Agent Starting Run: 00kr9sl0 with config: batch_size: 4 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 00kr9sl0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.727948267012835
The number of items in train is:
9
The loss for epoch 0
1.5253275852236483
The running loss is:
21.50830540060997
The number of items in train is:
9
The loss for epoch 1
2.3898117111788855
The running loss is:
16.788552042096853
The number of items in train is:
9
The loss for epoch 2
1.8653946713440948
The running loss is:
7.9370488822460175
The number of items in train is:
9
The loss for epoch 3
0.8818943202495575
The running loss is:
6.910562638193369
The number of items in train is:
9
The loss for epoch 4
0.7678402931325965
The running loss is:
6.337854765355587
The number of items in train is:
9
The loss for epoch 5
0.7042060850395097
The running loss is:
5.4855453334748745
The number of items in train is:
9
The loss for epoch 6
0.6095050370527638
The running loss is:
5.8733771443367
The number of items in train is:
9
The loss for epoch 7
0.6525974604818556
The running loss is:
6.408730834722519
The number of items in train is:
9
The loss for epoch 8
0.7120812038580576
The running loss is:
6.403976768255234
The number of items in train is:
9
The loss for epoch 9
0.7115529742505815
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.310756
48 30755 ... 7.642404
49 30756 ... 9.885168
50 30757 ... 12.911268
51 30758 ... 11.841020
52 30759 ... 8.110412
53 30760 ... 7.384973
54 30761 ... 10.239965
55 30762 ... 7.918401
56 30763 ... 7.714108
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 00kr9sl0 wandb: Agent Starting Run: sowhvjl7 with config: batch_size: 4 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sowhvjl7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.251713529229164
The number of items in train is:
9
The loss for epoch 0
1.1390792810254626
The running loss is:
19.286679983139038
The number of items in train is:
9
The loss for epoch 1
2.1429644425710044
The running loss is:
11.851648703217506
The number of items in train is:
9
The loss for epoch 2
1.3168498559130564
The running loss is:
8.593457102775574
The number of items in train is:
9
The loss for epoch 3
0.9548285669750638
The running loss is:
7.537827163934708
The number of items in train is:
9
The loss for epoch 4
0.8375363515483009
The running loss is:
7.457647129893303
The number of items in train is:
9
The loss for epoch 5
0.8286274588770337
The running loss is:
7.16678649187088
The number of items in train is:
9
The loss for epoch 6
0.7963096102078756
The running loss is:
6.750422567129135
The number of items in train is:
9
The loss for epoch 7
0.7500469519032372
The running loss is:
6.237434804439545
The number of items in train is:
9
The loss for epoch 8
0.6930483116043938
The running loss is:
6.342507421970367
The number of items in train is:
9
The loss for epoch 9
0.7047230468855964
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.323541
48 30755 ... 8.063728
49 30756 ... 10.272192
50 30757 ... 15.522292
51 30758 ... 12.543692
52 30759 ... 7.162727
53 30760 ... 10.342567
54 30761 ... 11.479841
55 30762 ... 9.222147
56 30763 ... 10.127317
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sowhvjl7 wandb: Agent Starting Run: mtxkvdqw with config: batch_size: 4 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: mtxkvdqw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.705665796995163
The number of items in train is:
8
The loss for epoch 0
2.3382082246243954
The running loss is:
18.839629769325256
The number of items in train is:
8
The loss for epoch 1
2.354953721165657
The running loss is:
23.626360967755318
The number of items in train is:
8
The loss for epoch 2
2.9532951209694147
The running loss is:
8.420704454183578
The number of items in train is:
8
The loss for epoch 3
1.0525880567729473
The running loss is:
7.341050535440445
The number of items in train is:
8
The loss for epoch 4
0.9176313169300556
The running loss is:
6.895925462245941
The number of items in train is:
8
The loss for epoch 5
0.8619906827807426
The running loss is:
6.075425148010254
The number of items in train is:
8
The loss for epoch 6
0.7594281435012817
The running loss is:
5.39270444214344
The number of items in train is:
8
The loss for epoch 7
0.67408805526793
The running loss is:
5.2611357271671295
The number of items in train is:
8
The loss for epoch 8
0.6576419658958912
The running loss is:
4.8258286118507385
The number of items in train is:
8
The loss for epoch 9
0.6032285764813423
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.815147
48 30755 ... 9.209466
49 30756 ... 9.237023
50 30757 ... 10.296669
51 30758 ... 9.815141
52 30759 ... 8.073587
53 30760 ... 7.225603
54 30761 ... 7.534699
55 30762 ... 7.330389
56 30763 ... 6.658091
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mtxkvdqw wandb: Agent Starting Run: l4rdkk5i with config: batch_size: 4 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: l4rdkk5i
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
81.38286215811968
The number of items in train is:
9
The loss for epoch 0
9.042540239791075
The running loss is:
6.7282320857048035
The number of items in train is:
9
The loss for epoch 1
0.7475813428560892
The running loss is:
17.271905541419983
The number of items in train is:
9
The loss for epoch 2
1.9191006157133315
The running loss is:
22.52288556098938
The number of items in train is:
9
The loss for epoch 3
2.502542840109931
The running loss is:
13.139688491821289
The number of items in train is:
9
The loss for epoch 4
1.4599653879801433
The running loss is:
12.133773386478424
The number of items in train is:
9
The loss for epoch 5
1.3481970429420471
The running loss is:
8.478021509945393
The number of items in train is:
9
The loss for epoch 6
0.9420023899939325
The running loss is:
8.083688005805016
The number of items in train is:
9
The loss for epoch 7
0.8981875562005572
The running loss is:
6.952758699655533
The number of items in train is:
9
The loss for epoch 8
0.7725287444061704
The running loss is:
6.886708460748196
The number of items in train is:
9
The loss for epoch 9
0.7651898289720217
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.982682
48 30755 ... 9.206006
49 30756 ... 9.838526
50 30757 ... 11.931196
51 30758 ... 10.667216
52 30759 ... 9.140854
53 30760 ... 8.847374
54 30761 ... 9.114708
55 30762 ... 8.678926
56 30763 ... 8.438699
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l4rdkk5i wandb: Agent Starting Run: iatf6fgg with config: batch_size: 4 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: iatf6fgg
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.24754601716995
The number of items in train is:
9
The loss for epoch 0
5.694171779685551
The running loss is:
8.4677115380764
The number of items in train is:
9
The loss for epoch 1
0.9408568375640445
The running loss is:
15.262419521808624
The number of items in train is:
9
The loss for epoch 2
1.6958243913120694
The running loss is:
9.589929044246674
The number of items in train is:
9
The loss for epoch 3
1.0655476715829637
The running loss is:
9.376197457313538
The number of items in train is:
9
The loss for epoch 4
1.041799717479282
The running loss is:
8.084025770425797
The number of items in train is:
9
The loss for epoch 5
0.8982250856028663
The running loss is:
7.947470888495445
The number of items in train is:
9
The loss for epoch 6
0.8830523209439384
The running loss is:
7.507450953125954
The number of items in train is:
9
The loss for epoch 7
0.8341612170139948
The running loss is:
7.8752095103263855
The number of items in train is:
9
The loss for epoch 8
0.875023278925154
The running loss is:
7.515006110072136
The number of items in train is:
9
The loss for epoch 9
0.835000678896904
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.094513
48 30755 ... 11.177944
49 30756 ... 12.555366
50 30757 ... 10.339748
51 30758 ... 10.501686
52 30759 ... 9.739458
53 30760 ... 9.221687
54 30761 ... 9.388515
55 30762 ... 9.439221
56 30763 ... 9.129675
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: iatf6fgg wandb: Agent Starting Run: u46ofsht with config: batch_size: 4 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u46ofsht
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
100.43890479207039
The number of items in train is:
8
The loss for epoch 0
12.554863099008799
The running loss is:
6.304996594786644
The number of items in train is:
8
The loss for epoch 1
0.7881245743483305
The running loss is:
17.867437183856964
The number of items in train is:
8
The loss for epoch 2
2.2334296479821205
The running loss is:
15.657972991466522
The number of items in train is:
8
The loss for epoch 3
1.9572466239333153
The running loss is:
14.777969121932983
The number of items in train is:
8
The loss for epoch 4
1.847246140241623
The running loss is:
11.4342300593853
The number of items in train is:
8
The loss for epoch 5
1.4292787574231625
The running loss is:
14.000842481851578
The number of items in train is:
8
The loss for epoch 6
1.7501053102314472
The running loss is:
7.894358307123184
The number of items in train is:
8
The loss for epoch 7
0.986794788390398
The running loss is:
7.187334030866623
The number of items in train is:
8
The loss for epoch 8
0.8984167538583279
The running loss is:
6.727936089038849
The number of items in train is:
8
The loss for epoch 9
0.8409920111298561
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.339002
48 30755 ... 8.151986
49 30756 ... 8.261250
50 30757 ... 8.263336
51 30758 ... 9.959813
52 30759 ... 9.977565
53 30760 ... 8.724285
54 30761 ... 8.880425
55 30762 ... 8.432564
56 30763 ... 8.202187
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u46ofsht wandb: Agent Starting Run: 2ar2l5wu with config: batch_size: 4 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 2ar2l5wu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.240214586257935
The number of items in train is:
9
The loss for epoch 0
1.2489127318064372
The running loss is:
8.247485101222992
The number of items in train is:
9
The loss for epoch 1
0.9163872334692214
The running loss is:
5.765671074390411
The number of items in train is:
9
The loss for epoch 2
0.6406301193767123
The running loss is:
5.146143764257431
The number of items in train is:
9
The loss for epoch 3
0.571793751584159
The running loss is:
4.820492431521416
The number of items in train is:
9
The loss for epoch 4
0.5356102701690462
The running loss is:
4.526142358779907
The number of items in train is:
9
The loss for epoch 5
0.5029047065311008
The running loss is:
4.435101807117462
The number of items in train is:
9
The loss for epoch 6
0.492789089679718
The running loss is:
4.415074750781059
The number of items in train is:
9
The loss for epoch 7
0.49056386119789547
The running loss is:
3.871296752244234
The number of items in train is:
9
The loss for epoch 8
0.4301440835826927
The running loss is:
3.9733955711126328
The number of items in train is:
9
The loss for epoch 9
0.4414883967902925
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.965207
48 30755 ... 14.476615
49 30756 ... 16.937613
50 30757 ... 17.153940
51 30758 ... 16.729450
52 30759 ... 17.081961
53 30760 ... 16.339411
54 30761 ... 15.521223
55 30762 ... 16.540747
56 30763 ... 17.925924
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2ar2l5wu wandb: Agent Starting Run: mv48xg3w with config: batch_size: 4 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: mv48xg3w
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.515716254711151
The number of items in train is:
8
The loss for epoch 0
1.189464531838894
The running loss is:
7.534291982650757
The number of items in train is:
8
The loss for epoch 1
0.9417864978313446
The running loss is:
5.5912118554115295
The number of items in train is:
8
The loss for epoch 2
0.6989014819264412
The running loss is:
4.792952626943588
The number of items in train is:
8
The loss for epoch 3
0.5991190783679485
The running loss is:
4.525293126702309
The number of items in train is:
8
The loss for epoch 4
0.5656616408377886
The running loss is:
4.299796998500824
The number of items in train is:
8
The loss for epoch 5
0.537474624812603
The running loss is:
4.276003211736679
The number of items in train is:
8
The loss for epoch 6
0.5345004014670849
The running loss is:
4.01696603000164
The number of items in train is:
8
The loss for epoch 7
0.502120753750205
The running loss is:
3.905553936958313
The number of items in train is:
8
The loss for epoch 8
0.4881942421197891
The running loss is:
3.9828645288944244
The number of items in train is:
8
The loss for epoch 9
0.49785806611180305
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.893699
48 30755 ... 6.638311
49 30756 ... 7.527349
50 30757 ... 7.468067
51 30758 ... 6.686835
52 30759 ... 6.755731
53 30760 ... 6.032629
54 30761 ... 1.660941
55 30762 ... 1.834283
56 30763 ... 2.062750
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mv48xg3w wandb: Agent Starting Run: hs9lsvq5 with config: batch_size: 4 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hs9lsvq5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.516059219837189
The number of items in train is:
8
The loss for epoch 0
1.1895074024796486
The running loss is:
6.715246796607971
The number of items in train is:
8
The loss for epoch 1
0.8394058495759964
The running loss is:
5.639530926942825
The number of items in train is:
8
The loss for epoch 2
0.7049413658678532
The running loss is:
4.6814810037612915
The number of items in train is:
8
The loss for epoch 3
0.5851851254701614
The running loss is:
4.4828057289123535
The number of items in train is:
8
The loss for epoch 4
0.5603507161140442
The running loss is:
4.376252077519894
The number of items in train is:
8
The loss for epoch 5
0.5470315096899867
The running loss is:
4.29168626666069
The number of items in train is:
8
The loss for epoch 6
0.5364607833325863
The running loss is:
4.129114165902138
The number of items in train is:
8
The loss for epoch 7
0.5161392707377672
The running loss is:
3.896572157740593
The number of items in train is:
8
The loss for epoch 8
0.4870715197175741
The running loss is:
3.9742572754621506
The number of items in train is:
8
The loss for epoch 9
0.4967821594327688
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.151683
48 30755 ... 6.115150
49 30756 ... 5.120647
50 30757 ... 5.428493
51 30758 ... 5.418796
52 30759 ... 5.150074
53 30760 ... 3.822505
54 30761 ... 0.330210
55 30762 ... 0.349950
56 30763 ... 0.434411
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hs9lsvq5 wandb: Agent Starting Run: y0msl3ra with config: batch_size: 4 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: y0msl3ra
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.602681040763855
The number of items in train is:
9
The loss for epoch 0
1.1780756711959839
The running loss is:
13.631228134036064
The number of items in train is:
9
The loss for epoch 1
1.514580903781785
The running loss is:
6.118208613246679
The number of items in train is:
9
The loss for epoch 2
0.6798009570274088
The running loss is:
5.688015699386597
The number of items in train is:
9
The loss for epoch 3
0.6320017443762885
The running loss is:
5.0169960260391235
The number of items in train is:
9
The loss for epoch 4
0.5574440028932359
The running loss is:
4.685733154416084
The number of items in train is:
9
The loss for epoch 5
0.5206370171573427
The running loss is:
4.271254613995552
The number of items in train is:
9
The loss for epoch 6
0.47458384599950576
The running loss is:
4.182044744491577
The number of items in train is:
9
The loss for epoch 7
0.4646716382768419
The running loss is:
3.620811596279964
The number of items in train is:
9
The loss for epoch 8
0.40231239958666265
The running loss is:
3.491945043206215
The number of items in train is:
9
The loss for epoch 9
0.3879938936895794
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.298182
48 30755 ... 13.530397
49 30756 ... 17.241079
50 30757 ... 17.800289
51 30758 ... 16.026747
52 30759 ... 16.836815
53 30760 ... 16.701458
54 30761 ... 15.817758
55 30762 ... 16.637817
56 30763 ... 17.145372
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y0msl3ra wandb: Agent Starting Run: 48gcksh1 with config: batch_size: 4 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 48gcksh1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.860792398452759
The number of items in train is:
8
The loss for epoch 0
1.2325990498065948
The running loss is:
14.10496175289154
The number of items in train is:
8
The loss for epoch 1
1.7631202191114426
The running loss is:
5.463801130652428
The number of items in train is:
8
The loss for epoch 2
0.6829751413315535
The running loss is:
5.403226584196091
The number of items in train is:
8
The loss for epoch 3
0.6754033230245113
The running loss is:
5.051839262247086
The number of items in train is:
8
The loss for epoch 4
0.6314799077808857
The running loss is:
4.48129203915596
The number of items in train is:
8
The loss for epoch 5
0.560161504894495
The running loss is:
4.7035655826330185
The number of items in train is:
8
The loss for epoch 6
0.5879456978291273
The running loss is:
4.368928179144859
The number of items in train is:
8
The loss for epoch 7
0.5461160223931074
The running loss is:
3.841419756412506
The number of items in train is:
8
The loss for epoch 8
0.48017746955156326
The running loss is:
4.101872503757477
The number of items in train is:
8
The loss for epoch 9
0.5127340629696846
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.275268
48 30755 ... 6.410582
49 30756 ... 7.161199
50 30757 ... 7.300799
51 30758 ... 6.098117
52 30759 ... 6.650946
53 30760 ... 7.211934
54 30761 ... 2.103153
55 30762 ... 2.071001
56 30763 ... 1.847907
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 48gcksh1 wandb: Agent Starting Run: 3rt84xz2 with config: batch_size: 4 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3rt84xz2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.657917499542236
The number of items in train is:
8
The loss for epoch 0
1.2072396874427795
The running loss is:
11.63252505660057
The number of items in train is:
8
The loss for epoch 1
1.4540656320750713
The running loss is:
5.313596427440643
The number of items in train is:
8
The loss for epoch 2
0.6641995534300804
The running loss is:
5.196029812097549
The number of items in train is:
8
The loss for epoch 3
0.6495037265121937
The running loss is:
4.855725049972534
The number of items in train is:
8
The loss for epoch 4
0.6069656312465668
The running loss is:
4.514636904001236
The number of items in train is:
8
The loss for epoch 5
0.5643296130001545
The running loss is:
4.483666583895683
The number of items in train is:
8
The loss for epoch 6
0.5604583229869604
The running loss is:
4.368599742650986
The number of items in train is:
8
The loss for epoch 7
0.5460749678313732
The running loss is:
3.887495845556259
The number of items in train is:
8
The loss for epoch 8
0.4859369806945324
The running loss is:
3.9840978533029556
The number of items in train is:
8
The loss for epoch 9
0.49801223166286945
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.280387
48 30755 ... 6.253471
49 30756 ... 3.794707
50 30757 ... 4.741993
51 30758 ... 5.272310
52 30759 ... 5.426122
53 30760 ... 5.281884
54 30761 ... 1.368745
55 30762 ... 1.047200
56 30763 ... 0.864929
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3rt84xz2 wandb: Agent Starting Run: 4l6ynrgv with config: batch_size: 4 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 4l6ynrgv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.533425658941269
The number of items in train is:
9
The loss for epoch 0
1.7259361843268077
The running loss is:
12.174829576164484
The number of items in train is:
9
The loss for epoch 1
1.3527588417960539
The running loss is:
11.701843023300171
The number of items in train is:
9
The loss for epoch 2
1.3002047803666856
The running loss is:
6.7660181522369385
The number of items in train is:
9
The loss for epoch 3
0.7517797946929932
The running loss is:
5.420725777745247
The number of items in train is:
9
The loss for epoch 4
0.6023028641939163
The running loss is:
5.102972134947777
The number of items in train is:
9
The loss for epoch 5
0.5669969038830863
The running loss is:
4.493372078268294
The number of items in train is:
9
The loss for epoch 6
0.49926356425203267
The running loss is:
4.5250896736979485
The number of items in train is:
9
The loss for epoch 7
0.5027877415219942
The running loss is:
3.6071000695228577
The number of items in train is:
9
The loss for epoch 8
0.40078889661365086
The running loss is:
4.666622310876846
The number of items in train is:
9
The loss for epoch 9
0.5185135900974274
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.809757
48 30755 ... 13.937504
49 30756 ... 15.696578
50 30757 ... 15.797330
51 30758 ... 14.323220
52 30759 ... 15.466822
53 30760 ... 16.896070
54 30761 ... 16.546282
55 30762 ... 16.577997
56 30763 ... 17.435064
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4l6ynrgv wandb: Agent Starting Run: ydoutypm with config: batch_size: 4 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ydoutypm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.363870769739151
The number of items in train is:
8
The loss for epoch 0
1.7954838462173939
The running loss is:
19.697499066591263
The number of items in train is:
8
The loss for epoch 1
2.462187383323908
The running loss is:
11.393310114741325
The number of items in train is:
8
The loss for epoch 2
1.4241637643426657
The running loss is:
8.402333736419678
The number of items in train is:
8
The loss for epoch 3
1.0502917170524597
The running loss is:
5.944117605686188
The number of items in train is:
8
The loss for epoch 4
0.7430147007107735
The running loss is:
5.597024708986282
The number of items in train is:
8
The loss for epoch 5
0.6996280886232853
The running loss is:
5.168054163455963
The number of items in train is:
8
The loss for epoch 6
0.6460067704319954
The running loss is:
4.947095543146133
The number of items in train is:
8
The loss for epoch 7
0.6183869428932667
The running loss is:
4.267922282218933
The number of items in train is:
8
The loss for epoch 8
0.5334902852773666
The running loss is:
4.8770816922187805
The number of items in train is:
8
The loss for epoch 9
0.6096352115273476
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.681001
48 30755 ... 8.239495
49 30756 ... 5.559090
50 30757 ... 7.716256
51 30758 ... 7.096302
52 30759 ... 8.370895
53 30760 ... 8.647257
54 30761 ... 5.265896
55 30762 ... 5.894797
56 30763 ... 5.552207
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ydoutypm wandb: Agent Starting Run: c644kaet with config: batch_size: 4 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: c644kaet
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.808787852525711
The number of items in train is:
8
The loss for epoch 0
1.6010984815657139
The running loss is:
18.55983731150627
The number of items in train is:
8
The loss for epoch 1
2.319979663938284
The running loss is:
9.308479636907578
The number of items in train is:
8
The loss for epoch 2
1.1635599546134472
The running loss is:
7.871344238519669
The number of items in train is:
8
The loss for epoch 3
0.9839180298149586
The running loss is:
6.256579011678696
The number of items in train is:
8
The loss for epoch 4
0.782072376459837
The running loss is:
6.102777987718582
The number of items in train is:
8
The loss for epoch 5
0.7628472484648228
The running loss is:
6.1117411851882935
The number of items in train is:
8
The loss for epoch 6
0.7639676481485367
The running loss is:
5.467746406793594
The number of items in train is:
8
The loss for epoch 7
0.6834683008491993
The running loss is:
5.107202380895615
The number of items in train is:
8
The loss for epoch 8
0.6384002976119518
The running loss is:
4.626663476228714
The number of items in train is:
8
The loss for epoch 9
0.5783329345285892
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.824013
48 30755 ... 10.360836
49 30756 ... 1.159604
50 30757 ... 4.956064
51 30758 ... 10.496676
52 30759 ... 9.896183
53 30760 ... 8.568040
54 30761 ... 4.366958
55 30762 ... 8.373426
56 30763 ... 12.185763
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c644kaet wandb: Agent Starting Run: 08iry1zu with config: batch_size: 4 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 08iry1zu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
75.98427636921406
The number of items in train is:
9
The loss for epoch 0
8.442697374357117
The running loss is:
7.671401828527451
The number of items in train is:
9
The loss for epoch 1
0.8523779809474945
The running loss is:
7.74273831769824
The number of items in train is:
9
The loss for epoch 2
0.8603042575220267
The running loss is:
20.43498346209526
The number of items in train is:
9
The loss for epoch 3
2.2705537180105844
The running loss is:
9.485761232674122
The number of items in train is:
9
The loss for epoch 4
1.0539734702971246
The running loss is:
7.028515428304672
The number of items in train is:
9
The loss for epoch 5
0.7809461587005191
The running loss is:
9.961183845996857
The number of items in train is:
9
The loss for epoch 6
1.1067982051107619
The running loss is:
8.72087475657463
The number of items in train is:
9
The loss for epoch 7
0.9689860840638479
The running loss is:
6.958840258419514
The number of items in train is:
9
The loss for epoch 8
0.7732044731577238
The running loss is:
6.960021182894707
The number of items in train is:
9
The loss for epoch 9
0.7733356869883008
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.854007
48 30755 ... 10.343146
49 30756 ... 10.939295
50 30757 ... 10.770342
51 30758 ... 10.956257
52 30759 ... 10.479692
53 30760 ... 10.429470
54 30761 ... 10.492990
55 30762 ... 9.486902
56 30763 ... 10.307619
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 08iry1zu wandb: Agent Starting Run: lex8ifnr with config: batch_size: 4 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: lex8ifnr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
74.78043869137764
The number of items in train is:
8
The loss for epoch 0
9.347554836422205
The running loss is:
7.614499539136887
The number of items in train is:
8
The loss for epoch 1
0.9518124423921108
The running loss is:
15.35375702381134
The number of items in train is:
8
The loss for epoch 2
1.9192196279764175
The running loss is:
8.587577134370804
The number of items in train is:
8
The loss for epoch 3
1.0734471417963505
The running loss is:
9.464078083634377
The number of items in train is:
8
The loss for epoch 4
1.183009760454297
The running loss is:
6.2125754952430725
The number of items in train is:
8
The loss for epoch 5
0.7765719369053841
The running loss is:
6.502643406391144
The number of items in train is:
8
The loss for epoch 6
0.812830425798893
The running loss is:
6.101149320602417
The number of items in train is:
8
The loss for epoch 7
0.7626436650753021
The running loss is:
5.572430431842804
The number of items in train is:
8
The loss for epoch 8
0.6965538039803505
The running loss is:
5.655242145061493
The number of items in train is:
8
The loss for epoch 9
0.7069052681326866
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.959207
48 30755 ... 9.834291
49 30756 ... 9.036126
50 30757 ... 9.565654
51 30758 ... 10.552333
52 30759 ... 8.679264
53 30760 ... 9.437155
54 30761 ... 8.514996
55 30762 ... 8.533216
56 30763 ... 8.519036
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lex8ifnr wandb: Agent Starting Run: cw2pk8sa with config: batch_size: 4 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: cw2pk8sa
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
59.434263706207275
The number of items in train is:
8
The loss for epoch 0
7.429282963275909
The running loss is:
7.967703193426132
The number of items in train is:
8
The loss for epoch 1
0.9959628991782665
The running loss is:
12.137783110141754
The number of items in train is:
8
The loss for epoch 2
1.5172228887677193
The running loss is:
6.155479699373245
The number of items in train is:
8
The loss for epoch 3
0.7694349624216557
The running loss is:
8.069218963384628
The number of items in train is:
8
The loss for epoch 4
1.0086523704230785
The running loss is:
6.376190662384033
The number of items in train is:
8
The loss for epoch 5
0.7970238327980042
The running loss is:
6.5400115847587585
The number of items in train is:
8
The loss for epoch 6
0.8175014480948448
The running loss is:
6.4503806829452515
The number of items in train is:
8
The loss for epoch 7
0.8062975853681564
The running loss is:
5.695991367101669
The number of items in train is:
8
The loss for epoch 8
0.7119989208877087
The running loss is:
5.114424854516983
The number of items in train is:
8
The loss for epoch 9
0.6393031068146229
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.761915
48 30755 ... 8.762178
49 30756 ... 9.847136
50 30757 ... 10.490384
51 30758 ... 10.029481
52 30759 ... 9.967039
53 30760 ... 9.756455
54 30761 ... 9.366921
55 30762 ... 9.376884
56 30763 ... 9.368626
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cw2pk8sa wandb: Agent Starting Run: j4pjd9fg with config: batch_size: 5 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: j4pjd9fg
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.533234931528568
The number of items in train is:
9
The loss for epoch 0
1.2814705479476187
The running loss is:
6.274889692664146
The number of items in train is:
9
The loss for epoch 1
0.6972099658515718
The running loss is:
6.580070376396179
The number of items in train is:
9
The loss for epoch 2
0.7311189307106866
The running loss is:
6.824178397655487
The number of items in train is:
9
The loss for epoch 3
0.758242044183943
The running loss is:
6.764967136085033
The number of items in train is:
9
The loss for epoch 4
0.7516630151205592
The running loss is:
6.578010678291321
The number of items in train is:
9
The loss for epoch 5
0.7308900753657023
The running loss is:
6.553186744451523
The number of items in train is:
9
The loss for epoch 6
0.7281318604946136
The running loss is:
6.889299750328064
The number of items in train is:
9
The loss for epoch 7
0.7654777500364516
The running loss is:
6.328777223825455
The number of items in train is:
9
The loss for epoch 8
0.7031974693139394
The running loss is:
7.134986996650696
The number of items in train is:
9
The loss for epoch 9
0.7927763329611884
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 10.560451
48 30755 ... 9.577876
49 30756 ... 9.191813
50 30757 ... 9.049974
51 30758 ... 9.008125
52 30759 ... 9.007214
53 30760 ... 9.023063
54 30761 ... 8.932218
55 30762 ... 8.911247
56 30763 ... 8.918882
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: j4pjd9fg wandb: Agent Starting Run: a36qa9p5 with config: batch_size: 5 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: a36qa9p5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.704378187656403
The number of items in train is:
9
The loss for epoch 0
1.7449309097396002
The running loss is:
11.479490011930466
The number of items in train is:
9
The loss for epoch 1
1.2754988902144961
The running loss is:
11.382507085800171
The number of items in train is:
9
The loss for epoch 2
1.2647230095333524
The running loss is:
11.495850086212158
The number of items in train is:
9
The loss for epoch 3
1.2773166762457953
The running loss is:
11.004574656486511
The number of items in train is:
9
The loss for epoch 4
1.2227305173873901
The running loss is:
10.956842869520187
The number of items in train is:
9
The loss for epoch 5
1.217426985502243
The running loss is:
10.731719583272934
The number of items in train is:
9
The loss for epoch 6
1.192413287030326
The running loss is:
10.264773041009903
The number of items in train is:
9
The loss for epoch 7
1.1405303378899891
The running loss is:
10.230035275220871
The number of items in train is:
9
The loss for epoch 8
1.1366705861356523
The running loss is:
10.418312817811966
The number of items in train is:
9
The loss for epoch 9
1.1575903130902185
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 16.478621
48 30755 ... 18.715132
49 30756 ... 20.084146
50 30757 ... 20.847290
51 30758 ... 21.187290
52 30759 ... 21.231760
53 30760 ... 21.069832
54 30761 ... 22.114664
55 30762 ... 22.651400
56 30763 ... 22.833271
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: a36qa9p5 wandb: Agent Starting Run: tlrhr9xu with config: batch_size: 5 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: tlrhr9xu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.656018763780594
The number of items in train is:
8
The loss for epoch 0
1.5820023454725742
The running loss is:
8.512771248817444
The number of items in train is:
8
The loss for epoch 1
1.0640964061021805
The running loss is:
8.516142398118973
The number of items in train is:
8
The loss for epoch 2
1.0645177997648716
The running loss is:
8.601598471403122
The number of items in train is:
8
The loss for epoch 3
1.0751998089253902
The running loss is:
8.647248148918152
The number of items in train is:
8
The loss for epoch 4
1.080906018614769
The running loss is:
7.904319673776627
The number of items in train is:
8
The loss for epoch 5
0.9880399592220783
The running loss is:
8.513316988945007
The number of items in train is:
8
The loss for epoch 6
1.064164623618126
The running loss is:
8.36613380908966
The number of items in train is:
8
The loss for epoch 7
1.0457667261362076
The running loss is:
7.99756520986557
The number of items in train is:
8
The loss for epoch 8
0.9996956512331963
The running loss is:
8.158995658159256
The number of items in train is:
8
The loss for epoch 9
1.019874457269907
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 5.005669
48 30755 ... 1.284676
49 30756 ... -0.648910
50 30757 ... -1.834878
51 30758 ... -2.708139
52 30759 ... -3.450607
53 30760 ... -4.138366
54 30761 ... -2.162786
55 30762 ... -1.713670
56 30763 ... -1.903026
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tlrhr9xu wandb: Agent Starting Run: 5sh0r9aa with config: batch_size: 5 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5sh0r9aa
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.186528503894806
The number of items in train is:
9
The loss for epoch 0
1.3540587226549785
The running loss is:
9.87041188776493
The number of items in train is:
9
The loss for epoch 1
1.0967124319738812
The running loss is:
6.568782415241003
The number of items in train is:
9
The loss for epoch 2
0.7298647128045559
The running loss is:
6.8365867882966995
The number of items in train is:
9
The loss for epoch 3
0.7596207542551888
The running loss is:
7.052983522415161
The number of items in train is:
9
The loss for epoch 4
0.7836648358239068
The running loss is:
6.735688462853432
The number of items in train is:
9
The loss for epoch 5
0.7484098292059369
The running loss is:
6.670852228999138
The number of items in train is:
9
The loss for epoch 6
0.7412058032221265
The running loss is:
6.929626300930977
The number of items in train is:
9
The loss for epoch 7
0.7699584778812196
The running loss is:
6.557141110301018
The number of items in train is:
9
The loss for epoch 8
0.7285712344778909
The running loss is:
7.013601660728455
The number of items in train is:
9
The loss for epoch 9
0.7792890734142728
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 10.546264
48 30755 ... 9.607576
49 30756 ... 9.256057
50 30757 ... 9.132097
51 30758 ... 9.096332
52 30759 ... 9.094746
53 30760 ... 9.106406
54 30761 ... 9.037273
55 30762 ... 9.022756
56 30763 ... 9.029405
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5sh0r9aa wandb: Agent Starting Run: jwrpyn6n with config: batch_size: 5 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: jwrpyn6n
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.897263944149017
The number of items in train is:
9
The loss for epoch 0
1.877473771572113
The running loss is:
13.586029052734375
The number of items in train is:
9
The loss for epoch 1
1.5095587836371527
The running loss is:
11.505275323987007
The number of items in train is:
9
The loss for epoch 2
1.2783639248874452
The running loss is:
10.849119901657104
The number of items in train is:
9
The loss for epoch 3
1.2054577668507893
The running loss is:
10.990880310535431
The number of items in train is:
9
The loss for epoch 4
1.2212089233928256
The running loss is:
10.673891842365265
The number of items in train is:
9
The loss for epoch 5
1.1859879824850295
The running loss is:
10.410960853099823
The number of items in train is:
9
The loss for epoch 6
1.1567734281222026
The running loss is:
9.912422180175781
The number of items in train is:
9
The loss for epoch 7
1.1013802422417536
The running loss is:
9.722930133342743
The number of items in train is:
9
The loss for epoch 8
1.0803255703714159
The running loss is:
9.893279522657394
The number of items in train is:
9
The loss for epoch 9
1.0992532802952661
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 16.081408
48 30755 ... 18.041018
49 30756 ... 19.219566
50 30757 ... 19.854288
51 30758 ... 20.110369
52 30759 ... 20.102816
53 30760 ... 19.911705
54 30761 ... 20.893753
55 30762 ... 21.391663
56 30763 ... 21.552485
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jwrpyn6n wandb: Agent Starting Run: 61yhxkr5 with config: batch_size: 5 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 61yhxkr5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.252773106098175
The number of items in train is:
8
The loss for epoch 0
1.6565966382622719
The running loss is:
11.093029141426086
The number of items in train is:
8
The loss for epoch 1
1.3866286426782608
The running loss is:
8.942153513431549
The number of items in train is:
8
The loss for epoch 2
1.1177691891789436
The running loss is:
8.300474107265472
The number of items in train is:
8
The loss for epoch 3
1.037559263408184
The running loss is:
8.66373461484909
The number of items in train is:
8
The loss for epoch 4
1.0829668268561363
The running loss is:
8.129843354225159
The number of items in train is:
8
The loss for epoch 5
1.0162304192781448
The running loss is:
8.375961810350418
The number of items in train is:
8
The loss for epoch 6
1.0469952262938023
The running loss is:
8.051367044448853
The number of items in train is:
8
The loss for epoch 7
1.0064208805561066
The running loss is:
7.816939502954483
The number of items in train is:
8
The loss for epoch 8
0.9771174378693104
The running loss is:
7.919642895460129
The number of items in train is:
8
The loss for epoch 9
0.9899553619325161
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 5.484890
48 30755 ... 1.870857
49 30756 ... -0.053274
50 30757 ... -1.245361
51 30758 ... -2.120337
52 30759 ... -2.857944
53 30760 ... -3.536042
54 30761 ... -1.678325
55 30762 ... -1.232160
56 30763 ... -1.397465
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 61yhxkr5 wandb: Agent Starting Run: 9gucol9n with config: batch_size: 5 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 9gucol9n
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.346777260303497
The number of items in train is:
9
The loss for epoch 0
1.2607530289226108
The running loss is:
27.95102945715189
The number of items in train is:
9
The loss for epoch 1
3.105669939683543
The running loss is:
10.551504634320736
The number of items in train is:
9
The loss for epoch 2
1.172389403813415
The running loss is:
13.874582648277283
The number of items in train is:
9
The loss for epoch 3
1.5416202942530315
The running loss is:
7.543052405118942
The number of items in train is:
9
The loss for epoch 4
0.8381169339021047
The running loss is:
6.931498184800148
The number of items in train is:
9
The loss for epoch 5
0.7701664649777942
The running loss is:
6.799338757991791
The number of items in train is:
9
The loss for epoch 6
0.7554820842213101
The running loss is:
6.961371675133705
The number of items in train is:
9
The loss for epoch 7
0.7734857416815228
The running loss is:
6.578679084777832
The number of items in train is:
9
The loss for epoch 8
0.7309643427530924
The running loss is:
6.714740738272667
The number of items in train is:
9
The loss for epoch 9
0.7460823042525185
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 11.563630
48 30755 ... 11.000370
49 30756 ... 10.793115
50 30757 ... 10.731018
51 30758 ... 10.728108
52 30759 ... 10.749331
53 30760 ... 10.780396
54 30761 ... 10.658602
55 30762 ... 10.631351
56 30763 ... 10.642650
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9gucol9n wandb: Agent Starting Run: 559j47n1 with config: batch_size: 5 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 559j47n1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.399379521608353
The number of items in train is:
9
The loss for epoch 0
1.7110421690675948
The running loss is:
28.239181756973267
The number of items in train is:
9
The loss for epoch 1
3.1376868618859186
The running loss is:
13.408493876457214
The number of items in train is:
9
The loss for epoch 2
1.4898326529396906
The running loss is:
15.628408044576645
The number of items in train is:
9
The loss for epoch 3
1.7364897827307384
The running loss is:
10.764084279537201
The number of items in train is:
9
The loss for epoch 4
1.1960093643930223
The running loss is:
10.060381978750229
The number of items in train is:
9
The loss for epoch 5
1.1178202198611364
The running loss is:
9.791651472449303
The number of items in train is:
9
The loss for epoch 6
1.0879612747165892
The running loss is:
9.179567664861679
The number of items in train is:
9
The loss for epoch 7
1.0199519627624087
The running loss is:
8.98176957666874
The number of items in train is:
9
The loss for epoch 8
0.9979743974076377
The running loss is:
8.864021956920624
The number of items in train is:
9
The loss for epoch 9
0.984891328546736
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 14.776108
48 30755 ... 15.912499
49 30756 ... 16.591112
50 30757 ... 16.942139
51 30758 ... 17.058744
52 30759 ... 17.007603
53 30760 ... 16.836418
54 30761 ... 17.521439
55 30762 ... 17.877050
56 30763 ... 17.996941
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 559j47n1 wandb: Agent Starting Run: nf7t2ie9 with config: batch_size: 5 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: nf7t2ie9
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.581223011016846
The number of items in train is:
8
The loss for epoch 0
1.1976528763771057
The running loss is:
35.83604419231415
The number of items in train is:
8
The loss for epoch 1
4.4795055240392685
The running loss is:
11.085575520992279
The number of items in train is:
8
The loss for epoch 2
1.3856969401240349
The running loss is:
14.026957333087921
The number of items in train is:
8
The loss for epoch 3
1.7533696666359901
The running loss is:
8.350571095943451
The number of items in train is:
8
The loss for epoch 4
1.0438213869929314
The running loss is:
8.114606499671936
The number of items in train is:
8
The loss for epoch 5
1.014325812458992
The running loss is:
8.154320061206818
The number of items in train is:
8
The loss for epoch 6
1.0192900076508522
The running loss is:
7.604051381349564
The number of items in train is:
8
The loss for epoch 7
0.9505064226686954
The running loss is:
7.602997928857803
The number of items in train is:
8
The loss for epoch 8
0.9503747411072254
The running loss is:
7.65183824300766
The number of items in train is:
8
The loss for epoch 9
0.9564797803759575
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 6.058468
48 30755 ... 2.848610
49 30756 ... 1.165785
50 30757 ... 0.107837
51 30758 ... -0.694407
52 30759 ... -1.392015
53 30760 ... -2.046804
54 30761 ... -0.098818
55 30762 ... 0.328994
56 30763 ... 0.134736
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nf7t2ie9 wandb: Agent Starting Run: cl1kzlwf with config: batch_size: 5 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cl1kzlwf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
29.115166932344437
The number of items in train is:
9
The loss for epoch 0
3.235018548038271
The running loss is:
10.516705513000488
The number of items in train is:
9
The loss for epoch 1
1.168522834777832
The running loss is:
8.51107770204544
The number of items in train is:
9
The loss for epoch 2
0.9456753002272712
The running loss is:
8.960445433855057
The number of items in train is:
9
The loss for epoch 3
0.9956050482061174
The running loss is:
13.343494325876236
The number of items in train is:
9
The loss for epoch 4
1.482610480652915
The running loss is:
8.549514725804329
The number of items in train is:
9
The loss for epoch 5
0.9499460806449255
The running loss is:
12.743834301829338
The number of items in train is:
9
The loss for epoch 6
1.4159815890921488
The running loss is:
11.443218156695366
The number of items in train is:
9
The loss for epoch 7
1.2714686840772629
The running loss is:
7.235250249505043
The number of items in train is:
9
The loss for epoch 8
0.8039166943894492
The running loss is:
8.449952185153961
The number of items in train is:
9
The loss for epoch 9
0.9388835761282179
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 9.708012
48 30755 ... 8.497513
49 30756 ... 8.352589
50 30757 ... 8.753163
51 30758 ... 9.432993
52 30759 ... 10.255782
53 30760 ... 11.151757
54 30761 ... 8.761843
55 30762 ... 8.013142
56 30763 ... 8.104626
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cl1kzlwf wandb: Agent Starting Run: pdmnlk1y with config: batch_size: 5 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: pdmnlk1y
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
26.819443345069885
The number of items in train is:
9
The loss for epoch 0
2.9799381494522095
The running loss is:
14.902421951293945
The number of items in train is:
9
The loss for epoch 1
1.6558246612548828
The running loss is:
17.069870591163635
The number of items in train is:
9
The loss for epoch 2
1.8966522879070706
The running loss is:
11.382362842559814
The number of items in train is:
9
The loss for epoch 3
1.2647069825066461
The running loss is:
11.657361149787903
The number of items in train is:
9
The loss for epoch 4
1.2952623499764337
The running loss is:
13.20745787024498
The number of items in train is:
9
The loss for epoch 5
1.4674953189161088
The running loss is:
9.443842113018036
The number of items in train is:
9
The loss for epoch 6
1.0493157903353374
The running loss is:
11.438809677958488
The number of items in train is:
9
The loss for epoch 7
1.2709788531064987
The running loss is:
8.55271452665329
The number of items in train is:
9
The loss for epoch 8
0.9503016140725877
The running loss is:
10.242311969399452
The number of items in train is:
9
The loss for epoch 9
1.1380346632666059
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 16.249252
48 30755 ... 17.867855
49 30756 ... 18.567770
50 30757 ... 18.750107
51 30758 ... 18.640844
52 30759 ... 18.367302
53 30760 ... 18.001202
54 30761 ... 19.066870
55 30762 ... 19.455267
56 30763 ... 19.462097
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pdmnlk1y wandb: Agent Starting Run: v4p1w5d6 with config: batch_size: 5 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: v4p1w5d6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
29.159477710723877
The number of items in train is:
8
The loss for epoch 0
3.6449347138404846
The running loss is:
10.356956481933594
The number of items in train is:
8
The loss for epoch 1
1.2946195602416992
The running loss is:
17.295407086610794
The number of items in train is:
8
The loss for epoch 2
2.1619258858263493
The running loss is:
10.114732325077057
The number of items in train is:
8
The loss for epoch 3
1.264341540634632
The running loss is:
9.823338657617569
The number of items in train is:
8
The loss for epoch 4
1.2279173322021961
The running loss is:
8.202937006950378
The number of items in train is:
8
The loss for epoch 5
1.0253671258687973
The running loss is:
8.357675984501839
The number of items in train is:
8
The loss for epoch 6
1.0447094980627298
The running loss is:
7.424637317657471
The number of items in train is:
8
The loss for epoch 7
0.9280796647071838
The running loss is:
7.2614090740680695
The number of items in train is:
8
The loss for epoch 8
0.9076761342585087
The running loss is:
7.0375045388937
The number of items in train is:
8
The loss for epoch 9
0.8796880673617125
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
46 30753 ... 0.000000
47 30754 ... 7.158503
48 30755 ... 4.625562
49 30756 ... 3.375854
50 30757 ... 2.623850
51 30758 ... 2.064883
52 30759 ... 1.580785
53 30760 ... 1.125725
54 30761 ... 2.553036
55 30762 ... 2.839321
56 30763 ... 2.683055
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v4p1w5d6 wandb: Agent Starting Run: xx7hdryc with config: batch_size: 5 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: xx7hdryc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.653952911496162
The number of items in train is:
9
The loss for epoch 0
1.294883656832907
The running loss is:
6.35406494140625
The number of items in train is:
9
The loss for epoch 1
0.7060072157118056
The running loss is:
6.448800578713417
The number of items in train is:
9
The loss for epoch 2
0.7165333976348242
The running loss is:
6.175214782357216
The number of items in train is:
9
The loss for epoch 3
0.6861349758174684
The running loss is:
6.013192266225815
The number of items in train is:
9
The loss for epoch 4
0.6681324740250906
The running loss is:
6.216562658548355
The number of items in train is:
9
The loss for epoch 5
0.6907291842831506
The running loss is:
5.737043023109436
The number of items in train is:
9
The loss for epoch 6
0.6374492247899374
The running loss is:
5.503724917769432
The number of items in train is:
9
The loss for epoch 7
0.6115249908632703
The running loss is:
4.904528111219406
The number of items in train is:
9
The loss for epoch 8
0.5449475679132674
The running loss is:
5.226170241832733
The number of items in train is:
9
The loss for epoch 9
0.5806855824258592
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.194837
48 30755 ... 16.856466
49 30756 ... 16.424501
50 30757 ... 17.301683
51 30758 ... 16.259554
52 30759 ... 15.276786
53 30760 ... 13.607736
54 30761 ... 13.129473
55 30762 ... 17.536375
56 30763 ... 17.261248
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xx7hdryc wandb: Agent Starting Run: 5gp21eq4 with config: batch_size: 5 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 5gp21eq4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.606136918067932
The number of items in train is:
8
The loss for epoch 0
1.3257671147584915
The running loss is:
7.5615354180336
The number of items in train is:
8
The loss for epoch 1
0.9451919272542
The running loss is:
7.4385921359062195
The number of items in train is:
8
The loss for epoch 2
0.9298240169882774
The running loss is:
7.043540298938751
The number of items in train is:
8
The loss for epoch 3
0.8804425373673439
The running loss is:
6.746666252613068
The number of items in train is:
8
The loss for epoch 4
0.8433332815766335
The running loss is:
6.270362347364426
The number of items in train is:
8
The loss for epoch 5
0.7837952934205532
The running loss is:
6.0092626214027405
The number of items in train is:
8
The loss for epoch 6
0.7511578276753426
The running loss is:
6.145449280738831
The number of items in train is:
8
The loss for epoch 7
0.7681811600923538
The running loss is:
5.825879514217377
The number of items in train is:
8
The loss for epoch 8
0.7282349392771721
The running loss is:
5.999978452920914
The number of items in train is:
8
The loss for epoch 9
0.7499973066151142
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.111321
48 30755 ... 6.885062
49 30756 ... 3.949093
50 30757 ... 1.974898
51 30758 ... -1.738332
52 30759 ... -5.849308
53 30760 ... -11.026432
54 30761 ... -15.751204
55 30762 ... -15.569290
56 30763 ... -18.938940
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5gp21eq4 wandb: Agent Starting Run: v7w14fvq with config: batch_size: 5 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: v7w14fvq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.157624810934067
The number of items in train is:
8
The loss for epoch 0
1.2697031013667583
The running loss is:
6.297411605715752
The number of items in train is:
8
The loss for epoch 1
0.787176450714469
The running loss is:
6.1504600048065186
The number of items in train is:
8
The loss for epoch 2
0.7688075006008148
The running loss is:
6.285173416137695
The number of items in train is:
8
The loss for epoch 3
0.7856466770172119
The running loss is:
5.583762004971504
The number of items in train is:
8
The loss for epoch 4
0.697970250621438
The running loss is:
5.8202831000089645
The number of items in train is:
8
The loss for epoch 5
0.7275353875011206
The running loss is:
5.58960173279047
The number of items in train is:
8
The loss for epoch 6
0.6987002165988088
The running loss is:
5.187306389212608
The number of items in train is:
8
The loss for epoch 7
0.648413298651576
The running loss is:
5.519324317574501
The number of items in train is:
8
The loss for epoch 8
0.6899155396968126
The running loss is:
5.479003980755806
The number of items in train is:
8
The loss for epoch 9
0.6848754975944757
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.505090
48 30755 ... 8.611543
49 30756 ... 7.433668
50 30757 ... 6.379976
51 30758 ... 4.317859
52 30759 ... 1.654876
53 30760 ... -1.738726
54 30761 ... -2.300702
55 30762 ... -1.567690
56 30763 ... -2.170553
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v7w14fvq wandb: Agent Starting Run: ukec4csi with config: batch_size: 5 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ukec4csi
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.871211767196655
The number of items in train is:
9
The loss for epoch 0
1.3190235296885173
The running loss is:
11.86011016368866
The number of items in train is:
9
The loss for epoch 1
1.3177900181876288
The running loss is:
6.418770670890808
The number of items in train is:
9
The loss for epoch 2
0.7131967412100898
The running loss is:
6.4102838188409805
The number of items in train is:
9
The loss for epoch 3
0.7122537576489978
The running loss is:
6.108351901173592
The number of items in train is:
9
The loss for epoch 4
0.6787057667970657
The running loss is:
5.973604336380959
The number of items in train is:
9
The loss for epoch 5
0.6637338151534399
The running loss is:
5.5479738265275955
The number of items in train is:
9
The loss for epoch 6
0.616441536280844
The running loss is:
5.1741392612457275
The number of items in train is:
9
The loss for epoch 7
0.5749043623606364
The running loss is:
4.4630467891693115
The number of items in train is:
9
The loss for epoch 8
0.49589408768547905
The running loss is:
4.964875191450119
The number of items in train is:
9
The loss for epoch 9
0.5516527990500132
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.930080
48 30755 ... 16.040146
49 30756 ... 15.320904
50 30757 ... 15.965147
51 30758 ... 14.722304
52 30759 ... 13.738050
53 30760 ... 11.988651
54 30761 ... 10.827065
55 30762 ... 15.583311
56 30763 ... 15.162140
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ukec4csi wandb: Agent Starting Run: ft4g04qn with config: batch_size: 5 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ft4g04qn
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.880632519721985
The number of items in train is:
8
The loss for epoch 0
1.360079064965248
The running loss is:
9.620780944824219
The number of items in train is:
8
The loss for epoch 1
1.2025976181030273
The running loss is:
7.736795485019684
The number of items in train is:
8
The loss for epoch 2
0.9670994356274605
The running loss is:
6.95757669210434
The number of items in train is:
8
The loss for epoch 3
0.8696970865130424
The running loss is:
6.781202018260956
The number of items in train is:
8
The loss for epoch 4
0.8476502522826195
The running loss is:
6.057494938373566
The number of items in train is:
8
The loss for epoch 5
0.7571868672966957
The running loss is:
5.54942125082016
The number of items in train is:
8
The loss for epoch 6
0.69367765635252
The running loss is:
5.526401251554489
The number of items in train is:
8
The loss for epoch 7
0.6908001564443111
The running loss is:
5.341130912303925
The number of items in train is:
8
The loss for epoch 8
0.6676413640379906
The running loss is:
5.290408372879028
The number of items in train is:
8
The loss for epoch 9
0.6613010466098785
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.421013
48 30755 ... 7.693488
49 30756 ... 4.838378
50 30757 ... 2.830646
51 30758 ... -1.172961
52 30759 ... -5.462883
53 30760 ... -11.114449
54 30761 ... -16.412426
55 30762 ... -16.639225
56 30763 ... -20.939789
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ft4g04qn wandb: Agent Starting Run: u1wlcs5o with config: batch_size: 5 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u1wlcs5o
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.196498736739159
The number of items in train is:
8
The loss for epoch 0
1.3995623420923948
The running loss is:
8.67428719997406
The number of items in train is:
8
The loss for epoch 1
1.0842858999967575
The running loss is:
6.3885288536548615
The number of items in train is:
8
The loss for epoch 2
0.7985661067068577
The running loss is:
6.005099095404148
The number of items in train is:
8
The loss for epoch 3
0.7506373869255185
The running loss is:
5.570761099457741
The number of items in train is:
8
The loss for epoch 4
0.6963451374322176
The running loss is:
5.671713694930077
The number of items in train is:
8
The loss for epoch 5
0.7089642118662596
The running loss is:
5.326850637793541
The number of items in train is:
8
The loss for epoch 6
0.6658563297241926
The running loss is:
4.999603778123856
The number of items in train is:
8
The loss for epoch 7
0.624950472265482
The running loss is:
5.124610349535942
The number of items in train is:
8
The loss for epoch 8
0.6405762936919928
The running loss is:
5.118088111281395
The number of items in train is:
8
The loss for epoch 9
0.6397610139101744
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.308200
48 30755 ... 5.241625
49 30756 ... 3.383986
50 30757 ... 0.737024
51 30758 ... -2.849844
52 30759 ... -7.332001
53 30760 ... -12.688560
54 30761 ... -12.326498
55 30762 ... -14.071939
56 30763 ... -16.703213
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u1wlcs5o wandb: Agent Starting Run: pi8csar3 with config: batch_size: 5 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: pi8csar3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.041293114423752
The number of items in train is:
9
The loss for epoch 0
1.1156992349359725
The running loss is:
24.0467449426651
The number of items in train is:
9
The loss for epoch 1
2.671860549185011
The running loss is:
11.829259186983109
The number of items in train is:
9
The loss for epoch 2
1.314362131887012
The running loss is:
8.914239928126335
The number of items in train is:
9
The loss for epoch 3
0.9904711031251483
The running loss is:
6.624034374952316
The number of items in train is:
9
The loss for epoch 4
0.7360038194391463
The running loss is:
6.917576104402542
The number of items in train is:
9
The loss for epoch 5
0.768619567155838
The running loss is:
5.983533605933189
The number of items in train is:
9
The loss for epoch 6
0.66483706732591
The running loss is:
5.81503838300705
The number of items in train is:
9
The loss for epoch 7
0.6461153758896722
The running loss is:
5.106647074222565
The number of items in train is:
9
The loss for epoch 8
0.5674052304691739
The running loss is:
5.564130909740925
The number of items in train is:
9
The loss for epoch 9
0.6182367677489916
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 15.471273
48 30755 ... 17.168171
49 30756 ... 17.622458
50 30757 ... 17.658239
51 30758 ... 17.125072
52 30759 ... 16.369062
53 30760 ... 15.348657
54 30761 ... 16.736712
55 30762 ... 18.282732
56 30763 ... 18.265202
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pi8csar3 wandb: Agent Starting Run: 4hehj93f with config: batch_size: 5 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4hehj93f
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.713887721300125
The number of items in train is:
8
The loss for epoch 0
1.0892359651625156
The running loss is:
22.801980674266815
The number of items in train is:
8
The loss for epoch 1
2.850247584283352
The running loss is:
8.347535133361816
The number of items in train is:
8
The loss for epoch 2
1.043441891670227
The running loss is:
9.818920910358429
The number of items in train is:
8
The loss for epoch 3
1.2273651137948036
The running loss is:
7.308171451091766
The number of items in train is:
8
The loss for epoch 4
0.9135214313864708
The running loss is:
6.845404148101807
The number of items in train is:
8
The loss for epoch 5
0.8556755185127258
The running loss is:
6.43958380818367
The number of items in train is:
8
The loss for epoch 6
0.8049479760229588
The running loss is:
6.40879088640213
The number of items in train is:
8
The loss for epoch 7
0.8010988608002663
The running loss is:
6.1408664882183075
The number of items in train is:
8
The loss for epoch 8
0.7676083110272884
The running loss is:
5.660664469003677
The number of items in train is:
8
The loss for epoch 9
0.7075830586254597
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.766214
48 30755 ... 6.847561
49 30756 ... 3.781909
50 30757 ... 2.416294
51 30758 ... 0.047228
52 30759 ... -1.721929
53 30760 ... -3.810858
54 30761 ... -6.423064
55 30762 ... -5.039513
56 30763 ... -5.555659
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4hehj93f wandb: Agent Starting Run: 6cko91sl with config: batch_size: 5 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 6cko91sl
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.506135255098343
The number of items in train is:
8
The loss for epoch 0
1.0632669068872929
The running loss is:
24.01819033920765
The number of items in train is:
8
The loss for epoch 1
3.002273792400956
The running loss is:
10.206629455089569
The number of items in train is:
8
The loss for epoch 2
1.2758286818861961
The running loss is:
9.913901567459106
The number of items in train is:
8
The loss for epoch 3
1.2392376959323883
The running loss is:
6.586266487836838
The number of items in train is:
8
The loss for epoch 4
0.8232833109796047
The running loss is:
6.10785585641861
The number of items in train is:
8
The loss for epoch 5
0.7634819820523262
The running loss is:
5.772560715675354
The number of items in train is:
8
The loss for epoch 6
0.7215700894594193
The running loss is:
5.264330431818962
The number of items in train is:
8
The loss for epoch 7
0.6580413039773703
The running loss is:
5.442826643586159
The number of items in train is:
8
The loss for epoch 8
0.6803533304482698
The running loss is:
4.980601117014885
The number of items in train is:
8
The loss for epoch 9
0.6225751396268606
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.926193
48 30755 ... 9.950300
49 30756 ... 9.398391
50 30757 ... 8.685193
51 30758 ... 7.131873
52 30759 ... 4.907981
53 30760 ... 1.956089
54 30761 ... 1.788214
55 30762 ... 2.207295
56 30763 ... 1.670653
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6cko91sl wandb: Agent Starting Run: 1y5z9zl3 with config: batch_size: 5 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1y5z9zl3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
34.98532968759537
The number of items in train is:
9
The loss for epoch 0
3.8872588541772632
The running loss is:
12.941614404320717
The number of items in train is:
9
The loss for epoch 1
1.4379571560356352
The running loss is:
11.81175396591425
The number of items in train is:
9
The loss for epoch 2
1.3124171073238056
The running loss is:
13.589459389448166
The number of items in train is:
9
The loss for epoch 3
1.5099399321609073
The running loss is:
10.549855262041092
The number of items in train is:
9
The loss for epoch 4
1.172206140226788
The running loss is:
12.399509191513062
The number of items in train is:
9
The loss for epoch 5
1.3777232435014513
The running loss is:
13.321157723665237
The number of items in train is:
9
The loss for epoch 6
1.480128635962804
The running loss is:
8.162745237350464
The number of items in train is:
9
The loss for epoch 7
0.9069716930389404
The running loss is:
8.067213207483292
The number of items in train is:
9
The loss for epoch 8
0.896357023053699
The running loss is:
7.0703848749399185
The number of items in train is:
9
The loss for epoch 9
0.7855983194377687
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.806156
48 30755 ... 14.069129
49 30756 ... 13.659444
50 30757 ... 13.352436
51 30758 ... 12.880804
52 30759 ... 12.412155
53 30760 ... 11.924775
54 30761 ... 12.530951
55 30762 ... 13.979243
56 30763 ... 13.637586
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1y5z9zl3 wandb: Agent Starting Run: bv342o38 with config: batch_size: 5 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: bv342o38
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.1297847032547
The number of items in train is:
8
The loss for epoch 0
2.8912230879068375
The running loss is:
9.419984936714172
The number of items in train is:
8
The loss for epoch 1
1.1774981170892715
The running loss is:
15.98174238204956
The number of items in train is:
8
The loss for epoch 2
1.997717797756195
The running loss is:
9.02855908870697
The number of items in train is:
8
The loss for epoch 3
1.1285698860883713
The running loss is:
7.561536103487015
The number of items in train is:
8
The loss for epoch 4
0.9451920129358768
The running loss is:
6.622726082801819
The number of items in train is:
8
The loss for epoch 5
0.8278407603502274
The running loss is:
6.519628286361694
The number of items in train is:
8
The loss for epoch 6
0.8149535357952118
The running loss is:
5.425025045871735
The number of items in train is:
8
The loss for epoch 7
0.6781281307339668
The running loss is:
7.119292467832565
The number of items in train is:
8
The loss for epoch 8
0.8899115584790707
The running loss is:
6.246462732553482
The number of items in train is:
8
The loss for epoch 9
0.7808078415691853
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.322372
48 30755 ... 6.233348
49 30756 ... 5.780288
50 30757 ... 5.569169
51 30758 ... 5.308512
52 30759 ... 5.067289
53 30760 ... 4.781678
54 30761 ... 2.610401
55 30762 ... 4.669430
56 30763 ... 4.904677
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bv342o38 wandb: Agent Starting Run: v6al9cws with config: batch_size: 5 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: v6al9cws
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.912554055452347
The number of items in train is:
8
The loss for epoch 0
2.8640692569315434
The running loss is:
7.984839051961899
The number of items in train is:
8
The loss for epoch 1
0.9981048814952374
The running loss is:
8.602033376693726
The number of items in train is:
8
The loss for epoch 2
1.0752541720867157
The running loss is:
9.541735291481018
The number of items in train is:
8
The loss for epoch 3
1.1927169114351273
The running loss is:
6.243432849645615
The number of items in train is:
8
The loss for epoch 4
0.7804291062057018
The running loss is:
7.455722868442535
The number of items in train is:
8
The loss for epoch 5
0.9319653585553169
The running loss is:
6.309693947434425
The number of items in train is:
8
The loss for epoch 6
0.7887117434293032
The running loss is:
6.356328025460243
The number of items in train is:
8
The loss for epoch 7
0.7945410031825304
The running loss is:
6.21287739276886
The number of items in train is:
8
The loss for epoch 8
0.7766096740961075
The running loss is:
5.354219913482666
The number of items in train is:
8
The loss for epoch 9
0.6692774891853333
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.646266
48 30755 ... 10.808380
49 30756 ... 10.536748
50 30757 ... 10.119283
51 30758 ... 9.140769
52 30759 ... 7.776768
53 30760 ... 6.020148
54 30761 ... 6.451089
55 30762 ... 7.264283
56 30763 ... 7.389930
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v6al9cws wandb: Agent Starting Run: o3oq5f4z with config: batch_size: 5 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: o3oq5f4z
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.30842438340187
The number of items in train is:
8
The loss for epoch 0
1.1635530479252338
The running loss is:
9.48618969321251
The number of items in train is:
8
The loss for epoch 1
1.1857737116515636
The running loss is:
5.621234282851219
The number of items in train is:
8
The loss for epoch 2
0.7026542853564024
The running loss is:
4.817091893404722
The number of items in train is:
8
The loss for epoch 3
0.6021364866755903
The running loss is:
4.489563524723053
The number of items in train is:
8
The loss for epoch 4
0.5611954405903816
The running loss is:
4.262367948889732
The number of items in train is:
8
The loss for epoch 5
0.5327959936112165
The running loss is:
4.1890451312065125
The number of items in train is:
8
The loss for epoch 6
0.5236306414008141
The running loss is:
4.206894904375076
The number of items in train is:
8
The loss for epoch 7
0.5258618630468845
The running loss is:
4.1976680383086205
The number of items in train is:
8
The loss for epoch 8
0.5247085047885776
The running loss is:
3.844587281346321
The number of items in train is:
8
The loss for epoch 9
0.48057341016829014
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.245362
48 30755 ... 7.406672
49 30756 ... 13.971702
50 30757 ... 13.071504
51 30758 ... 12.476460
52 30759 ... 12.218643
53 30760 ... 10.048891
54 30761 ... 9.944292
55 30762 ... 10.011600
56 30763 ... 15.057905
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: o3oq5f4z wandb: Agent Starting Run: l7gk8jk5 with config: batch_size: 5 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: l7gk8jk5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.721231788396835
The number of items in train is:
8
The loss for epoch 0
1.3401539735496044
The running loss is:
6.999983549118042
The number of items in train is:
8
The loss for epoch 1
0.8749979436397552
The running loss is:
6.762904524803162
The number of items in train is:
8
The loss for epoch 2
0.8453630656003952
The running loss is:
6.13987572491169
The number of items in train is:
8
The loss for epoch 3
0.7674844656139612
The running loss is:
5.951361909508705
The number of items in train is:
8
The loss for epoch 4
0.7439202386885881
The running loss is:
5.882794544100761
The number of items in train is:
8
The loss for epoch 5
0.7353493180125952
The running loss is:
5.625875897705555
The number of items in train is:
8
The loss for epoch 6
0.7032344872131944
The running loss is:
5.734223559498787
The number of items in train is:
8
The loss for epoch 7
0.7167779449373484
The running loss is:
5.470184274017811
The number of items in train is:
8
The loss for epoch 8
0.6837730342522264
The running loss is:
4.977894231677055
The number of items in train is:
8
The loss for epoch 9
0.6222367789596319
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.194105
48 30755 ... 6.603125
49 30756 ... 11.639103
50 30757 ... 11.402129
51 30758 ... 11.610652
52 30759 ... 11.500878
53 30760 ... 9.903611
54 30761 ... 9.999037
55 30762 ... 10.313538
56 30763 ... 14.491574
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l7gk8jk5 wandb: Agent Starting Run: n40k40ot with config: batch_size: 5 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: n40k40ot
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.84519910812378
The number of items in train is:
8
The loss for epoch 0
1.2306498885154724
The running loss is:
6.748609364032745
The number of items in train is:
8
The loss for epoch 1
0.8435761705040932
The running loss is:
6.234087198972702
The number of items in train is:
8
The loss for epoch 2
0.7792608998715878
The running loss is:
5.676519811153412
The number of items in train is:
8
The loss for epoch 3
0.7095649763941765
The running loss is:
5.602851450443268
The number of items in train is:
8
The loss for epoch 4
0.7003564313054085
The running loss is:
5.303595423698425
The number of items in train is:
8
The loss for epoch 5
0.6629494279623032
The running loss is:
5.084870457649231
The number of items in train is:
8
The loss for epoch 6
0.6356088072061539
The running loss is:
5.002656936645508
The number of items in train is:
8
The loss for epoch 7
0.6253321170806885
The running loss is:
4.769860535860062
The number of items in train is:
8
The loss for epoch 8
0.5962325669825077
The running loss is:
4.391438692808151
The number of items in train is:
8
The loss for epoch 9
0.5489298366010189
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.658195
48 30755 ... 10.081340
49 30756 ... 15.058569
50 30757 ... 15.923815
51 30758 ... 16.395542
52 30759 ... 17.664595
53 30760 ... 17.107052
54 30761 ... 22.228762
55 30762 ... 23.952763
56 30763 ... 29.323387
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n40k40ot wandb: Agent Starting Run: 9tt63aws with config: batch_size: 5 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 9tt63aws
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.10678744316101
The number of items in train is:
8
The loss for epoch 0
1.0133484303951263
The running loss is:
27.54156595468521
The number of items in train is:
8
The loss for epoch 1
3.4426957443356514
The running loss is:
6.247965717688203
The number of items in train is:
8
The loss for epoch 2
0.7809957147110254
The running loss is:
6.217851877212524
The number of items in train is:
8
The loss for epoch 3
0.7772314846515656
The running loss is:
5.920749947428703
The number of items in train is:
8
The loss for epoch 4
0.7400937434285879
The running loss is:
4.904174625873566
The number of items in train is:
8
The loss for epoch 5
0.6130218282341957
The running loss is:
4.424663543701172
The number of items in train is:
8
The loss for epoch 6
0.5530829429626465
The running loss is:
4.41470830142498
The number of items in train is:
8
The loss for epoch 7
0.5518385376781225
The running loss is:
4.161341153085232
The number of items in train is:
8
The loss for epoch 8
0.520167644135654
The running loss is:
3.9557350426912308
The number of items in train is:
8
The loss for epoch 9
0.49446688033640385
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.901354
48 30755 ... 7.838363
49 30756 ... 13.712195
50 30757 ... 12.818233
51 30758 ... 12.069808
52 30759 ... 11.796654
53 30760 ... 9.732699
54 30761 ... 9.699532
55 30762 ... 9.651850
56 30763 ... 14.155675
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9tt63aws wandb: Agent Starting Run: dzxow86q with config: batch_size: 5 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: dzxow86q
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.758483454585075
The number of items in train is:
8
The loss for epoch 0
1.3448104318231344
The running loss is:
11.171189188957214
The number of items in train is:
8
The loss for epoch 1
1.3963986486196518
The running loss is:
6.5673965737223625
The number of items in train is:
8
The loss for epoch 2
0.8209245717152953
The running loss is:
6.287336528301239
The number of items in train is:
8
The loss for epoch 3
0.7859170660376549
The running loss is:
5.87205146253109
The number of items in train is:
8
The loss for epoch 4
0.7340064328163862
The running loss is:
5.778154879808426
The number of items in train is:
8
The loss for epoch 5
0.7222693599760532
The running loss is:
5.273692026734352
The number of items in train is:
8
The loss for epoch 6
0.659211503341794
The running loss is:
5.136383637785912
The number of items in train is:
8
The loss for epoch 7
0.642047954723239
The running loss is:
4.941792532801628
The number of items in train is:
8
The loss for epoch 8
0.6177240666002035
The running loss is:
4.391803033649921
The number of items in train is:
8
The loss for epoch 9
0.5489753792062402
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.843055
48 30755 ... 8.735225
49 30756 ... 11.784624
50 30757 ... 11.745650
51 30758 ... 11.402711
52 30759 ... 10.388110
53 30760 ... 8.058597
54 30761 ... 9.430935
55 30762 ... 10.906927
56 30763 ... 13.199764
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: dzxow86q wandb: Agent Starting Run: oyieacp4 with config: batch_size: 5 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: oyieacp4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.876974672079086
The number of items in train is:
8
The loss for epoch 0
1.2346218340098858
The running loss is:
10.934117525815964
The number of items in train is:
8
The loss for epoch 1
1.3667646907269955
The running loss is:
6.11262384057045
The number of items in train is:
8
The loss for epoch 2
0.7640779800713062
The running loss is:
5.829475224018097
The number of items in train is:
8
The loss for epoch 3
0.7286844030022621
The running loss is:
5.622194975614548
The number of items in train is:
8
The loss for epoch 4
0.7027743719518185
The running loss is:
5.299667567014694
The number of items in train is:
8
The loss for epoch 5
0.6624584458768368
The running loss is:
4.95116651058197
The number of items in train is:
8
The loss for epoch 6
0.6188958138227463
The running loss is:
4.8218607902526855
The number of items in train is:
8
The loss for epoch 7
0.6027325987815857
The running loss is:
4.772080212831497
The number of items in train is:
8
The loss for epoch 8
0.5965100266039371
The running loss is:
3.9954182356595993
The number of items in train is:
8
The loss for epoch 9
0.4994272794574499
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.704037
48 30755 ... 7.192714
49 30756 ... 10.031803
50 30757 ... 10.899514
51 30758 ... 11.257930
52 30759 ... 11.452247
53 30760 ... 10.973282
54 30761 ... 12.872341
55 30762 ... 12.492766
56 30763 ... 16.084013
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: oyieacp4 wandb: Agent Starting Run: caveqhc6 with config: batch_size: 5 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: caveqhc6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.880411952733994
The number of items in train is:
8
The loss for epoch 0
1.3600514940917492
The running loss is:
43.80143243074417
The number of items in train is:
8
The loss for epoch 1
5.475179053843021
The running loss is:
15.616842031478882
The number of items in train is:
8
The loss for epoch 2
1.9521052539348602
The running loss is:
9.589914422482252
The number of items in train is:
8
The loss for epoch 3
1.1987393028102815
The running loss is:
6.671413034200668
The number of items in train is:
8
The loss for epoch 4
0.8339266292750835
The running loss is:
7.4757488667964935
The number of items in train is:
8
The loss for epoch 5
0.9344686083495617
The running loss is:
4.646433234214783
The number of items in train is:
8
The loss for epoch 6
0.5808041542768478
The running loss is:
5.482744470238686
The number of items in train is:
8
The loss for epoch 7
0.6853430587798357
The running loss is:
4.8297248259186745
The number of items in train is:
8
The loss for epoch 8
0.6037156032398343
The running loss is:
4.43698213994503
The number of items in train is:
8
The loss for epoch 9
0.5546227674931288
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.569696
48 30755 ... 9.416870
49 30756 ... 13.286760
50 30757 ... 12.562493
51 30758 ... 11.830906
52 30759 ... 11.178302
53 30760 ... 9.640971
54 30761 ... 9.453139
55 30762 ... 9.259923
56 30763 ... 12.173406
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: caveqhc6 wandb: Agent Starting Run: nceedklu with config: batch_size: 5 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: nceedklu
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.912759125232697
The number of items in train is:
8
The loss for epoch 0
1.114094890654087
The running loss is:
25.029663145542145
The number of items in train is:
8
The loss for epoch 1
3.128707893192768
The running loss is:
10.025477290153503
The number of items in train is:
8
The loss for epoch 2
1.253184661269188
The running loss is:
14.02464845776558
The number of items in train is:
8
The loss for epoch 3
1.7530810572206974
The running loss is:
7.915584564208984
The number of items in train is:
8
The loss for epoch 4
0.989448070526123
The running loss is:
6.710186213254929
The number of items in train is:
8
The loss for epoch 5
0.8387732766568661
The running loss is:
6.474571600556374
The number of items in train is:
8
The loss for epoch 6
0.8093214500695467
The running loss is:
6.211176082491875
The number of items in train is:
8
The loss for epoch 7
0.7763970103114843
The running loss is:
6.195676773786545
The number of items in train is:
8
The loss for epoch 8
0.7744595967233181
The running loss is:
5.697741895914078
The number of items in train is:
8
The loss for epoch 9
0.7122177369892597
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.836226
48 30755 ... 10.511021
49 30756 ... 14.086117
50 30757 ... 13.573318
51 30758 ... 13.186073
52 30759 ... 13.511204
53 30760 ... 12.587166
54 30761 ... 13.003458
55 30762 ... 13.056839
56 30763 ... 15.238908
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nceedklu wandb: Agent Starting Run: 0eqou6e5 with config: batch_size: 5 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 0eqou6e5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
7.586898952722549
The number of items in train is:
8
The loss for epoch 0
0.9483623690903187
The running loss is:
25.946052193641663
The number of items in train is:
8
The loss for epoch 1
3.243256524205208
The running loss is:
7.6804980635643005
The number of items in train is:
8
The loss for epoch 2
0.9600622579455376
The running loss is:
9.825101613998413
The number of items in train is:
8
The loss for epoch 3
1.2281377017498016
The running loss is:
7.51312929391861
The number of items in train is:
8
The loss for epoch 4
0.9391411617398262
The running loss is:
6.463720321655273
The number of items in train is:
8
The loss for epoch 5
0.8079650402069092
The running loss is:
6.129735618829727
The number of items in train is:
8
The loss for epoch 6
0.7662169523537159
The running loss is:
5.783123850822449
The number of items in train is:
8
The loss for epoch 7
0.7228904813528061
The running loss is:
5.273890644311905
The number of items in train is:
8
The loss for epoch 8
0.6592363305389881
The running loss is:
4.53999987244606
The number of items in train is:
8
The loss for epoch 9
0.5674999840557575
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.657432
48 30755 ... 8.412302
49 30756 ... 10.765085
50 30757 ... 11.026249
51 30758 ... 10.217522
52 30759 ... 8.858908
53 30760 ... 6.510315
54 30761 ... 9.282034
55 30762 ... 8.430615
56 30763 ... 10.268279
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0eqou6e5 wandb: Agent Starting Run: 5pne6ual with config: batch_size: 5 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5pne6ual
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
77.71084105968475
The number of items in train is:
8
The loss for epoch 0
9.713855132460594
The running loss is:
5.338430866599083
The number of items in train is:
8
The loss for epoch 1
0.6673038583248854
The running loss is:
27.426336839795113
The number of items in train is:
8
The loss for epoch 2
3.428292104974389
The running loss is:
74.70189869403839
The number of items in train is:
8
The loss for epoch 3
9.337737336754799
The running loss is:
16.624776780605316
The number of items in train is:
8
The loss for epoch 4
2.0780970975756645
The running loss is:
22.714191049337387
The number of items in train is:
8
The loss for epoch 5
2.8392738811671734
The running loss is:
8.933165550231934
The number of items in train is:
8
The loss for epoch 6
1.1166456937789917
The running loss is:
10.674087047576904
The number of items in train is:
8
The loss for epoch 7
1.334260880947113
The running loss is:
7.016788870096207
The number of items in train is:
8
The loss for epoch 8
0.8770986087620258
The running loss is:
5.2304157465696335
The number of items in train is:
8
The loss for epoch 9
0.6538019683212042
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.728264
48 30755 ... 12.739908
49 30756 ... 15.023680
50 30757 ... 15.135052
51 30758 ... 14.314179
52 30759 ... 13.451766
53 30760 ... 12.209122
54 30761 ... 15.023045
55 30762 ... 15.040199
56 30763 ... 15.918568
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5pne6ual wandb: Agent Starting Run: uwmkpwjd with config: batch_size: 5 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: uwmkpwjd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
40.486722499132156
The number of items in train is:
8
The loss for epoch 0
5.0608403123915195
The running loss is:
7.990162819623947
The number of items in train is:
8
The loss for epoch 1
0.9987703524529934
The running loss is:
16.418078929185867
The number of items in train is:
8
The loss for epoch 2
2.0522598661482334
The running loss is:
37.9519681930542
The number of items in train is:
8
The loss for epoch 3
4.743996024131775
The running loss is:
15.55551365017891
The number of items in train is:
8
The loss for epoch 4
1.9444392062723637
The running loss is:
8.367789804935455
The number of items in train is:
8
The loss for epoch 5
1.045973725616932
The running loss is:
11.206081509590149
The number of items in train is:
8
The loss for epoch 6
1.4007601886987686
The running loss is:
9.642450213432312
The number of items in train is:
8
The loss for epoch 7
1.205306276679039
The running loss is:
9.567102372646332
The number of items in train is:
8
The loss for epoch 8
1.1958877965807915
The running loss is:
6.858975321054459
The number of items in train is:
8
The loss for epoch 9
0.8573719151318073
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.748694
48 30755 ... 8.776375
49 30756 ... 8.766631
50 30757 ... 8.860359
51 30758 ... 9.283177
52 30759 ... 9.806849
53 30760 ... 10.339288
54 30761 ... 8.879484
55 30762 ... 8.919710
56 30763 ... 8.532740
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: uwmkpwjd wandb: Agent Starting Run: nqs19zfh with config: batch_size: 5 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: nqs19zfh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
30.585171580314636
The number of items in train is:
8
The loss for epoch 0
3.8231464475393295
The running loss is:
7.479733049869537
The number of items in train is:
8
The loss for epoch 1
0.9349666312336922
The running loss is:
14.812964379787445
The number of items in train is:
8
The loss for epoch 2
1.8516205474734306
The running loss is:
23.101281613111496
The number of items in train is:
8
The loss for epoch 3
2.887660201638937
The running loss is:
8.297429740428925
The number of items in train is:
8
The loss for epoch 4
1.0371787175536156
The running loss is:
11.319238305091858
The number of items in train is:
8
The loss for epoch 5
1.4149047881364822
The running loss is:
15.387986540794373
The number of items in train is:
8
The loss for epoch 6
1.9234983175992966
The running loss is:
7.361476421356201
The number of items in train is:
8
The loss for epoch 7
0.9201845526695251
The running loss is:
7.971918612718582
The number of items in train is:
8
The loss for epoch 8
0.9964898265898228
The running loss is:
7.466582655906677
The number of items in train is:
8
The loss for epoch 9
0.9333228319883347
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.595874
48 30755 ... 7.394851
49 30756 ... 9.121369
50 30757 ... 8.088429
51 30758 ... 7.770226
52 30759 ... 7.506985
53 30760 ... 7.117284
54 30761 ... 6.944593
55 30762 ... 6.501761
56 30763 ... 8.242576
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nqs19zfh wandb: Agent Starting Run: bvh1t9d2 with config: batch_size: 5 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bvh1t9d2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.538057163357735
The number of items in train is:
8
The loss for epoch 0
1.1922571454197168
The running loss is:
5.761137902736664
The number of items in train is:
8
The loss for epoch 1
0.720142237842083
The running loss is:
5.462558537721634
The number of items in train is:
8
The loss for epoch 2
0.6828198172152042
The running loss is:
4.668862268328667
The number of items in train is:
8
The loss for epoch 3
0.5836077835410833
The running loss is:
4.292478419840336
The number of items in train is:
8
The loss for epoch 4
0.536559802480042
The running loss is:
4.50324796885252
The number of items in train is:
8
The loss for epoch 5
0.562905996106565
The running loss is:
4.087679527699947
The number of items in train is:
8
The loss for epoch 6
0.5109599409624934
The running loss is:
4.086334981024265
The number of items in train is:
8
The loss for epoch 7
0.5107918726280332
The running loss is:
3.8916722163558006
The number of items in train is:
8
The loss for epoch 8
0.4864590270444751
The running loss is:
3.467552863061428
The number of items in train is:
8
The loss for epoch 9
0.4334441078826785
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.701126
48 30755 ... 10.617829
49 30756 ... 12.164164
50 30757 ... 13.254706
51 30758 ... 13.646997
52 30759 ... 14.125133
53 30760 ... 14.707135
54 30761 ... 15.274608
55 30762 ... 16.445068
56 30763 ... 17.851898
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bvh1t9d2 wandb: Agent Starting Run: 9s62j1js with config: batch_size: 5 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 9s62j1js
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.855386734008789
The number of items in train is:
8
The loss for epoch 0
1.2319233417510986
The running loss is:
6.053606033325195
The number of items in train is:
8
The loss for epoch 1
0.7567007541656494
The running loss is:
5.227531760931015
The number of items in train is:
8
The loss for epoch 2
0.6534414701163769
The running loss is:
4.913850545883179
The number of items in train is:
8
The loss for epoch 3
0.6142313182353973
The running loss is:
4.2742534428834915
The number of items in train is:
8
The loss for epoch 4
0.5342816803604364
The running loss is:
4.127818286418915
The number of items in train is:
8
The loss for epoch 5
0.5159772858023643
The running loss is:
3.93484203517437
The number of items in train is:
8
The loss for epoch 6
0.4918552543967962
The running loss is:
3.8864687383174896
The number of items in train is:
8
The loss for epoch 7
0.4858085922896862
The running loss is:
3.5512097850441933
The number of items in train is:
8
The loss for epoch 8
0.44390122313052416
The running loss is:
3.7246112003922462
The number of items in train is:
8
The loss for epoch 9
0.4655764000490308
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.418179
48 30755 ... 11.002016
49 30756 ... 12.337150
50 30757 ... 14.577664
51 30758 ... 16.363276
52 30759 ... 18.793327
53 30760 ... 21.699623
54 30761 ... 22.705818
55 30762 ... 23.938343
56 30763 ... 26.309530
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9s62j1js wandb: Agent Starting Run: cgoy7ndt with config: batch_size: 5 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: cgoy7ndt
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.800299257040024
The number of items in train is:
8
The loss for epoch 0
1.350037407130003
The running loss is:
6.719909101724625
The number of items in train is:
8
The loss for epoch 1
0.8399886377155781
The running loss is:
6.147316336631775
The number of items in train is:
8
The loss for epoch 2
0.7684145420789719
The running loss is:
5.55186402797699
The number of items in train is:
8
The loss for epoch 3
0.6939830034971237
The running loss is:
5.256973952054977
The number of items in train is:
8
The loss for epoch 4
0.6571217440068722
The running loss is:
4.77255941927433
The number of items in train is:
8
The loss for epoch 5
0.5965699274092913
The running loss is:
4.5062213987112045
The number of items in train is:
8
The loss for epoch 6
0.5632776748389006
The running loss is:
4.393381476402283
The number of items in train is:
8
The loss for epoch 7
0.5491726845502853
The running loss is:
4.38474141061306
The number of items in train is:
8
The loss for epoch 8
0.5480926763266325
The running loss is:
4.287996828556061
The number of items in train is:
8
The loss for epoch 9
0.5359996035695076
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.864444
48 30755 ... 11.327341
49 30756 ... 12.577684
50 30757 ... 14.237209
51 30758 ... 15.412471
52 30759 ... 17.135647
53 30760 ... 19.146513
54 30761 ... 20.154495
55 30762 ... 21.093636
56 30763 ... 22.628614
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cgoy7ndt wandb: Agent Starting Run: rtci6z3m with config: batch_size: 5 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: rtci6z3m
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.546842649579048
The number of items in train is:
8
The loss for epoch 0
1.193355331197381
The running loss is:
8.43789367377758
The number of items in train is:
8
The loss for epoch 1
1.0547367092221975
The running loss is:
4.924015037715435
The number of items in train is:
8
The loss for epoch 2
0.6155018797144294
The running loss is:
4.314315214753151
The number of items in train is:
8
The loss for epoch 3
0.5392894018441439
The running loss is:
4.0485982075333595
The number of items in train is:
8
The loss for epoch 4
0.5060747759416699
The running loss is:
4.1723093539476395
The number of items in train is:
8
The loss for epoch 5
0.5215386692434549
The running loss is:
3.7383037842810154
The number of items in train is:
8
The loss for epoch 6
0.4672879730351269
The running loss is:
3.931921534240246
The number of items in train is:
8
The loss for epoch 7
0.4914901917800307
The running loss is:
3.2728704884648323
The number of items in train is:
8
The loss for epoch 8
0.40910881105810404
The running loss is:
2.915392220020294
The number of items in train is:
8
The loss for epoch 9
0.3644240275025368
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.045798
48 30755 ... 10.157353
49 30756 ... 12.095802
50 30757 ... 12.449658
51 30758 ... 13.165064
52 30759 ... 13.813021
53 30760 ... 14.683218
54 30761 ... 14.160168
55 30762 ... 16.617773
56 30763 ... 18.648075
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rtci6z3m wandb: Agent Starting Run: w4b6zyi6 with config: batch_size: 5 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: w4b6zyi6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.17788852751255
The number of items in train is:
8
The loss for epoch 0
1.3972360659390688
The running loss is:
7.812009304761887
The number of items in train is:
8
The loss for epoch 1
0.9765011630952358
The running loss is:
5.429758012294769
The number of items in train is:
8
The loss for epoch 2
0.6787197515368462
The running loss is:
4.718441881239414
The number of items in train is:
8
The loss for epoch 3
0.5898052351549268
The running loss is:
4.047854967415333
The number of items in train is:
8
The loss for epoch 4
0.5059818709269166
The running loss is:
4.080165818333626
The number of items in train is:
8
The loss for epoch 5
0.5100207272917032
The running loss is:
3.7863672226667404
The number of items in train is:
8
The loss for epoch 6
0.47329590283334255
The running loss is:
3.964346893131733
The number of items in train is:
8
The loss for epoch 7
0.4955433616414666
The running loss is:
3.737635724246502
The number of items in train is:
8
The loss for epoch 8
0.46720446553081274
The running loss is:
3.944605380296707
The number of items in train is:
8
The loss for epoch 9
0.4930756725370884
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.542191
48 30755 ... 11.410826
49 30756 ... 11.835811
50 30757 ... 13.282190
51 30758 ... 14.953685
52 30759 ... 17.249598
53 30760 ... 20.018517
54 30761 ... 21.872402
55 30762 ... 22.083441
56 30763 ... 23.206171
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: w4b6zyi6 wandb: Agent Starting Run: 72mdqylc with config: batch_size: 5 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 72mdqylc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.393648847937584
The number of items in train is:
8
The loss for epoch 0
1.424206105992198
The running loss is:
9.387817233800888
The number of items in train is:
8
The loss for epoch 1
1.173477154225111
The running loss is:
5.967179387807846
The number of items in train is:
8
The loss for epoch 2
0.7458974234759808
The running loss is:
5.219222843647003
The number of items in train is:
8
The loss for epoch 3
0.6524028554558754
The running loss is:
5.00519023835659
The number of items in train is:
8
The loss for epoch 4
0.6256487797945738
The running loss is:
4.8075766414403915
The number of items in train is:
8
The loss for epoch 5
0.6009470801800489
The running loss is:
4.8459101021289825
The number of items in train is:
8
The loss for epoch 6
0.6057387627661228
The running loss is:
4.758179634809494
The number of items in train is:
8
The loss for epoch 7
0.5947724543511868
The running loss is:
4.346340090036392
The number of items in train is:
8
The loss for epoch 8
0.543292511254549
The running loss is:
4.356025725603104
The number of items in train is:
8
The loss for epoch 9
0.544503215700388
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.593064
48 30755 ... 11.480613
49 30756 ... 12.681897
50 30757 ... 13.842297
51 30758 ... 15.154292
52 30759 ... 17.142323
53 30760 ... 19.458761
54 30761 ... 19.006266
55 30762 ... 20.721127
56 30763 ... 22.308397
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 72mdqylc wandb: Agent Starting Run: 2zunql63 with config: batch_size: 5 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 2zunql63
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
7.381741419434547
The number of items in train is:
8
The loss for epoch 0
0.9227176774293184
The running loss is:
25.146740198135376
The number of items in train is:
8
The loss for epoch 1
3.143342524766922
The running loss is:
6.870392799377441
The number of items in train is:
8
The loss for epoch 2
0.8587990999221802
The running loss is:
8.847517043352127
The number of items in train is:
8
The loss for epoch 3
1.1059396304190159
The running loss is:
6.185571424663067
The number of items in train is:
8
The loss for epoch 4
0.7731964280828834
The running loss is:
5.277693450450897
The number of items in train is:
8
The loss for epoch 5
0.6597116813063622
The running loss is:
4.669010818004608
The number of items in train is:
8
The loss for epoch 6
0.583626352250576
The running loss is:
4.379348270595074
The number of items in train is:
8
The loss for epoch 7
0.5474185338243842
The running loss is:
4.096095941960812
The number of items in train is:
8
The loss for epoch 8
0.5120119927451015
The running loss is:
3.4440850913524628
The number of items in train is:
8
The loss for epoch 9
0.43051063641905785
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.933676
48 30755 ... 12.289965
49 30756 ... 13.424484
50 30757 ... 16.420580
51 30758 ... 15.872095
52 30759 ... 16.816118
53 30760 ... 16.920258
54 30761 ... 17.218924
55 30762 ... 19.419926
56 30763 ... 20.266211
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2zunql63 wandb: Agent Starting Run: ktoorkl6 with config: batch_size: 5 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ktoorkl6
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.426167532801628
The number of items in train is:
8
The loss for epoch 0
1.0532709416002035
The running loss is:
19.593581795692444
The number of items in train is:
8
The loss for epoch 1
2.4491977244615555
The running loss is:
7.231603503227234
The number of items in train is:
8
The loss for epoch 2
0.9039504379034042
The running loss is:
7.827229708433151
The number of items in train is:
8
The loss for epoch 3
0.9784037135541439
The running loss is:
6.041022434830666
The number of items in train is:
8
The loss for epoch 4
0.7551278043538332
The running loss is:
5.206323370337486
The number of items in train is:
8
The loss for epoch 5
0.6507904212921858
The running loss is:
4.792576283216476
The number of items in train is:
8
The loss for epoch 6
0.5990720354020596
The running loss is:
4.740285784006119
The number of items in train is:
8
The loss for epoch 7
0.5925357230007648
The running loss is:
4.0978415086865425
The number of items in train is:
8
The loss for epoch 8
0.5122301885858178
The running loss is:
4.568242058157921
The number of items in train is:
8
The loss for epoch 9
0.5710302572697401
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 19.106853
48 30755 ... 13.079176
49 30756 ... 16.165695
50 30757 ... 16.851734
51 30758 ... 19.214518
52 30759 ... 20.072746
53 30760 ... 22.310108
54 30761 ... 26.341103
55 30762 ... 25.220377
56 30763 ... 26.363348
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ktoorkl6 wandb: Agent Starting Run: ve8frys1 with config: batch_size: 5 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ve8frys1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.473036348819733
The number of items in train is:
8
The loss for epoch 0
1.0591295436024666
The running loss is:
29.853841066360474
The number of items in train is:
8
The loss for epoch 1
3.731730133295059
The running loss is:
7.707319617271423
The number of items in train is:
8
The loss for epoch 2
0.9634149521589279
The running loss is:
9.419616043567657
The number of items in train is:
8
The loss for epoch 3
1.1774520054459572
The running loss is:
6.854966193437576
The number of items in train is:
8
The loss for epoch 4
0.856870774179697
The running loss is:
6.6577427089214325
The number of items in train is:
8
The loss for epoch 5
0.8322178386151791
The running loss is:
5.656194299459457
The number of items in train is:
8
The loss for epoch 6
0.7070242874324322
The running loss is:
4.75788351893425
The number of items in train is:
8
The loss for epoch 7
0.5947354398667812
The running loss is:
4.642626956105232
The number of items in train is:
8
The loss for epoch 8
0.580328369513154
The running loss is:
4.646610513329506
The number of items in train is:
8
The loss for epoch 9
0.5808263141661882
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.130877
48 30755 ... 9.629366
49 30756 ... 11.600607
50 30757 ... 13.214843
51 30758 ... 13.308360
52 30759 ... 13.217094
53 30760 ... 13.293304
54 30761 ... 13.836164
55 30762 ... 15.439205
56 30763 ... 15.485834
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ve8frys1 wandb: Agent Starting Run: y3b1pfx7 with config: batch_size: 5 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: y3b1pfx7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
31.35861313343048
The number of items in train is:
8
The loss for epoch 0
3.91982664167881
The running loss is:
7.149083212018013
The number of items in train is:
8
The loss for epoch 1
0.8936354015022516
The running loss is:
20.340464413166046
The number of items in train is:
8
The loss for epoch 2
2.5425580516457558
The running loss is:
9.993232488632202
The number of items in train is:
8
The loss for epoch 3
1.2491540610790253
The running loss is:
6.315747439861298
The number of items in train is:
8
The loss for epoch 4
0.7894684299826622
The running loss is:
6.914129972457886
The number of items in train is:
8
The loss for epoch 5
0.8642662465572357
The running loss is:
8.855332881212234
The number of items in train is:
8
The loss for epoch 6
1.1069166101515293
The running loss is:
7.344175457954407
The number of items in train is:
8
The loss for epoch 7
0.9180219322443008
The running loss is:
6.533271104097366
The number of items in train is:
8
The loss for epoch 8
0.8166588880121708
The running loss is:
6.510418713092804
The number of items in train is:
8
The loss for epoch 9
0.8138023391366005
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.678343
48 30755 ... 10.423984
49 30756 ... 10.337050
50 30757 ... 9.651506
51 30758 ... 9.475930
52 30759 ... 9.294815
53 30760 ... 9.063562
54 30761 ... 9.299700
55 30762 ... 9.436070
56 30763 ... 9.489004
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y3b1pfx7 wandb: Agent Starting Run: 2a35yhra with config: batch_size: 5 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2a35yhra
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
24.757554709911346
The number of items in train is:
8
The loss for epoch 0
3.0946943387389183
The running loss is:
8.207798480987549
The number of items in train is:
8
The loss for epoch 1
1.0259748101234436
The running loss is:
17.192712485790253
The number of items in train is:
8
The loss for epoch 2
2.1490890607237816
The running loss is:
8.110509365797043
The number of items in train is:
8
The loss for epoch 3
1.0138136707246304
The running loss is:
8.176392793655396
The number of items in train is:
8
The loss for epoch 4
1.0220490992069244
The running loss is:
6.2795825600624084
The number of items in train is:
8
The loss for epoch 5
0.7849478200078011
The running loss is:
5.406195282936096
The number of items in train is:
8
The loss for epoch 6
0.675774410367012
The running loss is:
6.565752103924751
The number of items in train is:
8
The loss for epoch 7
0.8207190129905939
The running loss is:
4.730227127671242
The number of items in train is:
8
The loss for epoch 8
0.5912783909589052
The running loss is:
5.622362457215786
The number of items in train is:
8
The loss for epoch 9
0.7027953071519732
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.653543
48 30755 ... 11.666175
49 30756 ... 12.358805
50 30757 ... 12.517196
51 30758 ... 10.681630
52 30759 ... 11.495918
53 30760 ... 12.448450
54 30761 ... 13.540613
55 30762 ... 13.895693
56 30763 ... 14.009988
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2a35yhra wandb: Agent Starting Run: wi4kd4m5 with config: batch_size: 5 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: wi4kd4m5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.664043128490448
The number of items in train is:
8
The loss for epoch 0
3.583005391061306
The running loss is:
9.607732936739922
The number of items in train is:
8
The loss for epoch 1
1.2009666170924902
The running loss is:
20.923362255096436
The number of items in train is:
8
The loss for epoch 2
2.6154202818870544
The running loss is:
10.49313597381115
The number of items in train is:
8
The loss for epoch 3
1.3116419967263937
The running loss is:
8.878450512886047
The number of items in train is:
8
The loss for epoch 4
1.109806314110756
The running loss is:
7.381859600543976
The number of items in train is:
8
The loss for epoch 5
0.922732450067997
The running loss is:
7.193650335073471
The number of items in train is:
8
The loss for epoch 6
0.8992062918841839
The running loss is:
7.023971408605576
The number of items in train is:
8
The loss for epoch 7
0.877996426075697
The running loss is:
7.099064201116562
The number of items in train is:
8
The loss for epoch 8
0.8873830251395702
The running loss is:
7.1568794548511505
The number of items in train is:
8
The loss for epoch 9
0.8946099318563938
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.627852
48 30755 ... 9.286406
49 30756 ... 9.280918
50 30757 ... 9.513455
51 30758 ... 9.275638
52 30759 ... 9.122575
53 30760 ... 8.958853
54 30761 ... 9.268032
55 30762 ... 9.285326
56 30763 ... 9.277149
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wi4kd4m5 wandb: Agent Starting Run: pkhq8vpm with config: batch_size: 5 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: pkhq8vpm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.593297243118286
The number of items in train is:
8
The loss for epoch 0
1.1991621553897858
The running loss is:
5.726599365472794
The number of items in train is:
8
The loss for epoch 1
0.7158249206840992
The running loss is:
5.369395866990089
The number of items in train is:
8
The loss for epoch 2
0.6711744833737612
The running loss is:
4.905842535197735
The number of items in train is:
8
The loss for epoch 3
0.6132303168997169
The running loss is:
4.665864020586014
The number of items in train is:
8
The loss for epoch 4
0.5832330025732517
The running loss is:
4.398593630641699
The number of items in train is:
8
The loss for epoch 5
0.5498242038302124
The running loss is:
4.1014852412045
The number of items in train is:
8
The loss for epoch 6
0.5126856551505625
The running loss is:
4.372003979980946
The number of items in train is:
8
The loss for epoch 7
0.5465004974976182
The running loss is:
4.193980306386948
The number of items in train is:
8
The loss for epoch 8
0.5242475382983685
The running loss is:
4.117913290858269
The number of items in train is:
8
The loss for epoch 9
0.5147391613572836
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.286014
48 30755 ... 9.692314
49 30756 ... 10.136795
50 30757 ... 11.271959
51 30758 ... 14.237857
52 30759 ... 14.391908
53 30760 ... 14.427896
54 30761 ... 14.958170
55 30762 ... 14.813080
56 30763 ... 16.110613
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pkhq8vpm wandb: Agent Starting Run: sxces3b8 with config: batch_size: 5 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sxces3b8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.55923479795456
The number of items in train is:
8
The loss for epoch 0
1.31990434974432
The running loss is:
6.29985573887825
The number of items in train is:
8
The loss for epoch 1
0.7874819673597813
The running loss is:
5.972567766904831
The number of items in train is:
8
The loss for epoch 2
0.7465709708631039
The running loss is:
5.386669382452965
The number of items in train is:
8
The loss for epoch 3
0.6733336728066206
The running loss is:
5.082741692662239
The number of items in train is:
8
The loss for epoch 4
0.6353427115827799
The running loss is:
4.794009312987328
The number of items in train is:
8
The loss for epoch 5
0.599251164123416
The running loss is:
4.415606319904327
The number of items in train is:
8
The loss for epoch 6
0.5519507899880409
The running loss is:
4.496867328882217
The number of items in train is:
8
The loss for epoch 7
0.5621084161102772
The running loss is:
4.166094034910202
The number of items in train is:
8
The loss for epoch 8
0.5207617543637753
The running loss is:
4.42698822170496
The number of items in train is:
8
The loss for epoch 9
0.55337352771312
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.020846
48 30755 ... 11.632212
49 30756 ... 10.593838
50 30757 ... 11.659601
51 30758 ... 13.485876
52 30759 ... 14.449990
53 30760 ... 15.599710
54 30761 ... 15.936440
55 30762 ... 16.600374
56 30763 ... 17.529819
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sxces3b8 wandb: Agent Starting Run: u6jqkn40 with config: batch_size: 5 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u6jqkn40
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.690836369991302
The number of items in train is:
8
The loss for epoch 0
1.3363545462489128
The running loss is:
6.87058699131012
The number of items in train is:
8
The loss for epoch 1
0.858823373913765
The running loss is:
6.5186139941215515
The number of items in train is:
8
The loss for epoch 2
0.8148267492651939
The running loss is:
5.737721726298332
The number of items in train is:
8
The loss for epoch 3
0.7172152157872915
The running loss is:
5.308574818074703
The number of items in train is:
8
The loss for epoch 4
0.6635718522593379
The running loss is:
4.752960331737995
The number of items in train is:
8
The loss for epoch 5
0.5941200414672494
The running loss is:
5.247718453407288
The number of items in train is:
8
The loss for epoch 6
0.655964806675911
The running loss is:
5.271296665072441
The number of items in train is:
8
The loss for epoch 7
0.6589120831340551
The running loss is:
5.179829057306051
The number of items in train is:
8
The loss for epoch 8
0.6474786321632564
The running loss is:
4.976058304309845
The number of items in train is:
8
The loss for epoch 9
0.6220072880387306
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.681442
48 30755 ... 14.238687
49 30756 ... 6.291836
50 30757 ... 6.188722
51 30758 ... 4.669639
52 30759 ... 3.085255
53 30760 ... 1.716406
54 30761 ... 1.458660
55 30762 ... 1.863988
56 30763 ... 0.911042
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u6jqkn40 wandb: Agent Starting Run: 6zornv2x with config: batch_size: 5 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 6zornv2x
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.969246834516525
The number of items in train is:
8
The loss for epoch 0
1.3711558543145657
The running loss is:
7.660423636436462
The number of items in train is:
8
The loss for epoch 1
0.9575529545545578
The running loss is:
5.484717682003975
The number of items in train is:
8
The loss for epoch 2
0.6855897102504969
The running loss is:
4.548533156514168
The number of items in train is:
8
The loss for epoch 3
0.568566644564271
The running loss is:
4.64577092975378
The number of items in train is:
8
The loss for epoch 4
0.5807213662192225
The running loss is:
4.139353573322296
The number of items in train is:
8
The loss for epoch 5
0.517419196665287
The running loss is:
4.1177546083927155
The number of items in train is:
8
The loss for epoch 6
0.5147193260490894
The running loss is:
4.4892129227519035
The number of items in train is:
8
The loss for epoch 7
0.5611516153439879
The running loss is:
3.7275320515036583
The number of items in train is:
8
The loss for epoch 8
0.4659415064379573
The running loss is:
4.080616444349289
The number of items in train is:
8
The loss for epoch 9
0.5100770555436611
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.373961
48 30755 ... 9.177148
49 30756 ... 10.464656
50 30757 ... 11.428827
51 30758 ... 13.522120
52 30759 ... 14.078564
53 30760 ... 14.482571
54 30761 ... 14.862568
55 30762 ... 14.067533
56 30763 ... 16.003128
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6zornv2x wandb: Agent Starting Run: g32bev53 with config: batch_size: 5 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: g32bev53
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.977671682834625
The number of items in train is:
8
The loss for epoch 0
1.4972089603543282
The running loss is:
9.989576682448387
The number of items in train is:
8
The loss for epoch 1
1.2486970853060484
The running loss is:
6.243221879005432
The number of items in train is:
8
The loss for epoch 2
0.780402734875679
The running loss is:
5.672764778137207
The number of items in train is:
8
The loss for epoch 3
0.7090955972671509
The running loss is:
5.184059038758278
The number of items in train is:
8
The loss for epoch 4
0.6480073798447847
The running loss is:
4.671211451292038
The number of items in train is:
8
The loss for epoch 5
0.5839014314115047
The running loss is:
4.3249501734972
The number of items in train is:
8
The loss for epoch 6
0.54061877168715
The running loss is:
4.325228467583656
The number of items in train is:
8
The loss for epoch 7
0.540653558447957
The running loss is:
3.901700511574745
The number of items in train is:
8
The loss for epoch 8
0.48771256394684315
The running loss is:
4.088552720844746
The number of items in train is:
8
The loss for epoch 9
0.5110690901055932
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.630117
48 30755 ... 11.711292
49 30756 ... 11.650674
50 30757 ... 12.819802
51 30758 ... 13.787545
52 30759 ... 15.544405
53 30760 ... 17.753273
54 30761 ... 17.949461
55 30762 ... 17.935369
56 30763 ... 19.329866
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: g32bev53 wandb: Agent Starting Run: 392dutrx with config: batch_size: 5 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 392dutrx
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.297696448862553
The number of items in train is:
8
The loss for epoch 0
1.537212056107819
The running loss is:
8.727506756782532
The number of items in train is:
8
The loss for epoch 1
1.0909383445978165
The running loss is:
6.73730343580246
The number of items in train is:
8
The loss for epoch 2
0.8421629294753075
The running loss is:
5.71261340379715
The number of items in train is:
8
The loss for epoch 3
0.7140766754746437
The running loss is:
5.148693040013313
The number of items in train is:
8
The loss for epoch 4
0.6435866300016642
The running loss is:
4.604528576135635
The number of items in train is:
8
The loss for epoch 5
0.5755660720169544
The running loss is:
4.971816077828407
The number of items in train is:
8
The loss for epoch 6
0.6214770097285509
The running loss is:
5.4065783098340034
The number of items in train is:
8
The loss for epoch 7
0.6758222887292504
The running loss is:
6.092674419283867
The number of items in train is:
8
The loss for epoch 8
0.7615843024104834
The running loss is:
5.4708035588264465
The number of items in train is:
8
The loss for epoch 9
0.6838504448533058
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.954944
48 30755 ... 14.330663
49 30756 ... 7.776496
50 30757 ... 7.571167
51 30758 ... 6.841137
52 30759 ... 6.501884
53 30760 ... 6.554061
54 30761 ... 5.964196
55 30762 ... 6.573196
56 30763 ... 5.763231
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 392dutrx wandb: Agent Starting Run: 6bg9psl8 with config: batch_size: 5 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 6bg9psl8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.58815935254097
The number of items in train is:
8
The loss for epoch 0
1.1985199190676212
The running loss is:
19.209636002779007
The number of items in train is:
8
The loss for epoch 1
2.401204500347376
The running loss is:
7.738292142748833
The number of items in train is:
8
The loss for epoch 2
0.9672865178436041
The running loss is:
7.697542876005173
The number of items in train is:
8
The loss for epoch 3
0.9621928595006466
The running loss is:
6.6694705337285995
The number of items in train is:
8
The loss for epoch 4
0.8336838167160749
The running loss is:
4.881348237395287
The number of items in train is:
8
The loss for epoch 5
0.6101685296744108
The running loss is:
5.010814595967531
The number of items in train is:
8
The loss for epoch 6
0.6263518244959414
The running loss is:
5.574698239564896
The number of items in train is:
8
The loss for epoch 7
0.696837279945612
The running loss is:
4.987785197794437
The number of items in train is:
8
The loss for epoch 8
0.6234731497243047
The running loss is:
4.6631989777088165
The number of items in train is:
8
The loss for epoch 9
0.5828998722136021
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.443740
48 30755 ... 12.292900
49 30756 ... 12.623646
50 30757 ... 12.933738
51 30758 ... 14.440177
52 30759 ... 14.580387
53 30760 ... 13.962379
54 30761 ... 13.850780
55 30762 ... 11.960580
56 30763 ... 13.511158
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6bg9psl8 wandb: Agent Starting Run: v3ddsk1y with config: batch_size: 5 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: v3ddsk1y
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.516865834593773
The number of items in train is:
8
The loss for epoch 0
1.1896082293242216
The running loss is:
23.52896511554718
The number of items in train is:
8
The loss for epoch 1
2.9411206394433975
The running loss is:
7.973791569471359
The number of items in train is:
8
The loss for epoch 2
0.9967239461839199
The running loss is:
9.503426253795624
The number of items in train is:
8
The loss for epoch 3
1.187928281724453
The running loss is:
6.929812371730804
The number of items in train is:
8
The loss for epoch 4
0.8662265464663506
The running loss is:
6.647747039794922
The number of items in train is:
8
The loss for epoch 5
0.8309683799743652
The running loss is:
5.848790943622589
The number of items in train is:
8
The loss for epoch 6
0.7310988679528236
The running loss is:
5.039943665266037
The number of items in train is:
8
The loss for epoch 7
0.6299929581582546
The running loss is:
5.0003694742918015
The number of items in train is:
8
The loss for epoch 8
0.6250461842864752
The running loss is:
4.339855998754501
The number of items in train is:
8
The loss for epoch 9
0.5424819998443127
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.040102
48 30755 ... 10.688581
49 30756 ... 11.481241
50 30757 ... 12.348065
51 30758 ... 13.985934
52 30759 ... 14.072204
53 30760 ... 13.699750
54 30761 ... 15.169630
55 30762 ... 14.083228
56 30763 ... 15.484697
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v3ddsk1y wandb: Agent Starting Run: 2s9xavbj with config: batch_size: 5 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 2s9xavbj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.567524492740631
The number of items in train is:
8
The loss for epoch 0
1.1959405615925789
The running loss is:
21.582385897636414
The number of items in train is:
8
The loss for epoch 1
2.6977982372045517
The running loss is:
8.409520030021667
The number of items in train is:
8
The loss for epoch 2
1.0511900037527084
The running loss is:
8.695797711610794
The number of items in train is:
8
The loss for epoch 3
1.0869747139513493
The running loss is:
7.450117468833923
The number of items in train is:
8
The loss for epoch 4
0.9312646836042404
The running loss is:
7.004117637872696
The number of items in train is:
8
The loss for epoch 5
0.875514704734087
The running loss is:
6.92552524805069
The number of items in train is:
8
The loss for epoch 6
0.8656906560063362
The running loss is:
6.250691711902618
The number of items in train is:
8
The loss for epoch 7
0.7813364639878273
The running loss is:
6.194503873586655
The number of items in train is:
8
The loss for epoch 8
0.7743129841983318
The running loss is:
6.021981239318848
The number of items in train is:
8
The loss for epoch 9
0.752747654914856
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.852979
48 30755 ... 10.419504
49 30756 ... 7.349399
50 30757 ... 7.643004
51 30758 ... 8.218159
52 30759 ... 7.719066
53 30760 ... 7.764626
54 30761 ... 5.754187
55 30762 ... 3.776912
56 30763 ... 4.989199
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2s9xavbj wandb: Agent Starting Run: bsztwaei with config: batch_size: 5 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bsztwaei
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.21518623828888
The number of items in train is:
8
The loss for epoch 0
2.77689827978611
The running loss is:
7.293961197137833
The number of items in train is:
8
The loss for epoch 1
0.9117451496422291
The running loss is:
11.329310700297356
The number of items in train is:
8
The loss for epoch 2
1.4161638375371695
The running loss is:
8.372911632061005
The number of items in train is:
8
The loss for epoch 3
1.0466139540076256
The running loss is:
7.673612356185913
The number of items in train is:
8
The loss for epoch 4
0.9592015445232391
The running loss is:
6.563172549009323
The number of items in train is:
8
The loss for epoch 5
0.8203965686261654
The running loss is:
7.0265980660915375
The number of items in train is:
8
The loss for epoch 6
0.8783247582614422
The running loss is:
7.765732854604721
The number of items in train is:
8
The loss for epoch 7
0.9707166068255901
The running loss is:
5.755122497677803
The number of items in train is:
8
The loss for epoch 8
0.7193903122097254
The running loss is:
6.191661715507507
The number of items in train is:
8
The loss for epoch 9
0.7739577144384384
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.349856
48 30755 ... 14.594925
49 30756 ... 8.787890
50 30757 ... 10.063706
51 30758 ... 12.845061
52 30759 ... 11.149172
53 30760 ... 12.277591
54 30761 ... 10.631094
55 30762 ... 7.704789
56 30763 ... 11.401577
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bsztwaei wandb: Agent Starting Run: 0bra3ihp with config: batch_size: 5 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 0bra3ihp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
30.714923441410065
The number of items in train is:
8
The loss for epoch 0
3.839365430176258
The running loss is:
8.897786349058151
The number of items in train is:
8
The loss for epoch 1
1.112223293632269
The running loss is:
14.070866167545319
The number of items in train is:
8
The loss for epoch 2
1.7588582709431648
The running loss is:
6.147258788347244
The number of items in train is:
8
The loss for epoch 3
0.7684073485434055
The running loss is:
8.751449584960938
The number of items in train is:
8
The loss for epoch 4
1.0939311981201172
The running loss is:
6.525316268205643
The number of items in train is:
8
The loss for epoch 5
0.8156645335257053
The running loss is:
6.006653621792793
The number of items in train is:
8
The loss for epoch 6
0.7508317027240992
The running loss is:
5.657045960426331
The number of items in train is:
8
The loss for epoch 7
0.7071307450532913
The running loss is:
5.266755282878876
The number of items in train is:
8
The loss for epoch 8
0.6583444103598595
The running loss is:
4.700027108192444
The number of items in train is:
8
The loss for epoch 9
0.5875033885240555
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 13.381409
48 30755 ... 11.875984
49 30756 ... 7.917060
50 30757 ... 8.531528
51 30758 ... 9.563288
52 30759 ... 10.676108
53 30760 ... 9.577621
54 30761 ... 7.140139
55 30762 ... 5.638883
56 30763 ... 8.996849
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0bra3ihp wandb: Agent Starting Run: llavyg4a with config: batch_size: 5 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: llavyg4a
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
25.851928889751434
The number of items in train is:
8
The loss for epoch 0
3.2314911112189293
The running loss is:
9.666099555790424
The number of items in train is:
8
The loss for epoch 1
1.208262444473803
The running loss is:
17.461497962474823
The number of items in train is:
8
The loss for epoch 2
2.182687245309353
The running loss is:
11.974535584449768
The number of items in train is:
8
The loss for epoch 3
1.496816948056221
The running loss is:
7.328074067831039
The number of items in train is:
8
The loss for epoch 4
0.9160092584788799
The running loss is:
7.055084586143494
The number of items in train is:
8
The loss for epoch 5
0.8818855732679367
The running loss is:
7.310244619846344
The number of items in train is:
8
The loss for epoch 6
0.913780577480793
The running loss is:
8.090441286563873
The number of items in train is:
8
The loss for epoch 7
1.0113051608204842
The running loss is:
6.187301903963089
The number of items in train is:
8
The loss for epoch 8
0.7734127379953861
The running loss is:
7.4150442481040955
The number of items in train is:
8
The loss for epoch 9
0.9268805310130119
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.429152
48 30755 ... 9.470564
49 30756 ... 7.614705
50 30757 ... 7.615232
51 30758 ... 6.435814
52 30759 ... 6.161608
53 30760 ... 6.723379
54 30761 ... 6.004760
55 30762 ... 5.973912
56 30763 ... 6.007796
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: llavyg4a wandb: Agent Starting Run: cva4oexj with config: batch_size: 5 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cva4oexj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.988087236881256
The number of items in train is:
8
The loss for epoch 0
1.373510904610157
The running loss is:
6.130865275859833
The number of items in train is:
8
The loss for epoch 1
0.7663581594824791
The running loss is:
6.174404188990593
The number of items in train is:
8
The loss for epoch 2
0.7718005236238241
The running loss is:
5.187673270702362
The number of items in train is:
8
The loss for epoch 3
0.6484591588377953
The running loss is:
4.837460793554783
The number of items in train is:
8
The loss for epoch 4
0.6046825991943479
The running loss is:
4.544721320271492
The number of items in train is:
8
The loss for epoch 5
0.5680901650339365
The running loss is:
4.069583348929882
The number of items in train is:
8
The loss for epoch 6
0.5086979186162353
The running loss is:
3.594746358692646
The number of items in train is:
8
The loss for epoch 7
0.44934329483658075
The running loss is:
3.7067486941814423
The number of items in train is:
8
The loss for epoch 8
0.4633435867726803
The running loss is:
4.295153647661209
The number of items in train is:
8
The loss for epoch 9
0.5368942059576511
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 4.944542
48 30755 ... 9.224927
49 30756 ... 15.323524
50 30757 ... 8.676831
51 30758 ... 7.893984
52 30759 ... 5.685059
53 30760 ... 7.073691
54 30761 ... 5.709319
55 30762 ... 6.393231
56 30763 ... 8.572709
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cva4oexj wandb: Agent Starting Run: t7i777b8 with config: batch_size: 5 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: t7i777b8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.518769428133965
The number of items in train is:
8
The loss for epoch 0
1.3148461785167456
The running loss is:
5.923578202724457
The number of items in train is:
8
The loss for epoch 1
0.7404472753405571
The running loss is:
5.645459771156311
The number of items in train is:
8
The loss for epoch 2
0.7056824713945389
The running loss is:
4.980411872267723
The number of items in train is:
8
The loss for epoch 3
0.6225514840334654
The running loss is:
4.530896496027708
The number of items in train is:
8
The loss for epoch 4
0.5663620620034635
The running loss is:
4.397785879671574
The number of items in train is:
8
The loss for epoch 5
0.5497232349589467
The running loss is:
4.29297462105751
The number of items in train is:
8
The loss for epoch 6
0.5366218276321888
The running loss is:
4.506956547498703
The number of items in train is:
8
The loss for epoch 7
0.5633695684373379
The running loss is:
4.146910917013884
The number of items in train is:
8
The loss for epoch 8
0.5183638646267354
The running loss is:
4.1442591547966
The number of items in train is:
8
The loss for epoch 9
0.518032394349575
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.146306
48 30755 ... 10.201323
49 30756 ... 10.728070
50 30757 ... 5.294060
51 30758 ... 4.995479
52 30759 ... 3.408786
53 30760 ... 1.815881
54 30761 ... 1.260006
55 30762 ... 0.527362
56 30763 ... -0.697772
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: t7i777b8 wandb: Agent Starting Run: 5w26imkb with config: batch_size: 5 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 5w26imkb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.894125536084175
The number of items in train is:
7
The loss for epoch 0
1.2705893622977393
The running loss is:
5.564131408929825
The number of items in train is:
7
The loss for epoch 1
0.7948759155614036
The running loss is:
5.312940925359726
The number of items in train is:
7
The loss for epoch 2
0.7589915607656751
The running loss is:
5.099969863891602
The number of items in train is:
7
The loss for epoch 3
0.7285671234130859
The running loss is:
4.625931918621063
The number of items in train is:
7
The loss for epoch 4
0.6608474169458661
The running loss is:
4.33843432366848
The number of items in train is:
7
The loss for epoch 5
0.61977633195264
The running loss is:
4.1866855174303055
The number of items in train is:
7
The loss for epoch 6
0.5980979310614722
The running loss is:
3.9940166771411896
The number of items in train is:
7
The loss for epoch 7
0.5705738110201699
The running loss is:
3.970025137066841
The number of items in train is:
7
The loss for epoch 8
0.5671464481524059
The running loss is:
3.9160776883363724
The number of items in train is:
7
The loss for epoch 9
0.5594396697623389
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.635190
48 30755 ... 7.895287
49 30756 ... 8.697375
50 30757 ... 1.898233
51 30758 ... 0.671871
52 30759 ... -4.522796
53 30760 ... -9.575880
54 30761 ... -11.591200
55 30762 ... -12.904318
56 30763 ... -14.246117
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5w26imkb wandb: Agent Starting Run: ecutckzr with config: batch_size: 5 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ecutckzr
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.887800768017769
The number of items in train is:
8
The loss for epoch 0
1.485975096002221
The running loss is:
12.321395099163055
The number of items in train is:
8
The loss for epoch 1
1.540174387395382
The running loss is:
6.093603327870369
The number of items in train is:
8
The loss for epoch 2
0.7617004159837961
The running loss is:
5.896246939897537
The number of items in train is:
8
The loss for epoch 3
0.7370308674871922
The running loss is:
5.005269628018141
The number of items in train is:
8
The loss for epoch 4
0.6256587035022676
The running loss is:
4.166861433535814
The number of items in train is:
8
The loss for epoch 5
0.5208576791919768
The running loss is:
4.017287373542786
The number of items in train is:
8
The loss for epoch 6
0.5021609216928482
The running loss is:
3.493396818637848
The number of items in train is:
8
The loss for epoch 7
0.436674602329731
The running loss is:
3.3815640807151794
The number of items in train is:
8
The loss for epoch 8
0.42269551008939743
The running loss is:
3.7725103944540024
The number of items in train is:
8
The loss for epoch 9
0.4715637993067503
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 3.423247
48 30755 ... 7.961720
49 30756 ... 16.994312
50 30757 ... 8.721828
51 30758 ... 7.517489
52 30759 ... 5.470166
53 30760 ... 6.306812
54 30761 ... 4.383795
55 30762 ... 5.612186
56 30763 ... 9.138195
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ecutckzr wandb: Agent Starting Run: 1l8cw7d1 with config: batch_size: 5 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 1l8cw7d1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.111236214637756
The number of items in train is:
8
The loss for epoch 0
1.3889045268297195
The running loss is:
10.37959161400795
The number of items in train is:
8
The loss for epoch 1
1.2974489517509937
The running loss is:
5.6099735498428345
The number of items in train is:
8
The loss for epoch 2
0.7012466937303543
The running loss is:
5.337096557021141
The number of items in train is:
8
The loss for epoch 3
0.6671370696276426
The running loss is:
4.966018117964268
The number of items in train is:
8
The loss for epoch 4
0.6207522647455335
The running loss is:
4.362881056964397
The number of items in train is:
8
The loss for epoch 5
0.5453601321205497
The running loss is:
4.704715624451637
The number of items in train is:
8
The loss for epoch 6
0.5880894530564547
The running loss is:
4.736382022500038
The number of items in train is:
8
The loss for epoch 7
0.5920477528125048
The running loss is:
4.6529160887002945
The number of items in train is:
8
The loss for epoch 8
0.5816145110875368
The running loss is:
4.296320855617523
The number of items in train is:
8
The loss for epoch 9
0.5370401069521904
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.446108
48 30755 ... 11.343395
49 30756 ... 11.887388
50 30757 ... 7.717669
51 30758 ... 7.751965
52 30759 ... 7.669600
53 30760 ... 7.350806
54 30761 ... 7.241406
55 30762 ... 6.712784
56 30763 ... 5.831652
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1l8cw7d1 wandb: Agent Starting Run: nv44ow12 with config: batch_size: 5 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: nv44ow12
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.599854245781898
The number of items in train is:
7
The loss for epoch 0
1.3714077493974142
The running loss is:
7.652046352624893
The number of items in train is:
7
The loss for epoch 1
1.0931494789464133
The running loss is:
5.750150084495544
The number of items in train is:
7
The loss for epoch 2
0.821450012070792
The running loss is:
5.102803453803062
The number of items in train is:
7
The loss for epoch 3
0.7289719219718661
The running loss is:
4.570298731327057
The number of items in train is:
7
The loss for epoch 4
0.6528998187610081
The running loss is:
4.174758642911911
The number of items in train is:
7
The loss for epoch 5
0.5963940918445587
The running loss is:
4.100458398461342
The number of items in train is:
7
The loss for epoch 6
0.5857797712087631
The running loss is:
3.8777418956160545
The number of items in train is:
7
The loss for epoch 7
0.5539631279451507
The running loss is:
4.013542205095291
The number of items in train is:
7
The loss for epoch 8
0.5733631721564701
The running loss is:
3.7913883179426193
The number of items in train is:
7
The loss for epoch 9
0.5416269025632313
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.821921
48 30755 ... 7.197848
49 30756 ... 8.571998
50 30757 ... 2.402885
51 30758 ... 1.511044
52 30759 ... -4.203164
53 30760 ... -8.865639
54 30761 ... -11.548653
55 30762 ... -11.881847
56 30763 ... -11.955574
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nv44ow12 wandb: Agent Starting Run: obtghbzd with config: batch_size: 5 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: obtghbzd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.997101932764053
The number of items in train is:
8
The loss for epoch 0
1.2496377415955067
The running loss is:
25.993660151958466
The number of items in train is:
8
The loss for epoch 1
3.249207518994808
The running loss is:
8.482003197073936
The number of items in train is:
8
The loss for epoch 2
1.060250399634242
The running loss is:
9.39265489578247
The number of items in train is:
8
The loss for epoch 3
1.1740818619728088
The running loss is:
6.332621991634369
The number of items in train is:
8
The loss for epoch 4
0.7915777489542961
The running loss is:
6.0705039873719215
The number of items in train is:
8
The loss for epoch 5
0.7588129984214902
The running loss is:
4.406190410256386
The number of items in train is:
8
The loss for epoch 6
0.5507738012820482
The running loss is:
4.119934968650341
The number of items in train is:
8
The loss for epoch 7
0.5149918710812926
The running loss is:
3.609408460557461
The number of items in train is:
8
The loss for epoch 8
0.4511760575696826
The running loss is:
3.869946077466011
The number of items in train is:
8
The loss for epoch 9
0.4837432596832514
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 3.105083
48 30755 ... 7.483217
49 30756 ... 16.624786
50 30757 ... 13.093364
51 30758 ... 11.839172
52 30759 ... 8.308400
53 30760 ... 7.560250
54 30761 ... 4.328191
55 30762 ... 7.659884
56 30763 ... 15.055558
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: obtghbzd wandb: Agent Starting Run: zsuiwysp with config: batch_size: 5 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: zsuiwysp
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.068325817584991
The number of items in train is:
8
The loss for epoch 0
1.258540727198124
The running loss is:
24.007892698049545
The number of items in train is:
8
The loss for epoch 1
3.000986587256193
The running loss is:
9.265377074480057
The number of items in train is:
8
The loss for epoch 2
1.158172134310007
The running loss is:
8.75785793364048
The number of items in train is:
8
The loss for epoch 3
1.09473224170506
The running loss is:
6.427554905414581
The number of items in train is:
8
The loss for epoch 4
0.8034443631768227
The running loss is:
5.975850880146027
The number of items in train is:
8
The loss for epoch 5
0.7469813600182533
The running loss is:
5.8006473779678345
The number of items in train is:
8
The loss for epoch 6
0.7250809222459793
The running loss is:
5.041416525840759
The number of items in train is:
8
The loss for epoch 7
0.6301770657300949
The running loss is:
5.184276461601257
The number of items in train is:
8
The loss for epoch 8
0.6480345577001572
The running loss is:
4.828471004962921
The number of items in train is:
8
The loss for epoch 9
0.6035588756203651
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.685125
48 30755 ... 10.141446
49 30756 ... 10.176304
50 30757 ... 8.534622
51 30758 ... 8.422894
52 30759 ... 9.165926
53 30760 ... 8.473968
54 30761 ... 8.556828
55 30762 ... 8.253967
56 30763 ... 7.639414
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zsuiwysp wandb: Agent Starting Run: becfxy1h with config: batch_size: 5 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: becfxy1h
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.460621416568756
The number of items in train is:
7
The loss for epoch 0
1.2086602023669653
The running loss is:
18.102233052253723
The number of items in train is:
7
The loss for epoch 1
2.5860332931791032
The running loss is:
6.512787103652954
The number of items in train is:
7
The loss for epoch 2
0.9303981576647077
The running loss is:
6.982966423034668
The number of items in train is:
7
The loss for epoch 3
0.9975666318620954
The running loss is:
6.328465700149536
The number of items in train is:
7
The loss for epoch 4
0.9040665285927909
The running loss is:
5.637281686067581
The number of items in train is:
7
The loss for epoch 5
0.8053259551525116
The running loss is:
5.099390223622322
The number of items in train is:
7
The loss for epoch 6
0.7284843176603317
The running loss is:
5.197691917419434
The number of items in train is:
7
The loss for epoch 7
0.7425274167742048
The running loss is:
4.571497932076454
The number of items in train is:
7
The loss for epoch 8
0.6530711331537792
The running loss is:
4.5052072405815125
The number of items in train is:
7
The loss for epoch 9
0.6436010343687875
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.477296
48 30755 ... 12.216771
49 30756 ... 16.080605
50 30757 ... 7.985258
51 30758 ... 5.157682
52 30759 ... 5.292890
53 30760 ... 8.751102
54 30761 ... 6.112296
55 30762 ... 5.893753
56 30763 ... 2.171442
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: becfxy1h wandb: Agent Starting Run: ft6dluaf with config: batch_size: 5 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ft6dluaf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
51.745544634759426
The number of items in train is:
8
The loss for epoch 0
6.468193079344928
The running loss is:
7.415382172912359
The number of items in train is:
8
The loss for epoch 1
0.9269227716140449
The running loss is:
26.316525518894196
The number of items in train is:
8
The loss for epoch 2
3.2895656898617744
The running loss is:
10.214841291308403
The number of items in train is:
8
The loss for epoch 3
1.2768551614135504
The running loss is:
8.170285634696484
The number of items in train is:
8
The loss for epoch 4
1.0212857043370605
The running loss is:
7.0604946203529835
The number of items in train is:
8
The loss for epoch 5
0.8825618275441229
The running loss is:
7.179498016834259
The number of items in train is:
8
The loss for epoch 6
0.8974372521042824
The running loss is:
6.191406540572643
The number of items in train is:
8
The loss for epoch 7
0.7739258175715804
The running loss is:
5.223570495843887
The number of items in train is:
8
The loss for epoch 8
0.6529463119804859
The running loss is:
4.520765490829945
The number of items in train is:
8
The loss for epoch 9
0.5650956863537431
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 4.974351
48 30755 ... 8.985002
49 30756 ... 12.309855
50 30757 ... 13.367251
51 30758 ... 9.941705
52 30759 ... 8.789341
53 30760 ... 6.738607
54 30761 ... 6.319057
55 30762 ... 8.400917
56 30763 ... 14.151873
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ft6dluaf wandb: Agent Starting Run: 2arfilkc with config: batch_size: 5 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2arfilkc
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
41.46526186168194
The number of items in train is:
8
The loss for epoch 0
5.183157732710242
The running loss is:
9.50710366666317
The number of items in train is:
8
The loss for epoch 1
1.1883879583328962
The running loss is:
16.354243218898773
The number of items in train is:
8
The loss for epoch 2
2.0442804023623466
The running loss is:
13.173823714256287
The number of items in train is:
8
The loss for epoch 3
1.6467279642820358
The running loss is:
9.65525808930397
The number of items in train is:
8
The loss for epoch 4
1.2069072611629963
The running loss is:
8.45247933268547
The number of items in train is:
8
The loss for epoch 5
1.0565599165856838
The running loss is:
7.676742374897003
The number of items in train is:
8
The loss for epoch 6
0.9595927968621254
The running loss is:
7.17548294365406
The number of items in train is:
8
The loss for epoch 7
0.8969353679567575
The running loss is:
7.414336830377579
The number of items in train is:
8
The loss for epoch 8
0.9267921037971973
The running loss is:
7.242239236831665
The number of items in train is:
8
The loss for epoch 9
0.9052799046039581
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.665867
48 30755 ... 8.799163
49 30756 ... 8.671396
50 30757 ... 8.563816
51 30758 ... 8.574473
52 30759 ... 8.541787
53 30760 ... 8.166990
54 30761 ... 8.139524
55 30762 ... 8.140105
56 30763 ... 8.138222
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2arfilkc wandb: Agent Starting Run: 42em95oh with config: batch_size: 5 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 42em95oh
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.903275549411774
The number of items in train is:
7
The loss for epoch 0
4.129039364201682
The running loss is:
8.714233547449112
The number of items in train is:
7
The loss for epoch 1
1.2448905067784446
The running loss is:
10.163697183132172
The number of items in train is:
7
The loss for epoch 2
1.4519567404474532
The running loss is:
6.631345450878143
The number of items in train is:
7
The loss for epoch 3
0.9473350644111633
The running loss is:
8.022440493106842
The number of items in train is:
7
The loss for epoch 4
1.1460629275866918
The running loss is:
6.365507125854492
The number of items in train is:
7
The loss for epoch 5
0.909358160836356
The running loss is:
5.899640619754791
The number of items in train is:
7
The loss for epoch 6
0.842805802822113
The running loss is:
5.404639720916748
The number of items in train is:
7
The loss for epoch 7
0.7720913887023926
The running loss is:
4.700559139251709
The number of items in train is:
7
The loss for epoch 8
0.6715084484645298
The running loss is:
4.579154878854752
The number of items in train is:
7
The loss for epoch 9
0.654164982693536
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 14.387460
48 30755 ... 14.059313
49 30756 ... 16.322126
50 30757 ... 7.285743
51 30758 ... 7.333082
52 30759 ... 6.417980
53 30760 ... 8.817734
54 30761 ... 7.192719
55 30762 ... 7.644890
56 30763 ... 4.754567
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 42em95oh wandb: Agent Starting Run: v04iw04x with config: batch_size: 5 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: v04iw04x
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.009780496358871
The number of items in train is:
8
The loss for epoch 0
1.126222562044859
The running loss is:
8.815376043319702
The number of items in train is:
8
The loss for epoch 1
1.1019220054149628
The running loss is:
5.679255768656731
The number of items in train is:
8
The loss for epoch 2
0.7099069710820913
The running loss is:
5.220305755734444
The number of items in train is:
8
The loss for epoch 3
0.6525382194668055
The running loss is:
5.057030022144318
The number of items in train is:
8
The loss for epoch 4
0.6321287527680397
The running loss is:
5.1790468990802765
The number of items in train is:
8
The loss for epoch 5
0.6473808623850346
The running loss is:
4.504566803574562
The number of items in train is:
8
The loss for epoch 6
0.5630708504468203
The running loss is:
4.49835005402565
The number of items in train is:
8
The loss for epoch 7
0.5622937567532063
The running loss is:
4.113087989389896
The number of items in train is:
8
The loss for epoch 8
0.514135998673737
The running loss is:
4.175215393304825
The number of items in train is:
8
The loss for epoch 9
0.5219019241631031
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.973689
48 30755 ... 13.957306
49 30756 ... 14.184193
50 30757 ... 13.553813
51 30758 ... 9.452812
52 30759 ... 9.643188
53 30760 ... 9.692542
54 30761 ... 9.199206
55 30762 ... 8.749400
56 30763 ... 8.436934
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v04iw04x wandb: Agent Starting Run: z0gzzvz7 with config: batch_size: 5 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: z0gzzvz7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.857616066932678
The number of items in train is:
7
The loss for epoch 0
1.2653737238475256
The running loss is:
5.892047256231308
The number of items in train is:
7
The loss for epoch 1
0.8417210366044726
The running loss is:
5.294501721858978
The number of items in train is:
7
The loss for epoch 2
0.7563573888369969
The running loss is:
4.488193511962891
The number of items in train is:
7
The loss for epoch 3
0.6411705017089844
The running loss is:
4.085705995559692
The number of items in train is:
7
The loss for epoch 4
0.583672285079956
The running loss is:
3.9441015422344208
The number of items in train is:
7
The loss for epoch 5
0.5634430774620601
The running loss is:
3.6253725737333298
The number of items in train is:
7
The loss for epoch 6
0.5179103676761899
The running loss is:
3.4738786220550537
The number of items in train is:
7
The loss for epoch 7
0.4962683745792934
The running loss is:
3.252960652112961
The number of items in train is:
7
The loss for epoch 8
0.4647086645875658
The running loss is:
3.3102271109819412
The number of items in train is:
7
The loss for epoch 9
0.47288958728313446
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.235288
48 30755 ... 5.120963
49 30756 ... 6.150893
50 30757 ... 6.511737
51 30758 ... 0.237356
52 30759 ... -1.679703
53 30760 ... -7.668720
54 30761 ... -9.001451
55 30762 ... -10.168573
56 30763 ... -10.948854
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z0gzzvz7 wandb: Agent Starting Run: mg19jgh7 with config: batch_size: 5 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: mg19jgh7
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.379037261009216
The number of items in train is:
7
The loss for epoch 0
1.1970053230013167
The running loss is:
5.307533085346222
The number of items in train is:
7
The loss for epoch 1
0.7582190121923175
The running loss is:
4.932691335678101
The number of items in train is:
7
The loss for epoch 2
0.7046701908111572
The running loss is:
4.546344310045242
The number of items in train is:
7
The loss for epoch 3
0.6494777585778918
The running loss is:
4.347181588411331
The number of items in train is:
7
The loss for epoch 4
0.6210259412016187
The running loss is:
3.996902972459793
The number of items in train is:
7
The loss for epoch 5
0.5709861389228276
The running loss is:
3.996919736266136
The number of items in train is:
7
The loss for epoch 6
0.5709885337523052
The running loss is:
3.778156131505966
The number of items in train is:
7
The loss for epoch 7
0.539736590215138
The running loss is:
3.7420578598976135
The number of items in train is:
7
The loss for epoch 8
0.5345796942710876
The running loss is:
3.785576105117798
The number of items in train is:
7
The loss for epoch 9
0.5407965864453997
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.854308
48 30755 ... 5.433422
49 30756 ... 6.249044
50 30757 ... 6.006957
51 30758 ... 0.170424
52 30759 ... -1.708926
53 30760 ... -6.426423
54 30761 ... -8.075663
55 30762 ... -9.582035
56 30763 ... -10.701384
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mg19jgh7 wandb: Agent Starting Run: xujmq1wm with config: batch_size: 5 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: xujmq1wm
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.328620731830597
The number of items in train is:
8
The loss for epoch 0
1.2910775914788246
The running loss is:
17.95246112346649
The number of items in train is:
8
The loss for epoch 1
2.2440576404333115
The running loss is:
6.625293288379908
The number of items in train is:
8
The loss for epoch 2
0.8281616610474885
The running loss is:
6.007527709007263
The number of items in train is:
8
The loss for epoch 3
0.7509409636259079
The running loss is:
5.87974913418293
The number of items in train is:
8
The loss for epoch 4
0.7349686417728662
The running loss is:
5.40078030526638
The number of items in train is:
8
The loss for epoch 5
0.6750975381582975
The running loss is:
4.814377501606941
The number of items in train is:
8
The loss for epoch 6
0.6017971877008677
The running loss is:
4.766529709100723
The number of items in train is:
8
The loss for epoch 7
0.5958162136375904
The running loss is:
4.524849310517311
The number of items in train is:
8
The loss for epoch 8
0.5656061638146639
The running loss is:
4.09240049123764
The number of items in train is:
8
The loss for epoch 9
0.511550061404705
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.599988
48 30755 ... 14.127781
49 30756 ... 14.584249
50 30757 ... 14.020692
51 30758 ... 11.691189
52 30759 ... 11.752935
53 30760 ... 11.960830
54 30761 ... 11.773537
55 30762 ... 11.726958
56 30763 ... 11.685018
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xujmq1wm wandb: Agent Starting Run: 1mpruz7r with config: batch_size: 5 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 1mpruz7r
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.134911477565765
The number of items in train is:
7
The loss for epoch 0
1.3049873539379664
The running loss is:
11.372960567474365
The number of items in train is:
7
The loss for epoch 1
1.624708652496338
The running loss is:
4.703024297952652
The number of items in train is:
7
The loss for epoch 2
0.671860613993236
The running loss is:
4.89816290140152
The number of items in train is:
7
The loss for epoch 3
0.6997375573430743
The running loss is:
4.575336530804634
The number of items in train is:
7
The loss for epoch 4
0.653619504400662
The running loss is:
4.036156639456749
The number of items in train is:
7
The loss for epoch 5
0.5765938056366784
The running loss is:
3.7723549902439117
The number of items in train is:
7
The loss for epoch 6
0.5389078557491302
The running loss is:
3.553560823202133
The number of items in train is:
7
The loss for epoch 7
0.5076515461717334
The running loss is:
3.3667041957378387
The number of items in train is:
7
The loss for epoch 8
0.48095774224826265
The running loss is:
3.3663299083709717
The number of items in train is:
7
The loss for epoch 9
0.48090427262442453
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.382259
48 30755 ... 5.730763
49 30756 ... 6.944045
50 30757 ... 8.367525
51 30758 ... 3.260181
52 30759 ... 2.212879
53 30760 ... -2.212296
54 30761 ... -2.790353
55 30762 ... -3.146363
56 30763 ... -3.273260
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1mpruz7r wandb: Agent Starting Run: h98tjc97 with config: batch_size: 5 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: h98tjc97
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.568547546863556
The number of items in train is:
7
The loss for epoch 0
1.224078220980508
The running loss is:
7.439529746770859
The number of items in train is:
7
The loss for epoch 1
1.0627899638244085
The running loss is:
4.960866212844849
The number of items in train is:
7
The loss for epoch 2
0.7086951732635498
The running loss is:
4.659017026424408
The number of items in train is:
7
The loss for epoch 3
0.6655738609177726
The running loss is:
4.433339834213257
The number of items in train is:
7
The loss for epoch 4
0.6333342620304653
The running loss is:
3.8202225267887115
The number of items in train is:
7
The loss for epoch 5
0.5457460752555302
The running loss is:
3.9327641278505325
The number of items in train is:
7
The loss for epoch 6
0.5618234468357903
The running loss is:
3.604253336787224
The number of items in train is:
7
The loss for epoch 7
0.5148933338267463
The running loss is:
3.4691165685653687
The number of items in train is:
7
The loss for epoch 8
0.4955880812236241
The running loss is:
3.4035107642412186
The number of items in train is:
7
The loss for epoch 9
0.4862158234630312
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 5.711511
48 30755 ... 5.064266
49 30756 ... 5.884321
50 30757 ... 6.018492
51 30758 ... -0.261717
52 30759 ... -1.986962
53 30760 ... -7.378283
54 30761 ... -9.749792
55 30762 ... -11.496117
56 30763 ... -11.704885
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: h98tjc97 wandb: Agent Starting Run: os66dtsw with config: batch_size: 5 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: os66dtsw
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.596001714468002
The number of items in train is:
8
The loss for epoch 0
2.3245002143085003
The running loss is:
17.31740289926529
The number of items in train is:
8
The loss for epoch 1
2.164675362408161
The running loss is:
9.421775847673416
The number of items in train is:
8
The loss for epoch 2
1.177721980959177
The running loss is:
6.757692888379097
The number of items in train is:
8
The loss for epoch 3
0.8447116110473871
The running loss is:
6.253585696220398
The number of items in train is:
8
The loss for epoch 4
0.7816982120275497
The running loss is:
5.741266116499901
The number of items in train is:
8
The loss for epoch 5
0.7176582645624876
The running loss is:
4.830026730895042
The number of items in train is:
8
The loss for epoch 6
0.6037533413618803
The running loss is:
4.553853526711464
The number of items in train is:
8
The loss for epoch 7
0.569231690838933
The running loss is:
4.212658815085888
The number of items in train is:
8
The loss for epoch 8
0.526582351885736
The running loss is:
4.101347729563713
The number of items in train is:
8
The loss for epoch 9
0.5126684661954641
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.757821
48 30755 ... 14.091363
49 30756 ... 14.059839
50 30757 ... 13.189163
51 30758 ... 10.963506
52 30759 ... 10.853949
53 30760 ... 11.138344
54 30761 ... 11.210142
55 30762 ... 11.705401
56 30763 ... 11.253247
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: os66dtsw wandb: Agent Starting Run: dtx619mj with config: batch_size: 5 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: dtx619mj
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.538036316633224
The number of items in train is:
7
The loss for epoch 0
1.648290902376175
The running loss is:
27.30086961388588
The number of items in train is:
7
The loss for epoch 1
3.9001242305551256
The running loss is:
6.902018129825592
The number of items in train is:
7
The loss for epoch 2
0.9860025899750846
The running loss is:
8.486170530319214
The number of items in train is:
7
The loss for epoch 3
1.2123100757598877
The running loss is:
5.592561990022659
The number of items in train is:
7
The loss for epoch 4
0.7989374271460942
The running loss is:
5.384973257780075
The number of items in train is:
7
The loss for epoch 5
0.7692818939685822
The running loss is:
4.928272694349289
The number of items in train is:
7
The loss for epoch 6
0.7040389563356128
The running loss is:
4.354663372039795
The number of items in train is:
7
The loss for epoch 7
0.6220947674342564
The running loss is:
4.097138851881027
The number of items in train is:
7
The loss for epoch 8
0.5853055502687182
The running loss is:
3.9094666242599487
The number of items in train is:
7
The loss for epoch 9
0.5584952320371356
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.796641
48 30755 ... 9.342697
49 30756 ... 9.459212
50 30757 ... 9.968360
51 30758 ... 8.718388
52 30759 ... 8.447587
53 30760 ... 8.985465
54 30761 ... 8.420585
55 30762 ... 9.642568
56 30763 ... 9.002261
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: dtx619mj wandb: Agent Starting Run: ph3sz2jf with config: batch_size: 5 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ph3sz2jf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.805723547935486
The number of items in train is:
7
The loss for epoch 0
1.2579605068479265
The running loss is:
20.8605694770813
The number of items in train is:
7
The loss for epoch 1
2.980081353868757
The running loss is:
5.607284247875214
The number of items in train is:
7
The loss for epoch 2
0.8010406068393162
The running loss is:
6.950852543115616
The number of items in train is:
7
The loss for epoch 3
0.9929789347308022
The running loss is:
5.903511047363281
The number of items in train is:
7
The loss for epoch 4
0.8433587210518974
The running loss is:
5.360262036323547
The number of items in train is:
7
The loss for epoch 5
0.7657517194747925
The running loss is:
4.968137204647064
The number of items in train is:
7
The loss for epoch 6
0.709733886378152
The running loss is:
4.6906518042087555
The number of items in train is:
7
The loss for epoch 7
0.6700931148869651
The running loss is:
4.265324801206589
The number of items in train is:
7
The loss for epoch 8
0.6093321144580841
The running loss is:
4.243742972612381
The number of items in train is:
7
The loss for epoch 9
0.606248996087483
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.965941
48 30755 ... 7.205519
49 30756 ... 8.403504
50 30757 ... 9.476584
51 30758 ... 7.341923
52 30759 ... 7.236106
53 30760 ... 6.708858
54 30761 ... 3.748622
55 30762 ... 3.855751
56 30763 ... 3.793899
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ph3sz2jf wandb: Agent Starting Run: tl2ee0kx with config: batch_size: 5 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: tl2ee0kx
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
79.56610406935215
The number of items in train is:
8
The loss for epoch 0
9.945763008669019
The running loss is:
7.204314440488815
The number of items in train is:
8
The loss for epoch 1
0.9005393050611019
The running loss is:
34.79838861897588
The number of items in train is:
8
The loss for epoch 2
4.349798577371985
The running loss is:
13.492564976215363
The number of items in train is:
8
The loss for epoch 3
1.6865706220269203
The running loss is:
8.105150907533243
The number of items in train is:
8
The loss for epoch 4
1.0131438634416554
The running loss is:
17.24639244377613
The number of items in train is:
8
The loss for epoch 5
2.1557990554720163
The running loss is:
15.907869756221771
The number of items in train is:
8
The loss for epoch 6
1.9884837195277214
The running loss is:
9.063403755426407
The number of items in train is:
8
The loss for epoch 7
1.1329254694283009
The running loss is:
7.892887741327286
The number of items in train is:
8
The loss for epoch 8
0.9866109676659107
The running loss is:
7.113882530480623
The number of items in train is:
8
The loss for epoch 9
0.8892353163100779
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.513741
48 30755 ... 7.839818
49 30756 ... 7.624097
50 30757 ... 7.607502
51 30758 ... 6.127538
52 30759 ... 7.737118
53 30760 ... 7.606065
54 30761 ... 6.173356
55 30762 ... 6.936601
56 30763 ... 7.023078
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tl2ee0kx wandb: Agent Starting Run: 7fa9a6s1 with config: batch_size: 5 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 7fa9a6s1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
52.08390510082245
The number of items in train is:
7
The loss for epoch 0
7.440557871546064
The running loss is:
11.381277471780777
The number of items in train is:
7
The loss for epoch 1
1.6258967816829681
The running loss is:
25.816108763217926
The number of items in train is:
7
The loss for epoch 2
3.6880155376025607
The running loss is:
5.692464888095856
The number of items in train is:
7
The loss for epoch 3
0.8132092697279794
The running loss is:
12.835353791713715
The number of items in train is:
7
The loss for epoch 4
1.8336219702448164
The running loss is:
20.29457151889801
The number of items in train is:
7
The loss for epoch 5
2.899224502699716
The running loss is:
6.967081665992737
The number of items in train is:
7
The loss for epoch 6
0.9952973808561053
The running loss is:
7.198956787586212
The number of items in train is:
7
The loss for epoch 7
1.0284223982266016
The running loss is:
7.881454288959503
The number of items in train is:
7
The loss for epoch 8
1.1259220412799291
The running loss is:
7.26533517241478
The number of items in train is:
7
The loss for epoch 9
1.037905024630683
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.481693
48 30755 ... 7.128554
49 30756 ... 6.864052
50 30757 ... 6.029053
51 30758 ... 6.576490
52 30759 ... 6.761997
53 30760 ... 6.898374
54 30761 ... 7.043981
55 30762 ... 7.331190
56 30763 ... 6.609051
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7fa9a6s1 wandb: Agent Starting Run: 2g1uqyaf with config: batch_size: 5 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 2g1uqyaf
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
37.419967859983444
The number of items in train is:
7
The loss for epoch 0
5.345709694283349
The running loss is:
10.821948528289795
The number of items in train is:
7
The loss for epoch 1
1.545992646898542
The running loss is:
9.870258629322052
The number of items in train is:
7
The loss for epoch 2
1.4100369470460075
The running loss is:
5.8033487200737
The number of items in train is:
7
The loss for epoch 3
0.8290498171533857
The running loss is:
6.369944393634796
The number of items in train is:
7
The loss for epoch 4
0.9099920562335423
The running loss is:
5.617344975471497
The number of items in train is:
7
The loss for epoch 5
0.8024778536387852
The running loss is:
5.247073173522949
The number of items in train is:
7
The loss for epoch 6
0.7495818819318499
The running loss is:
5.167417734861374
The number of items in train is:
7
The loss for epoch 7
0.7382025335516248
The running loss is:
5.165225565433502
The number of items in train is:
7
The loss for epoch 8
0.7378893664905003
The running loss is:
4.82859468460083
The number of items in train is:
7
The loss for epoch 9
0.6897992406572614
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.674891
48 30755 ... 11.012010
49 30756 ... 10.963237
50 30757 ... 10.817793
51 30758 ... 5.869459
52 30759 ... 5.821937
53 30760 ... 5.026206
54 30761 ... 2.507891
55 30762 ... 2.534259
56 30763 ... 3.081643
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2g1uqyaf wandb: Agent Starting Run: fbzwgj5d with config: batch_size: 5 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fbzwgj5d
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.336233288049698
The number of items in train is:
7
The loss for epoch 0
1.3337476125785284
The running loss is:
5.11325016617775
The number of items in train is:
7
The loss for epoch 1
0.7304643094539642
The running loss is:
4.894846081733704
The number of items in train is:
7
The loss for epoch 2
0.6992637259619576
The running loss is:
4.361954137682915
The number of items in train is:
7
The loss for epoch 3
0.6231363053832736
The running loss is:
3.946231722831726
The number of items in train is:
7
The loss for epoch 4
0.5637473889759609
The running loss is:
4.036977797746658
The number of items in train is:
7
The loss for epoch 5
0.5767111139638084
The running loss is:
3.637524761259556
The number of items in train is:
7
The loss for epoch 6
0.5196463944656509
The running loss is:
3.5761826187372208
The number of items in train is:
7
The loss for epoch 7
0.5108832312481744
The running loss is:
3.4031307995319366
The number of items in train is:
7
The loss for epoch 8
0.4861615427902767
The running loss is:
3.205967530608177
The number of items in train is:
7
The loss for epoch 9
0.4579953615154539
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.806149
48 30755 ... 11.034535
49 30756 ... 14.467689
50 30757 ... 14.238250
51 30758 ... 10.971130
52 30759 ... 10.287059
53 30760 ... 10.894358
54 30761 ... 10.626654
55 30762 ... 10.909733
56 30763 ... 12.139064
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fbzwgj5d wandb: Agent Starting Run: z773q140 with config: batch_size: 5 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: z773q140
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.177690148353577
The number of items in train is:
7
The loss for epoch 0
1.3110985926219396
The running loss is:
5.94622865319252
The number of items in train is:
7
The loss for epoch 1
0.8494612361703601
The running loss is:
5.502836525440216
The number of items in train is:
7
The loss for epoch 2
0.7861195036343166
The running loss is:
4.882712662220001
The number of items in train is:
7
The loss for epoch 3
0.697530380317143
The running loss is:
4.823515743017197
The number of items in train is:
7
The loss for epoch 4
0.6890736775738853
The running loss is:
4.585278883576393
The number of items in train is:
7
The loss for epoch 5
0.6550398405109134
The running loss is:
4.415525987744331
The number of items in train is:
7
The loss for epoch 6
0.6307894268206188
The running loss is:
4.571172222495079
The number of items in train is:
7
The loss for epoch 7
0.6530246032135827
The running loss is:
4.134524956345558
The number of items in train is:
7
The loss for epoch 8
0.5906464223350797
The running loss is:
4.182448834180832
The number of items in train is:
7
The loss for epoch 9
0.5974926905972617
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.957873
48 30755 ... 10.888971
49 30756 ... 12.070364
50 30757 ... 12.814865
51 30758 ... 12.341984
52 30759 ... 10.130991
53 30760 ... 10.580561
54 30761 ... 11.226346
55 30762 ... 11.099922
56 30763 ... 11.260043
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z773q140 wandb: Agent Starting Run: c17omt6j with config: batch_size: 5 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: c17omt6j
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.464878857135773
The number of items in train is:
7
The loss for epoch 0
1.2092684081622533
The running loss is:
5.037981957197189
The number of items in train is:
7
The loss for epoch 1
0.719711708171027
The running loss is:
4.809891790151596
The number of items in train is:
7
The loss for epoch 2
0.6871273985930851
The running loss is:
4.0787065625190735
The number of items in train is:
7
The loss for epoch 3
0.5826723660741534
The running loss is:
4.271046087145805
The number of items in train is:
7
The loss for epoch 4
0.6101494410208294
The running loss is:
4.067079246044159
The number of items in train is:
7
The loss for epoch 5
0.5810113208634513
The running loss is:
4.014323055744171
The number of items in train is:
7
The loss for epoch 6
0.5734747222491673
The running loss is:
3.7231625616550446
The number of items in train is:
7
The loss for epoch 7
0.5318803659507206
The running loss is:
3.71854804456234
The number of items in train is:
7
The loss for epoch 8
0.5312211492231914
The running loss is:
3.612421989440918
The number of items in train is:
7
The loss for epoch 9
0.5160602842058454
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.139462
48 30755 ... 9.361436
49 30756 ... 10.952075
50 30757 ... 10.844501
51 30758 ... 9.159294
52 30759 ... 7.213850
53 30760 ... 7.122150
54 30761 ... 7.227113
55 30762 ... 6.614833
56 30763 ... 6.647117
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c17omt6j wandb: Agent Starting Run: dc420ovb with config: batch_size: 5 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: dc420ovb
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.042995542287827
The number of items in train is:
7
The loss for epoch 0
1.434713648898261
The running loss is:
7.474764108657837
The number of items in train is:
7
The loss for epoch 1
1.0678234440939767
The running loss is:
4.9013950526714325
The number of items in train is:
7
The loss for epoch 2
0.700199293238776
The running loss is:
4.431417480111122
The number of items in train is:
7
The loss for epoch 3
0.6330596400158746
The running loss is:
4.164117723703384
The number of items in train is:
7
The loss for epoch 4
0.594873960529055
The running loss is:
3.84988109767437
The number of items in train is:
7
The loss for epoch 5
0.5499830139534814
The running loss is:
3.5169313699007034
The number of items in train is:
7
The loss for epoch 6
0.502418767128672
The running loss is:
3.107982710003853
The number of items in train is:
7
The loss for epoch 7
0.4439975300005504
The running loss is:
3.3591590151190758
The number of items in train is:
7
The loss for epoch 8
0.4798798593027251
The running loss is:
3.0317525193095207
The number of items in train is:
7
The loss for epoch 9
0.43310750275850296
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.845029
48 30755 ... 11.769980
49 30756 ... 16.313171
50 30757 ... 15.718273
51 30758 ... 12.462557
52 30759 ... 11.991672
53 30760 ... 12.592597
54 30761 ... 12.409809
55 30762 ... 13.502852
56 30763 ... 15.533869
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: dc420ovb wandb: Agent Starting Run: 2lak3mf3 with config: batch_size: 5 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2lak3mf3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.486467003822327
The number of items in train is:
7
The loss for epoch 0
1.355209571974618
The running loss is:
7.774271607398987
The number of items in train is:
7
The loss for epoch 1
1.1106102296284266
The running loss is:
5.2772374749183655
The number of items in train is:
7
The loss for epoch 2
0.7538910678454808
The running loss is:
5.003746151924133
The number of items in train is:
7
The loss for epoch 3
0.7148208788463047
The running loss is:
4.869605340063572
The number of items in train is:
7
The loss for epoch 4
0.6956579057233674
The running loss is:
4.4538838267326355
The number of items in train is:
7
The loss for epoch 5
0.6362691181046622
The running loss is:
4.390820115804672
The number of items in train is:
7
The loss for epoch 6
0.6272600165435246
The running loss is:
4.38667120039463
The number of items in train is:
7
The loss for epoch 7
0.6266673143420901
The running loss is:
3.9946878850460052
The number of items in train is:
7
The loss for epoch 8
0.570669697863715
The running loss is:
3.964384078979492
The number of items in train is:
7
The loss for epoch 9
0.566340582711356
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.839034
48 30755 ... 11.101344
49 30756 ... 12.585072
50 30757 ... 13.072854
51 30758 ... 13.150121
52 30759 ... 10.736032
53 30760 ... 11.587616
54 30761 ... 11.559414
55 30762 ... 11.871531
56 30763 ... 12.667596
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2lak3mf3 wandb: Agent Starting Run: 1vfg1v1j with config: batch_size: 5 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1vfg1v1j
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.01353543996811
The number of items in train is:
7
The loss for epoch 0
1.2876479199954443
The running loss is:
8.305128276348114
The number of items in train is:
7
The loss for epoch 1
1.1864468966211592
The running loss is:
4.578442484140396
The number of items in train is:
7
The loss for epoch 2
0.6540632120200566
The running loss is:
4.405091732740402
The number of items in train is:
7
The loss for epoch 3
0.6292988189629146
The running loss is:
4.34169502556324
The number of items in train is:
7
The loss for epoch 4
0.6202421465090343
The running loss is:
3.9862598925828934
The number of items in train is:
7
The loss for epoch 5
0.5694656989404133
The running loss is:
3.979832261800766
The number of items in train is:
7
The loss for epoch 6
0.568547465971538
The running loss is:
3.5811107754707336
The number of items in train is:
7
The loss for epoch 7
0.5115872536386762
The running loss is:
3.5624044686555862
The number of items in train is:
7
The loss for epoch 8
0.5089149240936551
The running loss is:
3.448199100792408
The number of items in train is:
7
The loss for epoch 9
0.4925998715417726
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.244447
48 30755 ... 9.826646
49 30756 ... 11.896688
50 30757 ... 11.638386
51 30758 ... 9.964475
52 30759 ... 8.469487
53 30760 ... 8.533617
54 30761 ... 8.421778
55 30762 ... 8.096305
56 30763 ... 8.440117
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1vfg1v1j wandb: Agent Starting Run: j8qqp3c2 with config: batch_size: 5 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: j8qqp3c2
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.458968162536621
The number of items in train is:
7
The loss for epoch 0
1.3512811660766602
The running loss is:
21.075702905654907
The number of items in train is:
7
The loss for epoch 1
3.010814700807844
The running loss is:
5.451179146766663
The number of items in train is:
7
The loss for epoch 2
0.7787398781095233
The running loss is:
6.688863754272461
The number of items in train is:
7
The loss for epoch 3
0.9555519648960659
The running loss is:
6.188786864280701
The number of items in train is:
7
The loss for epoch 4
0.8841124091829572
The running loss is:
5.368324548006058
The number of items in train is:
7
The loss for epoch 5
0.7669035068580082
The running loss is:
4.517726391553879
The number of items in train is:
7
The loss for epoch 6
0.645389484507697
The running loss is:
4.753752812743187
The number of items in train is:
7
The loss for epoch 7
0.6791075446775982
The running loss is:
4.646036148071289
The number of items in train is:
7
The loss for epoch 8
0.6637194497244698
The running loss is:
4.074129417538643
The number of items in train is:
7
The loss for epoch 9
0.5820184882198062
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.402539
48 30755 ... 12.075924
49 30756 ... 15.184203
50 30757 ... 12.845176
51 30758 ... 8.898929
52 30759 ... 11.674198
53 30760 ... 11.553167
54 30761 ... 11.936520
55 30762 ... 12.232157
56 30763 ... 13.043743
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: j8qqp3c2 wandb: Agent Starting Run: zewye6m1 with config: batch_size: 5 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: zewye6m1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.001771569252014
The number of items in train is:
7
The loss for epoch 0
1.428824509893145
The running loss is:
20.346972823143005
The number of items in train is:
7
The loss for epoch 1
2.9067104033061435
The running loss is:
5.735487461090088
The number of items in train is:
7
The loss for epoch 2
0.8193553515842983
The running loss is:
6.7128947377204895
The number of items in train is:
7
The loss for epoch 3
0.9589849625314985
The running loss is:
6.372850209474564
The number of items in train is:
7
The loss for epoch 4
0.9104071727820805
The running loss is:
5.315346002578735
The number of items in train is:
7
The loss for epoch 5
0.7593351432255336
The running loss is:
4.923664838075638
The number of items in train is:
7
The loss for epoch 6
0.7033806911536625
The running loss is:
4.619252592325211
The number of items in train is:
7
The loss for epoch 7
0.6598932274750301
The running loss is:
4.849480867385864
The number of items in train is:
7
The loss for epoch 8
0.6927829810551235
The running loss is:
4.769946187734604
The number of items in train is:
7
The loss for epoch 9
0.6814208839620862
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.882496
48 30755 ... 12.364532
49 30756 ... 14.726078
50 30757 ... 13.591410
51 30758 ... 12.194124
52 30759 ... 12.492190
53 30760 ... 12.379921
54 30761 ... 12.688085
55 30762 ... 12.570847
56 30763 ... 12.598701
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zewye6m1 wandb: Agent Starting Run: 6gwcnc5t with config: batch_size: 5 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 6gwcnc5t
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.065265715122223
The number of items in train is:
7
The loss for epoch 0
1.5807522450174605
The running loss is:
19.994363248348236
The number of items in train is:
7
The loss for epoch 1
2.856337606906891
The running loss is:
5.749635964632034
The number of items in train is:
7
The loss for epoch 2
0.8213765663760049
The running loss is:
6.598259687423706
The number of items in train is:
7
The loss for epoch 3
0.9426085267748151
The running loss is:
4.696272283792496
The number of items in train is:
7
The loss for epoch 4
0.6708960405417851
The running loss is:
4.804319143295288
The number of items in train is:
7
The loss for epoch 5
0.6863313061850411
The running loss is:
4.463131815195084
The number of items in train is:
7
The loss for epoch 6
0.6375902593135834
The running loss is:
4.612153172492981
The number of items in train is:
7
The loss for epoch 7
0.6588790246418544
The running loss is:
4.284528285264969
The number of items in train is:
7
The loss for epoch 8
0.6120754693235669
The running loss is:
4.153792500495911
The number of items in train is:
7
The loss for epoch 9
0.593398928642273
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.800093
48 30755 ... 11.202961
49 30756 ... 11.976234
50 30757 ... 11.460857
51 30758 ... 10.998887
52 30759 ... 10.735220
53 30760 ... 10.952649
54 30761 ... 10.644355
55 30762 ... 10.612105
56 30763 ... 11.144648
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6gwcnc5t wandb: Agent Starting Run: 1oow5e52 with config: batch_size: 5 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1oow5e52
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
39.09426712989807
The number of items in train is:
7
The loss for epoch 0
5.584895304271153
The running loss is:
8.815387278795242
The number of items in train is:
7
The loss for epoch 1
1.2593410398278917
The running loss is:
10.441057562828064
The number of items in train is:
7
The loss for epoch 2
1.4915796518325806
The running loss is:
7.836777687072754
The number of items in train is:
7
The loss for epoch 3
1.119539669581822
The running loss is:
5.5894342958927155
The number of items in train is:
7
The loss for epoch 4
0.7984906136989594
The running loss is:
4.797979637980461
The number of items in train is:
7
The loss for epoch 5
0.6854256625686374
The running loss is:
5.106695920228958
The number of items in train is:
7
The loss for epoch 6
0.7295279886041369
The running loss is:
5.3624774515628815
The number of items in train is:
7
The loss for epoch 7
0.7660682073661259
The running loss is:
5.132751166820526
The number of items in train is:
7
The loss for epoch 8
0.7332501666886466
The running loss is:
4.637645840644836
The number of items in train is:
7
The loss for epoch 9
0.6625208343778338
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.461702
48 30755 ... 11.493561
49 30756 ... 7.273075
50 30757 ... 12.487080
51 30758 ... 11.164696
52 30759 ... 10.003759
53 30760 ... 9.965696
54 30761 ... 9.195720
55 30762 ... 9.681444
56 30763 ... 10.299913
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1oow5e52 wandb: Agent Starting Run: ervqlzd5 with config: batch_size: 5 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ervqlzd5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
36.73223286867142
The number of items in train is:
7
The loss for epoch 0
5.247461838381631
The running loss is:
8.665028989315033
The number of items in train is:
7
The loss for epoch 1
1.2378612841878618
The running loss is:
10.718747615814209
The number of items in train is:
7
The loss for epoch 2
1.53124965940203
The running loss is:
6.298239514231682
The number of items in train is:
7
The loss for epoch 3
0.8997485020330974
The running loss is:
6.406042277812958
The number of items in train is:
7
The loss for epoch 4
0.9151488968304226
The running loss is:
6.371782273054123
The number of items in train is:
7
The loss for epoch 5
0.9102546104363033
The running loss is:
6.079530298709869
The number of items in train is:
7
The loss for epoch 6
0.8685043283871242
The running loss is:
6.881429195404053
The number of items in train is:
7
The loss for epoch 7
0.9830613136291504
The running loss is:
5.822851479053497
The number of items in train is:
7
The loss for epoch 8
0.831835925579071
The running loss is:
5.205782949924469
The number of items in train is:
7
The loss for epoch 9
0.7436832785606384
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.829610
48 30755 ... 13.508774
49 30756 ... 13.238535
50 30757 ... 12.937251
51 30758 ... 12.953267
52 30759 ... 11.199141
53 30760 ... 11.241271
54 30761 ... 11.257262
55 30762 ... 11.259697
56 30763 ... 11.264960
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ervqlzd5 wandb: Agent Starting Run: 1csgx861 with config: batch_size: 5 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1csgx861
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
45.76984786987305
The number of items in train is:
7
The loss for epoch 0
6.538549695696149
The running loss is:
6.865525305271149
The number of items in train is:
7
The loss for epoch 1
0.9807893293244498
The running loss is:
13.207008957862854
The number of items in train is:
7
The loss for epoch 2
1.8867155654089791
The running loss is:
6.200265973806381
The number of items in train is:
7
The loss for epoch 3
0.8857522819723401
The running loss is:
7.200608611106873
The number of items in train is:
7
The loss for epoch 4
1.0286583730152674
The running loss is:
5.776394367218018
The number of items in train is:
7
The loss for epoch 5
0.8251991953168597
The running loss is:
5.003000259399414
The number of items in train is:
7
The loss for epoch 6
0.7147143227713448
The running loss is:
5.345502436161041
The number of items in train is:
7
The loss for epoch 7
0.763643205165863
The running loss is:
4.749779254198074
The number of items in train is:
7
The loss for epoch 8
0.6785398934568677
The running loss is:
4.6609319150447845
The number of items in train is:
7
The loss for epoch 9
0.6658474164349693
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.792873
48 30755 ... 9.695145
49 30756 ... 9.721715
50 30757 ... 10.123501
51 30758 ... 9.551498
52 30759 ... 9.261765
53 30760 ... 9.297737
54 30761 ... 9.213287
55 30762 ... 8.607971
56 30763 ... 8.690456
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1csgx861 wandb: Agent Starting Run: qf1wsozx with config: batch_size: 5 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: qf1wsozx
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.453750848770142
The number of items in train is:
7
The loss for epoch 0
1.207678692681449
The running loss is:
5.78881973028183
The number of items in train is:
7
The loss for epoch 1
0.8269742471831185
The running loss is:
4.940449774265289
The number of items in train is:
7
The loss for epoch 2
0.7057785391807556
The running loss is:
4.20541875064373
The number of items in train is:
7
The loss for epoch 3
0.6007741072348186
The running loss is:
3.9624558836221695
The number of items in train is:
7
The loss for epoch 4
0.5660651262317385
The running loss is:
3.706973645836115
The number of items in train is:
7
The loss for epoch 5
0.5295676636908736
The running loss is:
3.901065617799759
The number of items in train is:
7
The loss for epoch 6
0.5572950882571084
The running loss is:
3.821559399366379
The number of items in train is:
7
The loss for epoch 7
0.5459370570523399
The running loss is:
3.222411021590233
The number of items in train is:
7
The loss for epoch 8
0.46034443165574757
The running loss is:
3.5929430425167084
The number of items in train is:
7
The loss for epoch 9
0.5132775775023869
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.300883
48 30755 ... 7.877327
49 30756 ... 9.205451
50 30757 ... 11.192038
51 30758 ... 10.560779
52 30759 ... 8.089823
53 30760 ... 6.922207
54 30761 ... 6.764965
55 30762 ... 6.743966
56 30763 ... 6.344927
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qf1wsozx wandb: Agent Starting Run: 9y7auasy with config: batch_size: 5 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 9y7auasy
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
7.978905558586121
The number of items in train is:
7
The loss for epoch 0
1.1398436512265886
The running loss is:
5.127258628606796
The number of items in train is:
7
The loss for epoch 1
0.7324655183723995
The running loss is:
4.72313766181469
The number of items in train is:
7
The loss for epoch 2
0.6747339516878128
The running loss is:
4.185404866933823
The number of items in train is:
7
The loss for epoch 3
0.5979149809905461
The running loss is:
4.080670237541199
The number of items in train is:
7
The loss for epoch 4
0.5829528910773141
The running loss is:
3.9133199751377106
The number of items in train is:
7
The loss for epoch 5
0.5590457107339587
The running loss is:
3.774104356765747
The number of items in train is:
7
The loss for epoch 6
0.5391577652522496
The running loss is:
3.395247310400009
The number of items in train is:
7
The loss for epoch 7
0.48503533005714417
The running loss is:
3.3610329627990723
The number of items in train is:
7
The loss for epoch 8
0.48014756611415316
The running loss is:
3.049194633960724
The number of items in train is:
7
The loss for epoch 9
0.43559923342296053
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.223148
48 30755 ... 8.128177
49 30756 ... 9.358207
50 30757 ... 11.647758
51 30758 ... 10.551282
52 30759 ... 6.696947
53 30760 ... 4.689186
54 30761 ... 4.889297
55 30762 ... 4.608911
56 30763 ... 4.071383
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9y7auasy wandb: Agent Starting Run: notixq7k with config: batch_size: 5 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: notixq7k
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.997486591339111
The number of items in train is:
7
The loss for epoch 0
1.2853552273341589
The running loss is:
7.690601214766502
The number of items in train is:
7
The loss for epoch 1
1.0986573163952147
The running loss is:
5.448296874761581
The number of items in train is:
7
The loss for epoch 2
0.7783281249659402
The running loss is:
4.938282564282417
The number of items in train is:
7
The loss for epoch 3
0.705468937754631
The running loss is:
4.373410284519196
The number of items in train is:
7
The loss for epoch 4
0.6247728977884565
The running loss is:
4.2776922807097435
The number of items in train is:
7
The loss for epoch 5
0.611098897244249
The running loss is:
4.26933291554451
The number of items in train is:
7
The loss for epoch 6
0.6099047022206443
The running loss is:
4.139234617352486
The number of items in train is:
7
The loss for epoch 7
0.5913192310503551
The running loss is:
4.1257902681827545
The number of items in train is:
7
The loss for epoch 8
0.5893986097403935
The running loss is:
4.044198751449585
The number of items in train is:
7
The loss for epoch 9
0.5777426787785122
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.824650
48 30755 ... 8.085434
49 30756 ... 8.181070
50 30757 ... 8.486726
51 30758 ... 8.320390
52 30759 ... 6.810356
53 30760 ... 4.630260
54 30761 ... 4.928142
55 30762 ... 5.116070
56 30763 ... 4.218055
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: notixq7k wandb: Agent Starting Run: w9adv0f5 with config: batch_size: 5 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: w9adv0f5
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.615247905254364
The number of items in train is:
7
The loss for epoch 0
1.3736068436077662
The running loss is:
10.547258883714676
The number of items in train is:
7
The loss for epoch 1
1.5067512691020966
The running loss is:
4.555299267172813
The number of items in train is:
7
The loss for epoch 2
0.6507570381675448
The running loss is:
4.357711434364319
The number of items in train is:
7
The loss for epoch 3
0.6225302049091884
The running loss is:
4.136801086366177
The number of items in train is:
7
The loss for epoch 4
0.5909715837665966
The running loss is:
3.620665431022644
The number of items in train is:
7
The loss for epoch 5
0.5172379187175206
The running loss is:
3.600349932909012
The number of items in train is:
7
The loss for epoch 6
0.5143357047012874
The running loss is:
3.7059518694877625
The number of items in train is:
7
The loss for epoch 7
0.529421695641109
The running loss is:
3.25237987190485
The number of items in train is:
7
The loss for epoch 8
0.46462569598640713
The running loss is:
3.219434306025505
The number of items in train is:
7
The loss for epoch 9
0.45991918657507214
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.156307
48 30755 ... 7.571031
49 30756 ... 9.347271
50 30757 ... 11.671964
51 30758 ... 10.866534
52 30759 ... 8.150193
53 30760 ... 7.649214
54 30761 ... 7.405383
55 30762 ... 6.930293
56 30763 ... 6.566906
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: w9adv0f5 wandb: Agent Starting Run: gacyucuv with config: batch_size: 5 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: gacyucuv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.557386875152588
The number of items in train is:
7
The loss for epoch 0
1.2224838393075126
The running loss is:
7.062704995274544
The number of items in train is:
7
The loss for epoch 1
1.008957856467792
The running loss is:
4.506389617919922
The number of items in train is:
7
The loss for epoch 2
0.6437699454171317
The running loss is:
4.436160206794739
The number of items in train is:
7
The loss for epoch 3
0.6337371723992484
The running loss is:
4.230875015258789
The number of items in train is:
7
The loss for epoch 4
0.6044107164655413
The running loss is:
3.8724400401115417
The number of items in train is:
7
The loss for epoch 5
0.5532057200159345
The running loss is:
3.7256204038858414
The number of items in train is:
7
The loss for epoch 6
0.5322314862694059
The running loss is:
3.1940614581108093
The number of items in train is:
7
The loss for epoch 7
0.4562944940158299
The running loss is:
3.305657684803009
The number of items in train is:
7
The loss for epoch 8
0.4722368121147156
The running loss is:
2.8400733023881912
The number of items in train is:
7
The loss for epoch 9
0.4057247574840273
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.997660
48 30755 ... 8.063605
49 30756 ... 9.996701
50 30757 ... 12.595577
51 30758 ... 10.900799
52 30759 ... 6.122150
53 30760 ... 5.258817
54 30761 ... 5.399448
55 30762 ... 4.413244
56 30763 ... 4.609431
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gacyucuv wandb: Agent Starting Run: 8ioil8pg with config: batch_size: 5 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8ioil8pg
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.57857894897461
The number of items in train is:
7
The loss for epoch 0
1.6540827069963728
The running loss is:
15.518137007951736
The number of items in train is:
7
The loss for epoch 1
2.2168767154216766
The running loss is:
5.213935896754265
The number of items in train is:
7
The loss for epoch 2
0.7448479852506092
The running loss is:
5.0660145208239555
The number of items in train is:
7
The loss for epoch 3
0.7237163601177079
The running loss is:
5.008541256189346
The number of items in train is:
7
The loss for epoch 4
0.7155058937413352
The running loss is:
4.271195217967033
The number of items in train is:
7
The loss for epoch 5
0.610170745423862
The running loss is:
4.4964863657951355
The number of items in train is:
7
The loss for epoch 6
0.6423551951135907
The running loss is:
4.307799831032753
The number of items in train is:
7
The loss for epoch 7
0.6153999758618218
The running loss is:
4.247691720724106
The number of items in train is:
7
The loss for epoch 8
0.6068131029605865
The running loss is:
4.0502769947052
The number of items in train is:
7
The loss for epoch 9
0.5786109992436
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.857596
48 30755 ... 8.346721
49 30756 ... 8.373069
50 30757 ... 8.797526
51 30758 ... 8.479051
52 30759 ... 6.737048
53 30760 ... 5.295413
54 30761 ... 5.722424
55 30762 ... 5.626678
56 30763 ... 4.922710
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8ioil8pg wandb: Agent Starting Run: v2jkyt2t with config: batch_size: 5 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: v2jkyt2t
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.313868522644043
The number of items in train is:
7
The loss for epoch 0
2.0448383603777205
The running loss is:
21.173898339271545
The number of items in train is:
7
The loss for epoch 1
3.024842619895935
The running loss is:
8.537031590938568
The number of items in train is:
7
The loss for epoch 2
1.2195759415626526
The running loss is:
9.553512573242188
The number of items in train is:
7
The loss for epoch 3
1.3647875104631697
The running loss is:
5.124066233634949
The number of items in train is:
7
The loss for epoch 4
0.7320094619478498
The running loss is:
4.670688271522522
The number of items in train is:
7
The loss for epoch 5
0.6672411816460746
The running loss is:
4.281704246997833
The number of items in train is:
7
The loss for epoch 6
0.6116720352854047
The running loss is:
3.969690963625908
The number of items in train is:
7
The loss for epoch 7
0.5670987090894154
The running loss is:
4.173694938421249
The number of items in train is:
7
The loss for epoch 8
0.5962421340601785
The running loss is:
3.5966562777757645
The number of items in train is:
7
The loss for epoch 9
0.5138080396822521
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 11.959491
48 30755 ... 7.152155
49 30756 ... 11.036368
50 30757 ... 14.112470
51 30758 ... 12.477591
52 30759 ... 9.832200
53 30760 ... 10.799255
54 30761 ... 11.602201
55 30762 ... 9.996349
56 30763 ... 10.044203
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v2jkyt2t wandb: Agent Starting Run: b7cia89b with config: batch_size: 5 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: b7cia89b
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.498386919498444
The number of items in train is:
7
The loss for epoch 0
1.4997695599283491
The running loss is:
16.961153388023376
The number of items in train is:
7
The loss for epoch 1
2.423021912574768
The running loss is:
6.070439994335175
The number of items in train is:
7
The loss for epoch 2
0.8672057134764535
The running loss is:
7.044522300362587
The number of items in train is:
7
The loss for epoch 3
1.0063603286232268
The running loss is:
5.524796187877655
The number of items in train is:
7
The loss for epoch 4
0.7892565982682365
The running loss is:
5.174478992819786
The number of items in train is:
7
The loss for epoch 5
0.7392112846885409
The running loss is:
5.18627268075943
The number of items in train is:
7
The loss for epoch 6
0.7408960972513471
The running loss is:
4.556998088955879
The number of items in train is:
7
The loss for epoch 7
0.650999726993697
The running loss is:
4.025437951087952
The number of items in train is:
7
The loss for epoch 8
0.5750625644411359
The running loss is:
3.7488027215003967
The number of items in train is:
7
The loss for epoch 9
0.5355432459286281
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.350999
48 30755 ... 8.313608
49 30756 ... 9.650146
50 30757 ... 13.457047
51 30758 ... 11.586737
52 30759 ... 7.641543
53 30760 ... 7.716665
54 30761 ... 8.501719
55 30762 ... 7.343888
56 30763 ... 6.925780
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b7cia89b wandb: Agent Starting Run: msl0siip with config: batch_size: 5 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: msl0siip
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.923059403896332
The number of items in train is:
7
The loss for epoch 0
2.8461513434137617
The running loss is:
21.545911133289337
The number of items in train is:
7
The loss for epoch 1
3.0779873047556197
The running loss is:
14.83446341753006
The number of items in train is:
7
The loss for epoch 2
2.1192090596471513
The running loss is:
9.760437935590744
The number of items in train is:
7
The loss for epoch 3
1.3943482765129633
The running loss is:
5.346604257822037
The number of items in train is:
7
The loss for epoch 4
0.763800608260291
The running loss is:
6.062074542045593
The number of items in train is:
7
The loss for epoch 5
0.8660106488636562
The running loss is:
5.347100764513016
The number of items in train is:
7
The loss for epoch 6
0.7638715377875737
The running loss is:
4.903612896800041
The number of items in train is:
7
The loss for epoch 7
0.7005161281142916
The running loss is:
4.763592883944511
The number of items in train is:
7
The loss for epoch 8
0.6805132691349302
The running loss is:
4.394327566027641
The number of items in train is:
7
The loss for epoch 9
0.6277610808610916
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.194539
48 30755 ... 8.257804
49 30756 ... 8.486530
50 30757 ... 8.778533
51 30758 ... 8.804259
52 30759 ... 8.143517
53 30760 ... 7.652658
54 30761 ... 7.324890
55 30762 ... 7.184923
56 30763 ... 6.334022
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: msl0siip wandb: Agent Starting Run: j25gdui1 with config: batch_size: 5 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: j25gdui1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
67.53127729892731
The number of items in train is:
7
The loss for epoch 0
9.647325328418187
The running loss is:
8.399534657597542
The number of items in train is:
7
The loss for epoch 1
1.1999335225139345
The running loss is:
19.160128891468048
The number of items in train is:
7
The loss for epoch 2
2.737161270209721
The running loss is:
6.752385526895523
The number of items in train is:
7
The loss for epoch 3
0.9646265038422176
The running loss is:
10.865512549877167
The number of items in train is:
7
The loss for epoch 4
1.552216078553881
The running loss is:
8.864420533180237
The number of items in train is:
7
The loss for epoch 5
1.2663457904543196
The running loss is:
6.685234010219574
The number of items in train is:
7
The loss for epoch 6
0.9550334300313678
The running loss is:
5.997121214866638
The number of items in train is:
7
The loss for epoch 7
0.8567316021238055
The running loss is:
6.7596277594566345
The number of items in train is:
7
The loss for epoch 8
0.9656611084938049
The running loss is:
6.355755656957626
The number of items in train is:
7
The loss for epoch 9
0.9079650938510895
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.615163
48 30755 ... 9.802985
49 30756 ... 9.741320
50 30757 ... 9.703117
51 30758 ... 9.675394
52 30759 ... 9.667830
53 30760 ... 9.622468
54 30761 ... 9.616317
55 30762 ... 9.702218
56 30763 ... 9.624327
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: j25gdui1 wandb: Agent Starting Run: r2ml7nx8 with config: batch_size: 5 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: r2ml7nx8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
43.192112147808075
The number of items in train is:
7
The loss for epoch 0
6.170301735401154
The running loss is:
9.303201377391815
The number of items in train is:
7
The loss for epoch 1
1.3290287681988306
The running loss is:
15.101940214633942
The number of items in train is:
7
The loss for epoch 2
2.1574200306619917
The running loss is:
6.0063003450632095
The number of items in train is:
7
The loss for epoch 3
0.8580429064376014
The running loss is:
5.982577458024025
The number of items in train is:
7
The loss for epoch 4
0.8546539225748607
The running loss is:
6.759203761816025
The number of items in train is:
7
The loss for epoch 5
0.9656005374022892
The running loss is:
4.7542779594659805
The number of items in train is:
7
The loss for epoch 6
0.6791825656379972
The running loss is:
5.1109654903411865
The number of items in train is:
7
The loss for epoch 7
0.7301379271915981
The running loss is:
6.155610501766205
The number of items in train is:
7
The loss for epoch 8
0.8793729288237435
The running loss is:
4.374343603849411
The number of items in train is:
7
The loss for epoch 9
0.6249062291213444
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.731800
48 30755 ... 12.378132
49 30756 ... 11.761867
50 30757 ... 11.758492
51 30758 ... 11.453133
52 30759 ... 11.467014
53 30760 ... 11.495632
54 30761 ... 11.227182
55 30762 ... 11.354984
56 30763 ... 11.109964
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r2ml7nx8 wandb: Agent Starting Run: e5h01qn1 with config: batch_size: 5 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: e5h01qn1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
90.54687196016312
The number of items in train is:
7
The loss for epoch 0
12.935267422880445
The running loss is:
8.523807942867279
The number of items in train is:
7
The loss for epoch 1
1.21768684898104
The running loss is:
28.74505126476288
The number of items in train is:
7
The loss for epoch 2
4.1064358949661255
The running loss is:
11.200783550739288
The number of items in train is:
7
The loss for epoch 3
1.6001119358198983
The running loss is:
18.60291025042534
The number of items in train is:
7
The loss for epoch 4
2.6575586072036197
The running loss is:
29.870601654052734
The number of items in train is:
7
The loss for epoch 5
4.2672288077218195
The running loss is:
6.606499120593071
The number of items in train is:
7
The loss for epoch 6
0.943785588656153
The running loss is:
7.695777118206024
The number of items in train is:
7
The loss for epoch 7
1.0993967311722892
The running loss is:
6.955000162124634
The number of items in train is:
7
The loss for epoch 8
0.9935714517320905
The running loss is:
6.869924068450928
The number of items in train is:
7
The loss for epoch 9
0.9814177240644183
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.303787
48 30755 ... 7.303229
49 30756 ... 7.191536
50 30757 ... 7.176568
51 30758 ... 7.345643
52 30759 ... 7.316633
53 30760 ... 6.877242
54 30761 ... 6.870254
55 30762 ... 6.869648
56 30763 ... 7.055112
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: e5h01qn1 wandb: Agent Starting Run: 51pgmxyd with config: batch_size: 5 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 51pgmxyd
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.386345356702805
The number of items in train is:
7
The loss for epoch 0
1.1980493366718292
The running loss is:
5.305130660533905
The number of items in train is:
7
The loss for epoch 1
0.7578758086477008
The running loss is:
5.040349066257477
The number of items in train is:
7
The loss for epoch 2
0.720049866608211
The running loss is:
4.216301918029785
The number of items in train is:
7
The loss for epoch 3
0.6023288454328265
The running loss is:
4.013143762946129
The number of items in train is:
7
The loss for epoch 4
0.573306251849447
The running loss is:
4.111067958176136
The number of items in train is:
7
The loss for epoch 5
0.5872954225965908
The running loss is:
3.9650451093912125
The number of items in train is:
7
The loss for epoch 6
0.566435015627316
The running loss is:
3.8456651866436005
The number of items in train is:
7
The loss for epoch 7
0.5493807409490857
The running loss is:
3.4701995626091957
The number of items in train is:
7
The loss for epoch 8
0.49574279465845655
The running loss is:
3.600193105638027
The number of items in train is:
7
The loss for epoch 9
0.5143133008054325
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.014473
48 30755 ... 9.291738
49 30756 ... 10.382364
50 30757 ... 10.538802
51 30758 ... 10.259753
52 30759 ... 10.314054
53 30760 ... 9.395301
54 30761 ... 6.940967
55 30762 ... 7.337349
56 30763 ... 8.289805
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 51pgmxyd wandb: Agent Starting Run: gx05z4h0 with config: batch_size: 5 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: gx05z4h0
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.603733956813812
The number of items in train is:
7
The loss for epoch 0
1.2291048509734017
The running loss is:
5.768532857298851
The number of items in train is:
7
The loss for epoch 1
0.8240761224712644
The running loss is:
5.064010441303253
The number of items in train is:
7
The loss for epoch 2
0.7234300630433219
The running loss is:
4.223667658865452
The number of items in train is:
7
The loss for epoch 3
0.6033810941236359
The running loss is:
4.201617494225502
The number of items in train is:
7
The loss for epoch 4
0.6002310706036431
The running loss is:
4.033991657197475
The number of items in train is:
7
The loss for epoch 5
0.5762845224567822
The running loss is:
3.9912275075912476
The number of items in train is:
7
The loss for epoch 6
0.5701753582273211
The running loss is:
3.7576887756586075
The number of items in train is:
7
The loss for epoch 7
0.5368126822369439
The running loss is:
3.7496463656425476
The number of items in train is:
7
The loss for epoch 8
0.535663766520364
The running loss is:
3.759747177362442
The number of items in train is:
7
The loss for epoch 9
0.537106739623206
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 6.349306
48 30755 ... 6.258404
49 30756 ... 7.824118
50 30757 ... 7.399878
51 30758 ... 6.525862
52 30759 ... 6.587952
53 30760 ... 5.459343
54 30761 ... 1.024171
55 30762 ... 0.872965
56 30763 ... 1.004691
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gx05z4h0 wandb: Agent Starting Run: kua0nnmv with config: batch_size: 5 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: kua0nnmv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
8.157315015792847
The number of items in train is:
7
The loss for epoch 0
1.1653307165418352
The running loss is:
5.333026871085167
The number of items in train is:
7
The loss for epoch 1
0.7618609815835953
The running loss is:
4.923013836145401
The number of items in train is:
7
The loss for epoch 2
0.7032876908779144
The running loss is:
4.182542055845261
The number of items in train is:
7
The loss for epoch 3
0.5975060079778943
The running loss is:
3.877619966864586
The number of items in train is:
7
The loss for epoch 4
0.5539457095520837
The running loss is:
4.020708501338959
The number of items in train is:
7
The loss for epoch 5
0.5743869287627084
The running loss is:
3.8042884171009064
The number of items in train is:
7
The loss for epoch 6
0.543469773871558
The running loss is:
3.4904306679964066
The number of items in train is:
7
The loss for epoch 7
0.4986329525709152
The running loss is:
3.805373951792717
The number of items in train is:
7
The loss for epoch 8
0.5436248502561024
The running loss is:
3.578959584236145
The number of items in train is:
7
The loss for epoch 9
0.5112799406051636
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.411602
48 30755 ... 8.892941
49 30756 ... 7.403359
50 30757 ... 8.140916
51 30758 ... 9.077764
52 30759 ... 8.763077
53 30760 ... 7.171425
54 30761 ... 4.151009
55 30762 ... 4.456970
56 30763 ... 4.688587
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: kua0nnmv wandb: Agent Starting Run: 9nb3qucq with config: batch_size: 5 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 9nb3qucq
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.452470779418945
The number of items in train is:
7
The loss for epoch 0
1.3503529684884208
The running loss is:
8.573224395513535
The number of items in train is:
7
The loss for epoch 1
1.2247463422162193
The running loss is:
4.582139626145363
The number of items in train is:
7
The loss for epoch 2
0.6545913751636233
The running loss is:
4.537662208080292
The number of items in train is:
7
The loss for epoch 3
0.6482374582971845
The running loss is:
4.334219105541706
The number of items in train is:
7
The loss for epoch 4
0.6191741579345295
The running loss is:
3.8650491908192635
The number of items in train is:
7
The loss for epoch 5
0.5521498844027519
The running loss is:
4.087241470813751
The number of items in train is:
7
The loss for epoch 6
0.5838916386876788
The running loss is:
3.7244302183389664
The number of items in train is:
7
The loss for epoch 7
0.5320614597627095
The running loss is:
3.0911393761634827
The number of items in train is:
7
The loss for epoch 8
0.4415913394519261
The running loss is:
3.1409634202718735
The number of items in train is:
7
The loss for epoch 9
0.4487090600388391
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 8.991542
48 30755 ... 7.977815
49 30756 ... 11.552586
50 30757 ... 11.382884
51 30758 ... 9.104527
52 30759 ... 10.094441
53 30760 ... 10.687099
54 30761 ... 6.068766
55 30762 ... 6.669483
56 30763 ... 6.720552
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9nb3qucq wandb: Agent Starting Run: 2d77dsds with config: batch_size: 5 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 2d77dsds
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
10.341898024082184
The number of items in train is:
7
The loss for epoch 0
1.477414003440312
The running loss is:
9.692167803645134
The number of items in train is:
7
The loss for epoch 1
1.3845954005207335
The running loss is:
4.67776694893837
The number of items in train is:
7
The loss for epoch 2
0.66825242127691
The running loss is:
4.513872340321541
The number of items in train is:
7
The loss for epoch 3
0.6448389057602201
The running loss is:
4.335822895169258
The number of items in train is:
7
The loss for epoch 4
0.6194032707384655
The running loss is:
4.105712324380875
The number of items in train is:
7
The loss for epoch 5
0.5865303320544106
The running loss is:
4.100954279303551
The number of items in train is:
7
The loss for epoch 6
0.5858506113290787
The running loss is:
3.741816997528076
The number of items in train is:
7
The loss for epoch 7
0.5345452853611538
The running loss is:
3.687743529677391
The number of items in train is:
7
The loss for epoch 8
0.5268205042396273
The running loss is:
3.4706184715032578
The number of items in train is:
7
The loss for epoch 9
0.4958026387861797
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.107794
48 30755 ... 6.300855
49 30756 ... 8.690669
50 30757 ... 8.066691
51 30758 ... 6.239733
52 30759 ... 6.995705
53 30760 ... 7.065566
54 30761 ... 1.747199
55 30762 ... 1.620586
56 30763 ... 1.295900
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2d77dsds wandb: Agent Starting Run: kv3ugs2f with config: batch_size: 5 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: kv3ugs2f
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
9.399968564510345
The number of items in train is:
7
The loss for epoch 0
1.3428526520729065
The running loss is:
8.328093975782394
The number of items in train is:
7
The loss for epoch 1
1.1897277108260564
The running loss is:
4.483197212219238
The number of items in train is:
7
The loss for epoch 2
0.6404567446027484
The running loss is:
4.404286772012711
The number of items in train is:
7
The loss for epoch 3
0.6291838245732444
The running loss is:
4.283157721161842
The number of items in train is:
7
The loss for epoch 4
0.6118796744516918
The running loss is:
4.080961152911186
The number of items in train is:
7
The loss for epoch 5
0.5829944504158837
The running loss is:
3.922510102391243
The number of items in train is:
7
The loss for epoch 6
0.5603585860558918
The running loss is:
3.649494081735611
The number of items in train is:
7
The loss for epoch 7
0.5213562973908016
The running loss is:
4.0167796313762665
The number of items in train is:
7
The loss for epoch 8
0.5738256616251809
The running loss is:
3.7649319767951965
The number of items in train is:
7
The loss for epoch 9
0.5378474252564567
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.075241
48 30755 ... 9.679935
49 30756 ... 7.270753
50 30757 ... 8.642411
51 30758 ... 9.739583
52 30759 ... 9.584579
53 30760 ... 8.186583
54 30761 ... 6.058244
55 30762 ... 6.880507
56 30763 ... 6.824042
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: kv3ugs2f wandb: Agent Starting Run: s1dkmad8 with config: batch_size: 5 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: s1dkmad8
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.163711488246918
The number of items in train is:
7
The loss for epoch 0
2.0233873554638455
The running loss is:
17.172690749168396
The number of items in train is:
7
The loss for epoch 1
2.453241535595485
The running loss is:
7.470961958169937
The number of items in train is:
7
The loss for epoch 2
1.0672802797385625
The running loss is:
7.662623822689056
The number of items in train is:
7
The loss for epoch 3
1.0946605460984367
The running loss is:
4.7404936999082565
The number of items in train is:
7
The loss for epoch 4
0.6772133857011795
The running loss is:
4.622741907835007
The number of items in train is:
7
The loss for epoch 5
0.6603917011192867
The running loss is:
4.599970698356628
The number of items in train is:
7
The loss for epoch 6
0.6571386711938041
The running loss is:
4.118006765842438
The number of items in train is:
7
The loss for epoch 7
0.588286680834634
The running loss is:
3.2050129547715187
The number of items in train is:
7
The loss for epoch 8
0.4578589935387884
The running loss is:
3.9961725622415543
The number of items in train is:
7
The loss for epoch 9
0.5708817946059364
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.272706
48 30755 ... 10.734841
49 30756 ... 9.385545
50 30757 ... 11.560097
51 30758 ... 11.946331
52 30759 ... 12.485663
53 30760 ... 14.132852
54 30761 ... 12.056442
55 30762 ... 12.276989
56 30763 ... 12.371525
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: s1dkmad8 wandb: Agent Starting Run: ftcthxo3 with config: batch_size: 5 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ftcthxo3
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.386868000030518
The number of items in train is:
7
The loss for epoch 0
2.1981240000043596
The running loss is:
20.018226504325867
The number of items in train is:
7
The loss for epoch 1
2.8597466434751238
The running loss is:
8.846402645111084
The number of items in train is:
7
The loss for epoch 2
1.2637718064444405
The running loss is:
8.188300907611847
The number of items in train is:
7
The loss for epoch 3
1.1697572725159782
The running loss is:
5.718660831451416
The number of items in train is:
7
The loss for epoch 4
0.8169515473502023
The running loss is:
4.988060265779495
The number of items in train is:
7
The loss for epoch 5
0.7125800379684993
The running loss is:
4.967563331127167
The number of items in train is:
7
The loss for epoch 6
0.7096519044467381
The running loss is:
4.434747152030468
The number of items in train is:
7
The loss for epoch 7
0.633535307432924
The running loss is:
4.422097831964493
The number of items in train is:
7
The loss for epoch 8
0.6317282617092133
The running loss is:
4.5411578714847565
The number of items in train is:
7
The loss for epoch 9
0.6487368387835366
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 7.052814
48 30755 ... 7.284422
49 30756 ... 7.511244
50 30757 ... 8.769793
51 30758 ... 9.044814
52 30759 ... 9.060470
53 30760 ... 8.379431
54 30761 ... 7.380647
55 30762 ... 8.095577
56 30763 ... 8.026391
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ftcthxo3 wandb: Agent Starting Run: nfbfbmg4 with config: batch_size: 5 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: nfbfbmg4
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.547432959079742
The number of items in train is:
7
The loss for epoch 0
1.9353475655828203
The running loss is:
16.23163253068924
The number of items in train is:
7
The loss for epoch 1
2.3188046472413197
The running loss is:
6.393091231584549
The number of items in train is:
7
The loss for epoch 2
0.9132987473692212
The running loss is:
6.579031050205231
The number of items in train is:
7
The loss for epoch 3
0.9398615786007473
The running loss is:
5.11293551325798
The number of items in train is:
7
The loss for epoch 4
0.7304193590368543
The running loss is:
4.956169933080673
The number of items in train is:
7
The loss for epoch 5
0.7080242761543819
The running loss is:
4.477589040994644
The number of items in train is:
7
The loss for epoch 6
0.6396555772849492
The running loss is:
3.994989514350891
The number of items in train is:
7
The loss for epoch 7
0.570712787764413
The running loss is:
3.823404371738434
The number of items in train is:
7
The loss for epoch 8
0.5462006245340619
The running loss is:
4.004239939153194
The number of items in train is:
7
The loss for epoch 9
0.5720342770218849
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 10.857925
48 30755 ... 8.150393
49 30756 ... 0.958358
50 30757 ... 5.166536
51 30758 ... 7.655322
52 30759 ... 9.013206
53 30760 ... 7.398972
54 30761 ... 4.278189
55 30762 ... 6.075479
56 30763 ... 8.513471
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nfbfbmg4 wandb: Agent Starting Run: cbzag821 with config: batch_size: 5 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cbzag821
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
67.39246386289597
The number of items in train is:
7
The loss for epoch 0
9.627494837556567
The running loss is:
9.074194252490997
The number of items in train is:
7
The loss for epoch 1
1.296313464641571
The running loss is:
10.388038083910942
The number of items in train is:
7
The loss for epoch 2
1.484005440558706
The running loss is:
10.391907647252083
The number of items in train is:
7
The loss for epoch 3
1.4845582353217261
The running loss is:
5.420821771025658
The number of items in train is:
7
The loss for epoch 4
0.7744031101465225
The running loss is:
5.024749353528023
The number of items in train is:
7
The loss for epoch 5
0.7178213362182889
The running loss is:
4.97475703060627
The number of items in train is:
7
The loss for epoch 6
0.7106795758008957
The running loss is:
4.761862933635712
The number of items in train is:
7
The loss for epoch 7
0.6802661333765302
The running loss is:
4.68121574819088
The number of items in train is:
7
The loss for epoch 8
0.6687451068844114
The running loss is:
5.033755451440811
The number of items in train is:
7
The loss for epoch 9
0.7191079216344016
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 12.181989
48 30755 ... 11.518135
49 30756 ... 11.462760
50 30757 ... 11.136217
51 30758 ... 10.741853
52 30759 ... 10.793540
53 30760 ... 12.484796
54 30761 ... 9.014488
55 30762 ... 9.239480
56 30763 ... 8.877860
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cbzag821 wandb: Agent Starting Run: bdyp6lnn with config: batch_size: 5 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: bdyp6lnn
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
67.81293976306915
The number of items in train is:
7
The loss for epoch 0
9.687562823295593
The running loss is:
9.99773907661438
The number of items in train is:
7
The loss for epoch 1
1.42824843951634
The running loss is:
15.24121206998825
The number of items in train is:
7
The loss for epoch 2
2.1773160099983215
The running loss is:
7.703388452529907
The number of items in train is:
7
The loss for epoch 3
1.1004840646471297
The running loss is:
7.230520695447922
The number of items in train is:
7
The loss for epoch 4
1.0329315279211317
The running loss is:
5.7543908059597015
The number of items in train is:
7
The loss for epoch 5
0.8220558294228145
The running loss is:
6.086855813860893
The number of items in train is:
7
The loss for epoch 6
0.8695508305515561
The running loss is:
6.224896281957626
The number of items in train is:
7
The loss for epoch 7
0.8892708974225181
The running loss is:
5.51524843275547
The number of items in train is:
7
The loss for epoch 8
0.7878926332507815
The running loss is:
5.073978707194328
The number of items in train is:
7
The loss for epoch 9
0.7248541010277612
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.048117
48 30755 ... 10.169812
49 30756 ... 4.386463
50 30757 ... 8.051113
51 30758 ... 12.294018
52 30759 ... 9.637958
53 30760 ... 7.130473
54 30761 ... 8.857204
55 30762 ... 9.039351
56 30763 ... 8.967212
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bdyp6lnn wandb: Agent Starting Run: pml2qhh1 with config: batch_size: 5 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: pml2qhh1
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 5
dataset_params:
desc: null
value:
batch_size: 5
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Douglas County.csv
train_end: 45
training_path: Colorado_Douglas County.csv
valid_end: 58
valid_start: 46
validation_path: Colorado_Douglas County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Douglas County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Douglas County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 5
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
56.04367220401764
The number of items in train is:
7
The loss for epoch 0
8.006238886288234
The running loss is:
10.853782594203949
The number of items in train is:
7
The loss for epoch 1
1.550540370600564
The running loss is:
13.280152201652527
The number of items in train is:
7
The loss for epoch 2
1.8971646002360754
The running loss is:
7.083515048027039
The number of items in train is:
7
The loss for epoch 3
1.01193072114672
The running loss is:
5.93258336186409
The number of items in train is:
7
The loss for epoch 4
0.8475119088377271
The running loss is:
5.776451528072357
The number of items in train is:
7
The loss for epoch 5
0.8252073611531939
The running loss is:
5.619628816843033
The number of items in train is:
7
The loss for epoch 6
0.8028041166918618
The running loss is:
6.114215791225433
The number of items in train is:
7
The loss for epoch 7
0.8734593987464905
The running loss is:
5.572997599840164
The number of items in train is:
7
The loss for epoch 8
0.7961425142628806
The running loss is:
5.289255976676941
The number of items in train is:
7
The loss for epoch 9
0.7556079966681344
interpolate should be below
Now loading and scaling Colorado_Douglas County.csv
CSV Path below
Colorado_Douglas County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30744 ... 0.000000
38 30745 ... 0.000000
39 30746 ... 0.000000
40 30747 ... 0.000000
41 30748 ... 0.000000
42 30749 ... 0.000000
43 30750 ... 0.000000
44 30751 ... 0.000000
45 30752 ... 0.000000
46 30753 ... 0.000000
47 30754 ... 9.162136
48 30755 ... 9.868551
49 30756 ... 8.345331
50 30757 ... 9.502460
51 30758 ... 9.210078
52 30759 ... 9.329942
53 30760 ... 9.226681
54 30761 ... 9.408814
55 30762 ... 9.454621
56 30763 ... 9.417312
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pml2qhh1 Colorado_Eagle County Create sweep with ID: izk6f8yh Sweep URL: https://app.wandb.ai/igodfried/covid-forecast/sweeps/izk6f8yh
/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy del sys.path[0] /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:15: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy from ipykernel import kernelapp as app /usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:18: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
wandb: Agent Starting Run: 3md9qfjj with config: batch_size: 2 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3md9qfjj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
24.994310602545738
The number of items in train is:
21
The loss for epoch 0
1.1902052667878924
The running loss is:
31.338150784373283
The number of items in train is:
21
The loss for epoch 1
1.492292894493966
The running loss is:
23.230982203036547
The number of items in train is:
21
The loss for epoch 2
1.106237247763645
The running loss is:
22.80511908652261
The number of items in train is:
21
The loss for epoch 3
1.0859580517391718
The running loss is:
21.484980678884313
The number of items in train is:
21
The loss for epoch 4
1.0230943180421102
The running loss is:
22.467626813799143
The number of items in train is:
21
The loss for epoch 5
1.0698869911332924
The running loss is:
22.521564692491665
The number of items in train is:
21
The loss for epoch 6
1.0724554615472222
The running loss is:
21.74733708333224
The number of items in train is:
21
The loss for epoch 7
1.0355874801586782
The running loss is:
21.972762659657747
The number of items in train is:
21
The loss for epoch 8
1.0463220314122736
The running loss is:
21.711856733076274
The number of items in train is:
21
The loss for epoch 9
1.0338979396702987
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 9.320036
47 30819 ... 10.372439
48 30820 ... 10.091675
49 30821 ... 9.566354
50 30822 ... 8.996174
51 30823 ... 8.417763
52 30824 ... 7.837843
53 30825 ... 10.574365
54 30826 ... 10.602532
55 30827 ... 10.133883
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3md9qfjj wandb: Agent Starting Run: jedyojoo with config: batch_size: 2 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: jedyojoo
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
30.50091978907585
The number of items in train is:
20
The loss for epoch 0
1.5250459894537927
The running loss is:
35.48609974980354
The number of items in train is:
20
The loss for epoch 1
1.774304987490177
The running loss is:
28.23683187365532
The number of items in train is:
20
The loss for epoch 2
1.411841593682766
The running loss is:
28.132872357964516
The number of items in train is:
20
The loss for epoch 3
1.4066436178982258
The running loss is:
27.100994661450386
The number of items in train is:
20
The loss for epoch 4
1.3550497330725193
The running loss is:
26.87871690094471
The number of items in train is:
20
The loss for epoch 5
1.3439358450472354
The running loss is:
26.260645911097527
The number of items in train is:
20
The loss for epoch 6
1.3130322955548763
The running loss is:
26.076900631189346
The number of items in train is:
20
The loss for epoch 7
1.3038450315594674
The running loss is:
25.671136647462845
The number of items in train is:
20
The loss for epoch 8
1.2835568323731423
The running loss is:
25.587705582380295
The number of items in train is:
20
The loss for epoch 9
1.2793852791190148
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 16.139271
47 30819 ... 18.936136
48 30820 ... 18.685638
49 30821 ... 17.682741
50 30822 ... 16.494076
51 30823 ... 15.259542
52 30824 ... 14.013685
53 30825 ... 19.352375
54 30826 ... 19.729458
55 30827 ... 18.881512
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jedyojoo wandb: Agent Starting Run: ha9jzb1p with config: batch_size: 2 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ha9jzb1p
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
30.087819531559944
The number of items in train is:
20
The loss for epoch 0
1.5043909765779973
The running loss is:
38.96592804789543
The number of items in train is:
20
The loss for epoch 1
1.9482964023947715
The running loss is:
29.03825269639492
The number of items in train is:
20
The loss for epoch 2
1.451912634819746
The running loss is:
27.82487864047289
The number of items in train is:
20
The loss for epoch 3
1.3912439320236445
The running loss is:
26.97020795941353
The number of items in train is:
20
The loss for epoch 4
1.3485103979706765
The running loss is:
26.578218407928944
The number of items in train is:
20
The loss for epoch 5
1.328910920396447
The running loss is:
26.662743851542473
The number of items in train is:
20
The loss for epoch 6
1.3331371925771236
The running loss is:
26.146022632718086
The number of items in train is:
20
The loss for epoch 7
1.3073011316359042
The running loss is:
25.915332719683647
The number of items in train is:
20
The loss for epoch 8
1.2957666359841824
The running loss is:
25.717713937163353
The number of items in train is:
20
The loss for epoch 9
1.2858856968581676
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 1.090912
47 30819 Eagle County, Colorado, United States ... 47 0.957550
48 30820 Eagle County, Colorado, United States ... 48 0.796825
49 30821 Eagle County, Colorado, United States ... 49 0.632762
50 30822 Eagle County, Colorado, United States ... 50 0.468292
51 30823 Eagle County, Colorado, United States ... 51 0.303773
52 30824 Eagle County, Colorado, United States ... 52 0.139247
53 30825 Eagle County, Colorado, United States ... 53 0.985899
54 30826 Eagle County, Colorado, United States ... 54 0.944738
55 30827 Eagle County, Colorado, United States ... 55 0.795262
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ha9jzb1p wandb: Agent Starting Run: guveixrq with config: batch_size: 2 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: guveixrq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.42800808791071
The number of items in train is:
21
The loss for epoch 0
1.0203813375195576
The running loss is:
33.97634669393301
The number of items in train is:
21
The loss for epoch 1
1.617921271139667
The running loss is:
32.660160295665264
The number of items in train is:
21
The loss for epoch 2
1.5552457283650125
The running loss is:
26.03447231533937
The number of items in train is:
21
The loss for epoch 3
1.2397367769209224
The running loss is:
22.19169175659772
The number of items in train is:
21
The loss for epoch 4
1.0567472265046534
The running loss is:
22.451023087836802
The number of items in train is:
21
The loss for epoch 5
1.0690963375160383
The running loss is:
21.957806181162596
The number of items in train is:
21
The loss for epoch 6
1.0456098181505997
The running loss is:
22.098417993169278
The number of items in train is:
21
The loss for epoch 7
1.0523056187223465
The running loss is:
21.93328778957948
The number of items in train is:
21
The loss for epoch 8
1.044442275694261
The running loss is:
21.70377436140552
The number of items in train is:
21
The loss for epoch 9
1.0335130648288344
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 9.462493
47 30819 ... 10.482204
48 30820 ... 10.290704
49 30821 ... 9.902096
50 30822 ... 9.481412
51 30823 ... 9.055507
52 30824 ... 8.628753
53 30825 ... 10.703968
54 30826 ... 10.684237
55 30827 ... 10.323583
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: guveixrq wandb: Agent Starting Run: m6nbqbmq with config: batch_size: 2 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: m6nbqbmq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
26.785726577043533
The number of items in train is:
20
The loss for epoch 0
1.3392863288521766
The running loss is:
39.627033829689026
The number of items in train is:
20
The loss for epoch 1
1.9813516914844513
The running loss is:
33.684926599264145
The number of items in train is:
20
The loss for epoch 2
1.6842463299632073
The running loss is:
27.56533844769001
The number of items in train is:
20
The loss for epoch 3
1.3782669223845005
The running loss is:
26.230642080307007
The number of items in train is:
20
The loss for epoch 4
1.3115321040153503
The running loss is:
25.43548308312893
The number of items in train is:
20
The loss for epoch 5
1.2717741541564465
The running loss is:
24.62746013700962
The number of items in train is:
20
The loss for epoch 6
1.2313730068504811
The running loss is:
24.4681788533926
The number of items in train is:
20
The loss for epoch 7
1.22340894266963
The running loss is:
23.801658302545547
The number of items in train is:
20
The loss for epoch 8
1.1900829151272774
The running loss is:
23.667554318904877
The number of items in train is:
20
The loss for epoch 9
1.1833777159452439
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 15.175662
47 30819 ... 17.513287
48 30820 ... 17.114977
49 30821 ... 16.084354
50 30822 ... 14.907595
51 30823 ... 13.697062
52 30824 ... 12.478723
53 30825 ... 17.828556
54 30826 ... 18.126408
55 30827 ... 17.256680
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: m6nbqbmq wandb: Agent Starting Run: 3ff31iqc with config: batch_size: 2 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3ff31iqc
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
26.19386227428913
The number of items in train is:
20
The loss for epoch 0
1.3096931137144565
The running loss is:
42.867518559098244
The number of items in train is:
20
The loss for epoch 1
2.1433759279549123
The running loss is:
34.7266606092453
The number of items in train is:
20
The loss for epoch 2
1.736333030462265
The running loss is:
27.950618222355843
The number of items in train is:
20
The loss for epoch 3
1.397530911117792
The running loss is:
26.19993595778942
The number of items in train is:
20
The loss for epoch 4
1.309996797889471
The running loss is:
25.272186301648617
The number of items in train is:
20
The loss for epoch 5
1.2636093150824308
The running loss is:
25.510257616639137
The number of items in train is:
20
The loss for epoch 6
1.275512880831957
The running loss is:
24.659199744462967
The number of items in train is:
20
The loss for epoch 7
1.2329599872231483
The running loss is:
24.421232596039772
The number of items in train is:
20
The loss for epoch 8
1.2210616298019885
The running loss is:
24.122598320245743
The number of items in train is:
20
The loss for epoch 9
1.2061299160122871
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.737662
47 30819 Eagle County, Colorado, United States ... 47 2.728444
48 30820 Eagle County, Colorado, United States ... 48 2.546297
49 30821 Eagle County, Colorado, United States ... 49 2.347031
50 30822 Eagle County, Colorado, United States ... 50 2.146070
51 30823 Eagle County, Colorado, United States ... 51 1.944941
52 30824 Eagle County, Colorado, United States ... 52 1.743796
53 30825 Eagle County, Colorado, United States ... 53 2.811293
54 30826 Eagle County, Colorado, United States ... 54 2.735733
55 30827 Eagle County, Colorado, United States ... 55 2.547019
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3ff31iqc wandb: Agent Starting Run: jbvxtyo1 with config: batch_size: 2 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: jbvxtyo1
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.431543273851275
The number of items in train is:
21
The loss for epoch 0
1.3538830130405368
The running loss is:
24.86347783706151
The number of items in train is:
21
The loss for epoch 1
1.183975135098167
The running loss is:
27.93423504382372
The number of items in train is:
21
The loss for epoch 2
1.3302016687535105
The running loss is:
35.81483320891857
The number of items in train is:
21
The loss for epoch 3
1.7054682480437415
The running loss is:
36.937019128352404
The number of items in train is:
21
The loss for epoch 4
1.7589056727786858
The running loss is:
32.27701100707054
The number of items in train is:
21
The loss for epoch 5
1.5370005241462164
The running loss is:
27.327979074791074
The number of items in train is:
21
The loss for epoch 6
1.301332336894813
The running loss is:
22.494237068109214
The number of items in train is:
21
The loss for epoch 7
1.0711541461004388
The running loss is:
22.358194688451476
The number of items in train is:
21
The loss for epoch 8
1.0646759375453083
The running loss is:
21.776387142948806
The number of items in train is:
21
The loss for epoch 9
1.0369708163308955
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 9.246925
47 30819 ... 10.244971
48 30820 ... 10.100391
49 30821 ... 9.775701
50 30822 ... 9.422621
51 30823 ... 9.065064
52 30824 ... 8.706804
53 30825 ... 10.461733
54 30826 ... 10.436459
55 30827 ... 10.130575
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jbvxtyo1 wandb: Agent Starting Run: xrtaxjua with config: batch_size: 2 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: xrtaxjua
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
29.28187485039234
The number of items in train is:
20
The loss for epoch 0
1.464093742519617
The running loss is:
33.413817927241325
The number of items in train is:
20
The loss for epoch 1
1.6706908963620664
The running loss is:
32.58062018454075
The number of items in train is:
20
The loss for epoch 2
1.6290310092270375
The running loss is:
29.036787658929825
The number of items in train is:
20
The loss for epoch 3
1.4518393829464913
The running loss is:
33.49508434534073
The number of items in train is:
20
The loss for epoch 4
1.6747542172670364
The running loss is:
31.11882695555687
The number of items in train is:
20
The loss for epoch 5
1.5559413477778434
The running loss is:
27.91164129972458
The number of items in train is:
20
The loss for epoch 6
1.395582064986229
The running loss is:
24.096679963171482
The number of items in train is:
20
The loss for epoch 7
1.204833998158574
The running loss is:
22.1046689376235
The number of items in train is:
20
The loss for epoch 8
1.105233446881175
The running loss is:
22.059589117765427
The number of items in train is:
20
The loss for epoch 9
1.1029794558882713
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 13.587997
47 30819 ... 15.503042
48 30820 ... 15.083281
49 30821 ... 14.152758
50 30822 ... 13.110500
51 30823 ... 12.043802
52 30824 ... 10.971756
53 30825 ... 15.769411
54 30826 ... 15.980247
55 30827 ... 15.187674
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xrtaxjua wandb: Agent Starting Run: 0v9zhmnb with config: batch_size: 2 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 0v9zhmnb
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
31.78796711564064
The number of items in train is:
20
The loss for epoch 0
1.589398355782032
The running loss is:
33.291881904006004
The number of items in train is:
20
The loss for epoch 1
1.6645940952003002
The running loss is:
32.06749828159809
The number of items in train is:
20
The loss for epoch 2
1.6033749140799045
The running loss is:
28.367174096405506
The number of items in train is:
20
The loss for epoch 3
1.4183587048202753
The running loss is:
33.985155656933784
The number of items in train is:
20
The loss for epoch 4
1.6992577828466893
The running loss is:
34.81114760041237
The number of items in train is:
20
The loss for epoch 5
1.7405573800206184
The running loss is:
27.80887019634247
The number of items in train is:
20
The loss for epoch 6
1.3904435098171235
The running loss is:
39.12357208132744
The number of items in train is:
20
The loss for epoch 7
1.956178604066372
The running loss is:
27.10132560878992
The number of items in train is:
20
The loss for epoch 8
1.355066280439496
The running loss is:
25.432943373918533
The number of items in train is:
20
The loss for epoch 9
1.2716471686959268
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.820832
47 30819 Eagle County, Colorado, United States ... 47 6.710801
48 30820 Eagle County, Colorado, United States ... 48 6.761901
49 30821 Eagle County, Colorado, United States ... 49 6.808624
50 30822 Eagle County, Colorado, United States ... 50 6.855465
51 30823 Eagle County, Colorado, United States ... 51 6.902304
52 30824 Eagle County, Colorado, United States ... 52 6.949142
53 30825 Eagle County, Colorado, United States ... 53 6.659204
54 30826 Eagle County, Colorado, United States ... 54 6.715192
55 30827 Eagle County, Colorado, United States ... 55 6.761782
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0v9zhmnb wandb: Agent Starting Run: lx2yib44 with config: batch_size: 2 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: lx2yib44
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
48.09504758147523
The number of items in train is:
21
The loss for epoch 0
2.29024036102263
The running loss is:
22.480513457208872
The number of items in train is:
21
The loss for epoch 1
1.0705006408194702
The running loss is:
41.80015133321285
The number of items in train is:
21
The loss for epoch 2
1.9904833968196596
The running loss is:
40.18148048967123
The number of items in train is:
21
The loss for epoch 3
1.913403832841487
The running loss is:
27.97383632697165
The number of items in train is:
21
The loss for epoch 4
1.3320874441415071
The running loss is:
31.400769567117095
The number of items in train is:
21
The loss for epoch 5
1.4952747412912903
The running loss is:
32.24099379777908
The number of items in train is:
21
The loss for epoch 6
1.5352854189418612
The running loss is:
24.44546188414097
The number of items in train is:
21
The loss for epoch 7
1.1640696135305224
The running loss is:
22.073538778349757
The number of items in train is:
21
The loss for epoch 8
1.0511208942071313
The running loss is:
21.668216380290687
The number of items in train is:
21
The loss for epoch 9
1.0318198276328898
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 10.249763
47 30819 ... 10.780683
48 30820 ... 10.627822
49 30821 ... 10.421335
50 30822 ... 10.210644
51 30823 ... 9.999621
52 30824 ... 9.788574
53 30825 ... 10.939012
54 30826 ... 10.834738
55 30827 ... 10.632061
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lx2yib44 wandb: Agent Starting Run: rpc2w1fl with config: batch_size: 2 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: rpc2w1fl
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
57.4059556722641
The number of items in train is:
20
The loss for epoch 0
2.870297783613205
The running loss is:
40.249125987291336
The number of items in train is:
20
The loss for epoch 1
2.0124562993645667
The running loss is:
27.546720668673515
The number of items in train is:
20
The loss for epoch 2
1.3773360334336757
The running loss is:
39.57624187320471
The number of items in train is:
20
The loss for epoch 3
1.9788120936602354
The running loss is:
26.22379694879055
The number of items in train is:
20
The loss for epoch 4
1.3111898474395276
The running loss is:
26.18321020901203
The number of items in train is:
20
The loss for epoch 5
1.3091605104506017
The running loss is:
22.03504551947117
The number of items in train is:
20
The loss for epoch 6
1.1017522759735585
The running loss is:
21.372891955077648
The number of items in train is:
20
The loss for epoch 7
1.0686445977538823
The running loss is:
20.670882388949394
The number of items in train is:
20
The loss for epoch 8
1.0335441194474697
The running loss is:
20.363346807658672
The number of items in train is:
20
The loss for epoch 9
1.0181673403829337
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 11.920742
47 30819 ... 13.835093
48 30820 ... 13.454808
49 30821 ... 12.489900
50 30822 ... 11.376041
51 30823 ... 10.224234
52 30824 ... 9.062757
53 30825 ... 13.974960
54 30826 ... 14.358463
55 30827 ... 13.588152
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rpc2w1fl wandb: Agent Starting Run: 71uwwud0 with config: batch_size: 2 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 71uwwud0
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
65.11059759557247
The number of items in train is:
20
The loss for epoch 0
3.2555298797786234
The running loss is:
28.523036420345306
The number of items in train is:
20
The loss for epoch 1
1.4261518210172652
The running loss is:
33.405703380703926
The number of items in train is:
20
The loss for epoch 2
1.6702851690351963
The running loss is:
24.232465356588364
The number of items in train is:
20
The loss for epoch 3
1.211623267829418
The running loss is:
34.218861397355795
The number of items in train is:
20
The loss for epoch 4
1.7109430698677897
The running loss is:
25.364171378314495
The number of items in train is:
20
The loss for epoch 5
1.2682085689157248
The running loss is:
36.61564963310957
The number of items in train is:
20
The loss for epoch 6
1.8307824816554785
The running loss is:
22.46705986559391
The number of items in train is:
20
The loss for epoch 7
1.1233529932796955
The running loss is:
27.24634464085102
The number of items in train is:
20
The loss for epoch 8
1.362317232042551
The running loss is:
23.25190670788288
The number of items in train is:
20
The loss for epoch 9
1.162595335394144
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 10.090479
47 30819 ... 11.080034
48 30820 ... 11.165306
49 30821 ... 11.149635
50 30822 ... 11.122695
51 30823 ... 11.094498
52 30824 ... 11.066160
53 30825 ... 11.214138
54 30826 ... 11.205466
55 30827 ... 11.179308
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 71uwwud0 wandb: Agent Starting Run: 3rvnt4hr with config: batch_size: 2 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3rvnt4hr
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.894857458304614
The number of items in train is:
20
The loss for epoch 0
1.1447428729152307
The running loss is:
32.818418147042394
The number of items in train is:
20
The loss for epoch 1
1.6409209073521196
The running loss is:
22.32921899855137
The number of items in train is:
20
The loss for epoch 2
1.1164609499275684
The running loss is:
19.03028530627489
The number of items in train is:
20
The loss for epoch 3
0.9515142653137445
The running loss is:
17.922462274320424
The number of items in train is:
20
The loss for epoch 4
0.8961231137160212
The running loss is:
16.806524269282818
The number of items in train is:
20
The loss for epoch 5
0.8403262134641409
The running loss is:
17.183919344097376
The number of items in train is:
20
The loss for epoch 6
0.8591959672048688
The running loss is:
16.498050395399332
The number of items in train is:
20
The loss for epoch 7
0.8249025197699666
The running loss is:
16.132734179496765
The number of items in train is:
20
The loss for epoch 8
0.8066367089748383
The running loss is:
16.202645121142268
The number of items in train is:
20
The loss for epoch 9
0.8101322560571134
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.556585
47 30819 ... 9.645228
48 30820 ... 11.145407
49 30821 ... 10.554946
50 30822 ... 9.139843
51 30823 ... 7.114215
52 30824 ... 4.747508
53 30825 ... 5.182785
54 30826 ... 11.098437
55 30827 ... 11.842958
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3rvnt4hr wandb: Agent Starting Run: m31yaxhk with config: batch_size: 2 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: m31yaxhk
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.808099165558815
The number of items in train is:
20
The loss for epoch 0
1.1404049582779408
The running loss is:
32.54965762794018
The number of items in train is:
20
The loss for epoch 1
1.6274828813970088
The running loss is:
23.487822026014328
The number of items in train is:
20
The loss for epoch 2
1.1743911013007164
The running loss is:
21.436568334698677
The number of items in train is:
20
The loss for epoch 3
1.071828416734934
The running loss is:
20.173894971609116
The number of items in train is:
20
The loss for epoch 4
1.0086947485804558
The running loss is:
19.244802474975586
The number of items in train is:
20
The loss for epoch 5
0.9622401237487793
The running loss is:
19.414657458662987
The number of items in train is:
20
The loss for epoch 6
0.9707328729331494
The running loss is:
18.745623260736465
The number of items in train is:
20
The loss for epoch 7
0.9372811630368233
The running loss is:
18.42511696368456
The number of items in train is:
20
The loss for epoch 8
0.9212558481842279
The running loss is:
17.993324242532253
The number of items in train is:
20
The loss for epoch 9
0.8996662121266127
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 1.286533
47 30819 Eagle County, Colorado, United States ... 47 7.902304
48 30820 Eagle County, Colorado, United States ... 48 8.358495
49 30821 Eagle County, Colorado, United States ... 49 7.713692
50 30822 Eagle County, Colorado, United States ... 50 5.313522
51 30823 Eagle County, Colorado, United States ... 51 2.300918
52 30824 Eagle County, Colorado, United States ... 52 -1.653545
53 30825 Eagle County, Colorado, United States ... 53 -0.715274
54 30826 Eagle County, Colorado, United States ... 54 6.250890
55 30827 Eagle County, Colorado, United States ... 55 7.206236
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: m31yaxhk wandb: Agent Starting Run: 5wjn16ui with config: batch_size: 2 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 5wjn16ui
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.883200803771615
The number of items in train is:
19
The loss for epoch 0
1.2570105686195587
The running loss is:
29.3741205483675
The number of items in train is:
19
The loss for epoch 1
1.5460063446509211
The running loss is:
22.550002455711365
The number of items in train is:
19
The loss for epoch 2
1.1868422345111245
The running loss is:
21.398591592907906
The number of items in train is:
19
The loss for epoch 3
1.1262416627846266
The running loss is:
20.165410295128822
The number of items in train is:
19
The loss for epoch 4
1.0613373839541485
The running loss is:
19.983036041259766
The number of items in train is:
19
The loss for epoch 5
1.0517387390136719
The running loss is:
19.7033898383379
The number of items in train is:
19
The loss for epoch 6
1.0370205178072578
The running loss is:
20.062028273940086
The number of items in train is:
19
The loss for epoch 7
1.055896224944215
The running loss is:
19.604557141661644
The number of items in train is:
19
The loss for epoch 8
1.0318187969295602
The running loss is:
19.286929190158844
The number of items in train is:
19
The loss for epoch 9
1.0151015363241498
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.172461
47 30819 ... 9.464293
48 30820 ... 10.587953
49 30821 ... 11.135654
50 30822 ... 10.621194
51 30823 ... 9.779943
52 30824 ... 8.561573
53 30825 ... 7.978648
54 30826 ... 12.218817
55 30827 ... 12.135553
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5wjn16ui wandb: Agent Starting Run: qdw71sjg with config: batch_size: 2 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: qdw71sjg
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.258419326506555
The number of items in train is:
20
The loss for epoch 0
0.9629209663253278
The running loss is:
29.041860688477755
The number of items in train is:
20
The loss for epoch 1
1.4520930344238878
The running loss is:
28.806721806526184
The number of items in train is:
20
The loss for epoch 2
1.4403360903263092
The running loss is:
22.60324565321207
The number of items in train is:
20
The loss for epoch 3
1.1301622826606035
The running loss is:
17.439734483137727
The number of items in train is:
20
The loss for epoch 4
0.8719867241568864
The running loss is:
17.076150111854076
The number of items in train is:
20
The loss for epoch 5
0.8538075055927038
The running loss is:
16.122335635125637
The number of items in train is:
20
The loss for epoch 6
0.8061167817562819
The running loss is:
16.304215546697378
The number of items in train is:
20
The loss for epoch 7
0.8152107773348689
The running loss is:
15.875915486365557
The number of items in train is:
20
The loss for epoch 8
0.7937957743182779
The running loss is:
15.645636413246393
The number of items in train is:
20
The loss for epoch 9
0.7822818206623197
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.874076
47 30819 ... 10.008490
48 30820 ... 11.268057
49 30821 ... 10.409958
50 30822 ... 9.094545
51 30823 ... 7.289007
52 30824 ... 5.318330
53 30825 ... 5.599030
54 30826 ... 11.190384
55 30827 ... 11.729114
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qdw71sjg wandb: Agent Starting Run: txdsr8qd with config: batch_size: 2 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: txdsr8qd
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.926999300718307
The number of items in train is:
20
The loss for epoch 0
1.0963499650359154
The running loss is:
33.55658884346485
The number of items in train is:
20
The loss for epoch 1
1.6778294421732425
The running loss is:
27.994558811187744
The number of items in train is:
20
The loss for epoch 2
1.3997279405593872
The running loss is:
22.162001058459282
The number of items in train is:
20
The loss for epoch 3
1.108100052922964
The running loss is:
20.306521743535995
The number of items in train is:
20
The loss for epoch 4
1.0153260871767997
The running loss is:
19.236631900072098
The number of items in train is:
20
The loss for epoch 5
0.9618315950036049
The running loss is:
19.31939486414194
The number of items in train is:
20
The loss for epoch 6
0.965969743207097
The running loss is:
18.986520119011402
The number of items in train is:
20
The loss for epoch 7
0.9493260059505702
The running loss is:
17.964872032403946
The number of items in train is:
20
The loss for epoch 8
0.8982436016201973
The running loss is:
17.021880947053432
The number of items in train is:
20
The loss for epoch 9
0.8510940473526716
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 -1.726226
47 30819 Eagle County, Colorado, United States ... 47 8.152036
48 30820 Eagle County, Colorado, United States ... 48 9.121257
49 30821 Eagle County, Colorado, United States ... 49 7.794924
50 30822 Eagle County, Colorado, United States ... 50 5.571714
51 30823 Eagle County, Colorado, United States ... 51 2.250640
52 30824 Eagle County, Colorado, United States ... 52 -1.358527
53 30825 Eagle County, Colorado, United States ... 53 -2.516638
54 30826 Eagle County, Colorado, United States ... 54 6.146439
55 30827 Eagle County, Colorado, United States ... 55 7.692529
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: txdsr8qd wandb: Agent Starting Run: 1kt2ejdy with config: batch_size: 2 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1kt2ejdy
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.44402662664652
The number of items in train is:
19
The loss for epoch 0
1.0760014014024484
The running loss is:
31.244781777262688
The number of items in train is:
19
The loss for epoch 1
1.6444621988032992
The running loss is:
28.567642599344254
The number of items in train is:
19
The loss for epoch 2
1.5035601368075924
The running loss is:
22.09902586042881
The number of items in train is:
19
The loss for epoch 3
1.1631066242330952
The running loss is:
20.13299036026001
The number of items in train is:
19
The loss for epoch 4
1.059631071592632
The running loss is:
19.623609885573387
The number of items in train is:
19
The loss for epoch 5
1.032821572924915
The running loss is:
19.941684514284134
The number of items in train is:
19
The loss for epoch 6
1.0495623428570597
The running loss is:
20.171836733818054
The number of items in train is:
19
The loss for epoch 7
1.0616756175693713
The running loss is:
19.684818655252457
The number of items in train is:
19
The loss for epoch 8
1.0360430871185504
The running loss is:
18.656600639224052
The number of items in train is:
19
The loss for epoch 9
0.9819263494328448
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.344335
47 30819 ... 8.965163
48 30820 ... 9.366188
49 30821 ... 9.369502
50 30822 ... 8.577673
51 30823 ... 7.636180
52 30824 ... 6.371642
53 30825 ... 7.675599
54 30826 ... 10.337065
55 30827 ... 10.057920
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1kt2ejdy wandb: Agent Starting Run: bvwqzrjt with config: batch_size: 2 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: bvwqzrjt
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.858943171799183
The number of items in train is:
20
The loss for epoch 0
1.142947158589959
The running loss is:
25.452721800655127
The number of items in train is:
20
The loss for epoch 1
1.2726360900327562
The running loss is:
23.522745087742805
The number of items in train is:
20
The loss for epoch 2
1.1761372543871402
The running loss is:
30.910138800740242
The number of items in train is:
20
The loss for epoch 3
1.545506940037012
The running loss is:
27.686953529715538
The number of items in train is:
20
The loss for epoch 4
1.384347676485777
The running loss is:
22.573460146784782
The number of items in train is:
20
The loss for epoch 5
1.128673007339239
The running loss is:
17.657725639641285
The number of items in train is:
20
The loss for epoch 6
0.8828862819820642
The running loss is:
17.554872505366802
The number of items in train is:
20
The loss for epoch 7
0.8777436252683402
The running loss is:
16.82310827448964
The number of items in train is:
20
The loss for epoch 8
0.8411554137244821
The running loss is:
15.671338841319084
The number of items in train is:
20
The loss for epoch 9
0.7835669420659542
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.077608
47 30819 ... 9.250809
48 30820 ... 10.825143
49 30821 ... 9.578727
50 30822 ... 7.942455
51 30823 ... 5.830050
52 30824 ... 3.557108
53 30825 ... 3.781698
54 30826 ... 9.988200
55 30827 ... 11.042790
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: bvwqzrjt wandb: Agent Starting Run: 9hkq0cre with config: batch_size: 2 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 9hkq0cre
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
26.16333219408989
The number of items in train is:
20
The loss for epoch 0
1.3081666097044944
The running loss is:
26.045250490307808
The number of items in train is:
20
The loss for epoch 1
1.3022625245153905
The running loss is:
25.80753855407238
The number of items in train is:
20
The loss for epoch 2
1.290376927703619
The running loss is:
26.523033320903778
The number of items in train is:
20
The loss for epoch 3
1.3261516660451889
The running loss is:
26.54793219268322
The number of items in train is:
20
The loss for epoch 4
1.327396609634161
The running loss is:
22.712683379650116
The number of items in train is:
20
The loss for epoch 5
1.1356341689825058
The running loss is:
20.329153656959534
The number of items in train is:
20
The loss for epoch 6
1.0164576828479768
The running loss is:
19.61660325527191
The number of items in train is:
20
The loss for epoch 7
0.9808301627635956
The running loss is:
20.726151082664728
The number of items in train is:
20
The loss for epoch 8
1.0363075541332365
The running loss is:
19.05374999344349
The number of items in train is:
20
The loss for epoch 9
0.9526874996721745
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.453219
47 30819 Eagle County, Colorado, United States ... 47 9.035815
48 30820 Eagle County, Colorado, United States ... 48 9.680546
49 30821 Eagle County, Colorado, United States ... 49 9.059596
50 30822 Eagle County, Colorado, United States ... 50 7.984948
51 30823 Eagle County, Colorado, United States ... 51 6.752469
52 30824 Eagle County, Colorado, United States ... 52 5.493628
53 30825 Eagle County, Colorado, United States ... 53 6.058336
54 30826 Eagle County, Colorado, United States ... 54 9.732533
55 30827 Eagle County, Colorado, United States ... 55 9.939076
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9hkq0cre wandb: Agent Starting Run: wcq119wq with config: batch_size: 2 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: wcq119wq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.35972896963358
The number of items in train is:
19
The loss for epoch 0
1.2294594194543988
The running loss is:
29.350028984248638
The number of items in train is:
19
The loss for epoch 1
1.5447383675920336
The running loss is:
23.49043282866478
The number of items in train is:
19
The loss for epoch 2
1.2363385699297254
The running loss is:
24.20486121624708
The number of items in train is:
19
The loss for epoch 3
1.2739400640130043
The running loss is:
23.583865851163864
The number of items in train is:
19
The loss for epoch 4
1.2412560974296771
The running loss is:
21.583225786685944
The number of items in train is:
19
The loss for epoch 5
1.1359592519308392
The running loss is:
19.9445867985487
The number of items in train is:
19
The loss for epoch 6
1.0497150946604579
The running loss is:
20.0459441319108
The number of items in train is:
19
The loss for epoch 7
1.0550496911532001
The running loss is:
19.574128806591034
The number of items in train is:
19
The loss for epoch 8
1.0302173056100543
The running loss is:
19.495283983647823
The number of items in train is:
19
The loss for epoch 9
1.0260675780867274
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.255701
47 30819 ... 9.307986
48 30820 ... 10.159330
49 30821 ... 10.204440
50 30822 ... 9.981266
51 30823 ... 9.593956
52 30824 ... 9.135714
53 30825 ... 9.793672
54 30826 ... 10.906508
55 30827 ... 10.791603
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wcq119wq wandb: Agent Starting Run: yxaojihg with config: batch_size: 2 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yxaojihg
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
63.12795731425285
The number of items in train is:
20
The loss for epoch 0
3.1563978657126426
The running loss is:
27.380909606814384
The number of items in train is:
20
The loss for epoch 1
1.3690454803407193
The running loss is:
38.64922794699669
The number of items in train is:
20
The loss for epoch 2
1.9324613973498344
The running loss is:
24.797455199062824
The number of items in train is:
20
The loss for epoch 3
1.2398727599531412
The running loss is:
24.066325157880783
The number of items in train is:
20
The loss for epoch 4
1.203316257894039
The running loss is:
20.85441730171442
The number of items in train is:
20
The loss for epoch 5
1.042720865085721
The running loss is:
22.116691429167986
The number of items in train is:
20
The loss for epoch 6
1.1058345714583993
The running loss is:
20.194003105163574
The number of items in train is:
20
The loss for epoch 7
1.0097001552581788
The running loss is:
19.880487099289894
The number of items in train is:
20
The loss for epoch 8
0.9940243549644947
The running loss is:
19.48942229896784
The number of items in train is:
20
The loss for epoch 9
0.9744711149483919
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.095248
47 30819 ... 13.675316
48 30820 ... 13.755165
49 30821 ... 12.772159
50 30822 ... 11.387144
51 30823 ... 9.963962
52 30824 ... 8.419066
53 30825 ... 7.604329
54 30826 ... 14.152313
55 30827 ... 13.881279
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yxaojihg wandb: Agent Starting Run: vo69e3rr with config: batch_size: 2 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: vo69e3rr
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
44.05574178695679
The number of items in train is:
20
The loss for epoch 0
2.202787089347839
The running loss is:
25.349156990647316
The number of items in train is:
20
The loss for epoch 1
1.2674578495323658
The running loss is:
33.40304487943649
The number of items in train is:
20
The loss for epoch 2
1.6701522439718246
The running loss is:
31.406648948788643
The number of items in train is:
20
The loss for epoch 3
1.5703324474394322
The running loss is:
22.615651819854975
The number of items in train is:
20
The loss for epoch 4
1.1307825909927487
The running loss is:
22.341147303581238
The number of items in train is:
20
The loss for epoch 5
1.1170573651790618
The running loss is:
22.197795197367668
The number of items in train is:
20
The loss for epoch 6
1.1098897598683835
The running loss is:
24.94717773795128
The number of items in train is:
20
The loss for epoch 7
1.247358886897564
The running loss is:
21.06535917520523
The number of items in train is:
20
The loss for epoch 8
1.0532679587602616
The running loss is:
23.481164187192917
The number of items in train is:
20
The loss for epoch 9
1.1740582093596459
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.153221
47 30819 Eagle County, Colorado, United States ... 47 9.367915
48 30820 Eagle County, Colorado, United States ... 48 9.625638
49 30821 Eagle County, Colorado, United States ... 49 9.611838
50 30822 Eagle County, Colorado, United States ... 50 9.603510
51 30823 Eagle County, Colorado, United States ... 51 9.651998
52 30824 Eagle County, Colorado, United States ... 52 9.644343
53 30825 Eagle County, Colorado, United States ... 53 9.659492
54 30826 Eagle County, Colorado, United States ... 54 9.670691
55 30827 Eagle County, Colorado, United States ... 55 9.647216
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vo69e3rr wandb: Agent Starting Run: x99vu0oz with config: batch_size: 2 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: x99vu0oz
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
43.28711162507534
The number of items in train is:
19
The loss for epoch 0
2.2782690328987023
The running loss is:
25.05246562510729
The number of items in train is:
19
The loss for epoch 1
1.3185508223740678
The running loss is:
26.483036309480667
The number of items in train is:
19
The loss for epoch 2
1.3938440162884562
The running loss is:
23.21202003955841
The number of items in train is:
19
The loss for epoch 3
1.2216852652399164
The running loss is:
24.40618184953928
The number of items in train is:
19
The loss for epoch 4
1.284535886817857
The running loss is:
23.41523738205433
The number of items in train is:
19
The loss for epoch 5
1.2323809148449647
The running loss is:
21.69338585436344
The number of items in train is:
19
The loss for epoch 6
1.1417571502296548
The running loss is:
19.94015894830227
The number of items in train is:
19
The loss for epoch 7
1.0494820499106456
The running loss is:
20.32781156897545
The number of items in train is:
19
The loss for epoch 8
1.0698848194197605
The running loss is:
19.49485769867897
The number of items in train is:
19
The loss for epoch 9
1.0260451420357353
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.251549
47 30819 ... 10.083247
48 30820 ... 10.766473
49 30821 ... 10.922501
50 30822 ... 10.916012
51 30823 ... 10.829031
52 30824 ... 10.715705
53 30825 ... 9.894305
54 30826 ... 11.196030
55 30827 ... 11.021307
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: x99vu0oz wandb: Agent Starting Run: 0112l6k2 with config: batch_size: 2 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0112l6k2
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.372625601943582
The number of items in train is:
20
The loss for epoch 0
1.018631280097179
The running loss is:
42.762292738305405
The number of items in train is:
20
The loss for epoch 1
2.13811463691527
The running loss is:
30.07040224969387
The number of items in train is:
20
The loss for epoch 2
1.5035201124846935
The running loss is:
25.568414388224483
The number of items in train is:
20
The loss for epoch 3
1.278420719411224
The running loss is:
21.809938758146018
The number of items in train is:
20
The loss for epoch 4
1.0904969379073008
The running loss is:
19.993976016994566
The number of items in train is:
20
The loss for epoch 5
0.9996988008497283
The running loss is:
18.31971403909847
The number of items in train is:
20
The loss for epoch 6
0.9159857019549236
The running loss is:
18.475750502664596
The number of items in train is:
20
The loss for epoch 7
0.9237875251332298
The running loss is:
17.406269858358428
The number of items in train is:
20
The loss for epoch 8
0.8703134929179214
The running loss is:
15.831582311540842
The number of items in train is:
20
The loss for epoch 9
0.7915791155770421
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.211360
47 30819 Eagle County, Colorado, United States ... 47 0.805061
48 30820 Eagle County, Colorado, United States ... 48 6.456613
49 30821 Eagle County, Colorado, United States ... 49 5.171219
50 30822 Eagle County, Colorado, United States ... 50 4.403521
51 30823 Eagle County, Colorado, United States ... 51 3.981504
52 30824 Eagle County, Colorado, United States ... 52 1.503850
53 30825 Eagle County, Colorado, United States ... 53 1.144254
54 30826 Eagle County, Colorado, United States ... 54 1.294929
55 30827 Eagle County, Colorado, United States ... 55 6.817929
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0112l6k2 wandb: Agent Starting Run: cz0b2jhf with config: batch_size: 2 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: cz0b2jhf
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.58346115425229
The number of items in train is:
19
The loss for epoch 0
1.0833400607501205
The running loss is:
32.63544833660126
The number of items in train is:
19
The loss for epoch 1
1.7176551756105924
The running loss is:
24.86648626625538
The number of items in train is:
19
The loss for epoch 2
1.3087624350660725
The running loss is:
19.861273169517517
The number of items in train is:
19
The loss for epoch 3
1.0453301668167114
The running loss is:
19.426814898848534
The number of items in train is:
19
The loss for epoch 4
1.0224639420446597
The running loss is:
19.01237651705742
The number of items in train is:
19
The loss for epoch 5
1.000651395634601
The running loss is:
18.123736664652824
The number of items in train is:
19
The loss for epoch 6
0.9538808770869908
The running loss is:
17.36862461268902
The number of items in train is:
19
The loss for epoch 7
0.9141381375099483
The running loss is:
16.771386608481407
The number of items in train is:
19
The loss for epoch 8
0.8827045583411267
The running loss is:
16.049383729696274
The number of items in train is:
19
The loss for epoch 9
0.8447044068261197
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 0.222322
47 30819 ... 0.539564
48 30820 ... 14.811440
49 30821 ... 12.646440
50 30822 ... 12.469790
51 30823 ... 12.615289
52 30824 ... 7.882138
53 30825 ... 7.685679
54 30826 ... 7.464492
55 30827 ... 20.618021
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cz0b2jhf wandb: Agent Starting Run: 6m4vzuog with config: batch_size: 2 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 6m4vzuog
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.154827743768692
The number of items in train is:
19
The loss for epoch 0
1.008148828619405
The running loss is:
31.390202894806862
The number of items in train is:
19
The loss for epoch 1
1.65211594183194
The running loss is:
22.409427136182785
The number of items in train is:
19
The loss for epoch 2
1.1794435334833044
The running loss is:
20.129380136728287
The number of items in train is:
19
The loss for epoch 3
1.0594410598278046
The running loss is:
19.285180315375328
The number of items in train is:
19
The loss for epoch 4
1.015009490282912
The running loss is:
18.609702050685883
The number of items in train is:
19
The loss for epoch 5
0.979458002667678
The running loss is:
17.89329308271408
The number of items in train is:
19
The loss for epoch 6
0.9417522675112674
The running loss is:
18.30278380215168
The number of items in train is:
19
The loss for epoch 7
0.9633044106395621
The running loss is:
17.593301609158516
The number of items in train is:
19
The loss for epoch 8
0.9259632425872903
The running loss is:
16.95015725493431
The number of items in train is:
19
The loss for epoch 9
0.8921135397333848
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 1.498729
47 30819 ... 2.784153
48 30820 ... 7.250659
49 30821 ... 6.390955
50 30822 ... 6.113214
51 30823 ... 6.685583
52 30824 ... 4.513458
53 30825 ... 5.044778
54 30826 ... 6.276218
55 30827 ... 10.104283
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6m4vzuog wandb: Agent Starting Run: xj4p6nut with config: batch_size: 2 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: xj4p6nut
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
24.988776933401823
The number of items in train is:
20
The loss for epoch 0
1.2494388466700912
The running loss is:
34.32063250988722
The number of items in train is:
20
The loss for epoch 1
1.7160316254943608
The running loss is:
33.453855484724045
The number of items in train is:
20
The loss for epoch 2
1.6726927742362023
The running loss is:
23.9404144436121
The number of items in train is:
20
The loss for epoch 3
1.1970207221806048
The running loss is:
17.672576233861037
The number of items in train is:
20
The loss for epoch 4
0.8836288116930519
The running loss is:
17.489475843962282
The number of items in train is:
20
The loss for epoch 5
0.874473792198114
The running loss is:
17.147922162897885
The number of items in train is:
20
The loss for epoch 6
0.8573961081448942
The running loss is:
16.498743789969012
The number of items in train is:
20
The loss for epoch 7
0.8249371894984506
The running loss is:
17.00277705863118
The number of items in train is:
20
The loss for epoch 8
0.8501388529315591
The running loss is:
16.65495465998538
The number of items in train is:
20
The loss for epoch 9
0.832747732999269
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.488977
47 30819 Eagle County, Colorado, United States ... 47 0.897190
48 30820 Eagle County, Colorado, United States ... 48 6.354722
49 30821 Eagle County, Colorado, United States ... 49 4.820605
50 30822 Eagle County, Colorado, United States ... 50 4.016927
51 30823 Eagle County, Colorado, United States ... 51 4.606457
52 30824 Eagle County, Colorado, United States ... 52 2.254005
53 30825 Eagle County, Colorado, United States ... 53 1.486971
54 30826 Eagle County, Colorado, United States ... 54 1.760599
55 30827 Eagle County, Colorado, United States ... 55 7.010409
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xj4p6nut wandb: Agent Starting Run: ktbeaa9j with config: batch_size: 2 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ktbeaa9j
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.999079801142216
The number of items in train is:
19
The loss for epoch 0
1.1578463053232746
The running loss is:
30.826843470335007
The number of items in train is:
19
The loss for epoch 1
1.6224654458071057
The running loss is:
26.63893211632967
The number of items in train is:
19
The loss for epoch 2
1.4020490587541932
The running loss is:
22.48357506096363
The number of items in train is:
19
The loss for epoch 3
1.1833460558401911
The running loss is:
19.925148122012615
The number of items in train is:
19
The loss for epoch 4
1.0486920064217167
The running loss is:
18.893528878688812
The number of items in train is:
19
The loss for epoch 5
0.9943962567730954
The running loss is:
18.58210776746273
The number of items in train is:
19
The loss for epoch 6
0.9780056719717226
The running loss is:
17.370767161250114
The number of items in train is:
19
The loss for epoch 7
0.9142509032236902
The running loss is:
16.939767386764288
The number of items in train is:
19
The loss for epoch 8
0.8915667045665415
The running loss is:
18.0814261212945
The number of items in train is:
19
The loss for epoch 9
0.951654006383921
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.043530
47 30819 ... 8.564563
48 30820 ... 13.208735
49 30821 ... 13.813708
50 30822 ... 14.007776
51 30823 ... 12.857953
52 30824 ... 9.531335
53 30825 ... 11.662832
54 30826 ... 13.480352
55 30827 ... 18.950397
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ktbeaa9j wandb: Agent Starting Run: hxsffuei with config: batch_size: 2 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hxsffuei
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.854974925518036
The number of items in train is:
19
The loss for epoch 0
1.044998680290423
The running loss is:
30.09627439081669
The number of items in train is:
19
The loss for epoch 1
1.584014441621931
The running loss is:
26.052530765533447
The number of items in train is:
19
The loss for epoch 2
1.3711858297649182
The running loss is:
20.87158501148224
The number of items in train is:
19
The loss for epoch 3
1.0985044742885388
The running loss is:
19.386949434876442
The number of items in train is:
19
The loss for epoch 4
1.020365759730339
The running loss is:
18.365763187408447
The number of items in train is:
19
The loss for epoch 5
0.9666191151267604
The running loss is:
18.275505244731903
The number of items in train is:
19
The loss for epoch 6
0.9618686970911527
The running loss is:
18.561134546995163
The number of items in train is:
19
The loss for epoch 7
0.9769018182629033
The running loss is:
17.98644445836544
The number of items in train is:
19
The loss for epoch 8
0.9466549714929179
The running loss is:
16.56345410645008
The number of items in train is:
19
The loss for epoch 9
0.8717607424447411
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.921343
47 30819 ... 5.653644
48 30820 ... 9.571172
49 30821 ... 10.741131
50 30822 ... 9.583526
51 30823 ... 10.284985
52 30824 ... 8.859438
53 30825 ... 12.613676
54 30826 ... 13.139013
55 30827 ... 16.450876
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hxsffuei wandb: Agent Starting Run: b737k97a with config: batch_size: 2 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: b737k97a
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
40.35339838266373
The number of items in train is:
20
The loss for epoch 0
2.017669919133186
The running loss is:
25.41597201861441
The number of items in train is:
20
The loss for epoch 1
1.2707986009307206
The running loss is:
53.00542160903569
The number of items in train is:
20
The loss for epoch 2
2.650271080451785
The running loss is:
30.41038277000189
The number of items in train is:
20
The loss for epoch 3
1.5205191385000945
The running loss is:
40.67561185359955
The number of items in train is:
20
The loss for epoch 4
2.0337805926799772
The running loss is:
22.468553626909852
The number of items in train is:
20
The loss for epoch 5
1.1234276813454926
The running loss is:
21.3985225148499
The number of items in train is:
20
The loss for epoch 6
1.069926125742495
The running loss is:
19.585227265022695
The number of items in train is:
20
The loss for epoch 7
0.9792613632511348
The running loss is:
19.549080536235124
The number of items in train is:
20
The loss for epoch 8
0.9774540268117562
The running loss is:
21.40721446927637
The number of items in train is:
20
The loss for epoch 9
1.0703607234638184
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.792440
47 30819 Eagle County, Colorado, United States ... 47 7.494670
48 30820 Eagle County, Colorado, United States ... 48 7.285886
49 30821 Eagle County, Colorado, United States ... 49 7.716760
50 30822 Eagle County, Colorado, United States ... 50 7.138034
51 30823 Eagle County, Colorado, United States ... 51 6.490120
52 30824 Eagle County, Colorado, United States ... 52 5.939859
53 30825 Eagle County, Colorado, United States ... 53 8.235563
54 30826 Eagle County, Colorado, United States ... 54 8.465868
55 30827 Eagle County, Colorado, United States ... 55 8.199594
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b737k97a wandb: Agent Starting Run: fe84e15w with config: batch_size: 2 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fe84e15w
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
29.204040184617043
The number of items in train is:
19
The loss for epoch 0
1.5370547465587918
The running loss is:
24.24693512916565
The number of items in train is:
19
The loss for epoch 1
1.2761544804824025
The running loss is:
23.89077879488468
The number of items in train is:
19
The loss for epoch 2
1.2574094102570885
The running loss is:
25.985695831477642
The number of items in train is:
19
The loss for epoch 3
1.367668201656718
The running loss is:
23.965177146717906
The number of items in train is:
19
The loss for epoch 4
1.261325112985153
The running loss is:
21.409245938062668
The number of items in train is:
19
The loss for epoch 5
1.126802417792772
The running loss is:
19.704271476715803
The number of items in train is:
19
The loss for epoch 6
1.0370669198271476
The running loss is:
19.2407064512372
The number of items in train is:
19
The loss for epoch 7
1.0126687605914317
The running loss is:
18.875049274414778
The number of items in train is:
19
The loss for epoch 8
0.9934236460218304
The running loss is:
16.603436348959804
The number of items in train is:
19
The loss for epoch 9
0.8738650709978844
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.420867
47 30819 ... 10.179868
48 30820 ... 11.027630
49 30821 ... 11.649125
50 30822 ... 10.415971
51 30823 ... 8.790237
52 30824 ... 6.691815
53 30825 ... 10.714285
54 30826 ... 11.232683
55 30827 ... 11.909349
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fe84e15w wandb: Agent Starting Run: 8ufb9xcb with config: batch_size: 2 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8ufb9xcb
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
25.113935858011246
The number of items in train is:
19
The loss for epoch 0
1.3217860977900655
The running loss is:
22.519097536802292
The number of items in train is:
19
The loss for epoch 1
1.1852156598316996
The running loss is:
24.353960901498795
The number of items in train is:
19
The loss for epoch 2
1.2817874158683575
The running loss is:
24.2918109446764
The number of items in train is:
19
The loss for epoch 3
1.2785163655092842
The running loss is:
25.014960184693336
The number of items in train is:
19
The loss for epoch 4
1.316576851825965
The running loss is:
21.30792599916458
The number of items in train is:
19
The loss for epoch 5
1.1214697894297148
The running loss is:
19.39668668806553
The number of items in train is:
19
The loss for epoch 6
1.020878246740291
The running loss is:
19.37868858873844
The number of items in train is:
19
The loss for epoch 7
1.0199309783546548
The running loss is:
19.13155810534954
The number of items in train is:
19
The loss for epoch 8
1.0069241108078706
The running loss is:
19.100456029176712
The number of items in train is:
19
The loss for epoch 9
1.0052871594303532
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.524095
47 30819 ... 10.476821
48 30820 ... 11.046574
49 30821 ... 11.381286
50 30822 ... 10.889049
51 30823 ... 10.311730
52 30824 ... 9.664641
53 30825 ... 11.371816
54 30826 ... 11.416924
55 30827 ... 11.818830
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8ufb9xcb wandb: Agent Starting Run: g4xzyzr0 with config: batch_size: 2 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: g4xzyzr0
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
117.5767124183476
The number of items in train is:
20
The loss for epoch 0
5.87883562091738
The running loss is:
25.486171117052436
The number of items in train is:
20
The loss for epoch 1
1.2743085558526217
The running loss is:
37.6898739207536
The number of items in train is:
20
The loss for epoch 2
1.88449369603768
The running loss is:
23.39531859382987
The number of items in train is:
20
The loss for epoch 3
1.1697659296914935
The running loss is:
27.995998777856585
The number of items in train is:
20
The loss for epoch 4
1.3997999388928293
The running loss is:
37.414801586419344
The number of items in train is:
20
The loss for epoch 5
1.8707400793209672
The running loss is:
27.45275203883648
The number of items in train is:
20
The loss for epoch 6
1.372637601941824
The running loss is:
29.12205201201141
The number of items in train is:
20
The loss for epoch 7
1.4561026006005704
The running loss is:
21.42994563933462
The number of items in train is:
20
The loss for epoch 8
1.071497281966731
The running loss is:
20.176511982805096
The number of items in train is:
20
The loss for epoch 9
1.0088255991402548
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.190459
47 30819 ... 9.656222
48 30820 ... 10.072992
49 30821 ... 10.239223
50 30822 ... 9.966965
51 30823 ... 9.720456
52 30824 ... 9.445283
53 30825 ... 10.617431
54 30826 ... 10.793635
55 30827 ... 10.693918
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: g4xzyzr0 wandb: Agent Starting Run: q4a00375 with config: batch_size: 2 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: q4a00375
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
75.37063696980476
The number of items in train is:
19
The loss for epoch 0
3.9668756299897243
The running loss is:
28.946842608973384
The number of items in train is:
19
The loss for epoch 1
1.5235180320512307
The running loss is:
37.80971126258373
The number of items in train is:
19
The loss for epoch 2
1.9899848032938807
The running loss is:
28.027809100225568
The number of items in train is:
19
The loss for epoch 3
1.475147847380293
The running loss is:
22.214233489707112
The number of items in train is:
19
The loss for epoch 4
1.1691701836687953
The running loss is:
22.130612179636955
The number of items in train is:
19
The loss for epoch 5
1.1647690620861555
The running loss is:
20.125448502600193
The number of items in train is:
19
The loss for epoch 6
1.0592341317157996
The running loss is:
19.99137994274497
The number of items in train is:
19
The loss for epoch 7
1.0521778917234195
The running loss is:
19.447364665567875
The number of items in train is:
19
The loss for epoch 8
1.0235455087140988
The running loss is:
19.63094657845795
The number of items in train is:
19
The loss for epoch 9
1.0332077146556817
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.141244
47 30819 ... 8.384874
48 30820 ... 9.568216
49 30821 ... 10.020310
50 30822 ... 9.479197
51 30823 ... 9.105638
52 30824 ... 8.633883
53 30825 ... 9.554037
54 30826 ... 9.554685
55 30827 ... 10.687004
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: q4a00375 wandb: Agent Starting Run: oo78j1mm with config: batch_size: 2 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: oo78j1mm
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
55.04631087183952
The number of items in train is:
19
The loss for epoch 0
2.8971742564126064
The running loss is:
25.651281729340553
The number of items in train is:
19
The loss for epoch 1
1.3500674594389765
The running loss is:
29.31262482702732
The number of items in train is:
19
The loss for epoch 2
1.5427697277382801
The running loss is:
21.643531814217567
The number of items in train is:
19
The loss for epoch 3
1.139133253379872
The running loss is:
23.51069213449955
The number of items in train is:
19
The loss for epoch 4
1.237404849184187
The running loss is:
20.243462055921555
The number of items in train is:
19
The loss for epoch 5
1.0654453713642924
The running loss is:
19.515670895576477
The number of items in train is:
19
The loss for epoch 6
1.0271405734513934
The running loss is:
19.44848108291626
The number of items in train is:
19
The loss for epoch 7
1.0236042675219084
The running loss is:
19.702705189585686
The number of items in train is:
19
The loss for epoch 8
1.0369844836624045
The running loss is:
19.46839915215969
The number of items in train is:
19
The loss for epoch 9
1.0246525869557732
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.704140
47 30819 ... 8.862094
48 30820 ... 11.880857
49 30821 ... 11.703236
50 30822 ... 10.769067
51 30823 ... 8.554482
52 30824 ... 7.181332
53 30825 ... 9.513320
54 30826 ... 9.827226
55 30827 ... 12.694811
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: oo78j1mm wandb: Agent Starting Run: wdzwiki2 with config: batch_size: 2 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: wdzwiki2
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.439917542040348
The number of items in train is:
19
The loss for epoch 0
1.0231535548442288
The running loss is:
30.940813273191452
The number of items in train is:
19
The loss for epoch 1
1.6284638564837606
The running loss is:
20.62387929111719
The number of items in train is:
19
The loss for epoch 2
1.0854673311114311
The running loss is:
18.94204149954021
The number of items in train is:
19
The loss for epoch 3
0.9969495526073795
The running loss is:
18.354026339948177
The number of items in train is:
19
The loss for epoch 4
0.966001386313062
The running loss is:
17.25484985858202
The number of items in train is:
19
The loss for epoch 5
0.9081499925569484
The running loss is:
15.713611334562302
The number of items in train is:
19
The loss for epoch 6
0.827032175503279
The running loss is:
17.080039270222187
The number of items in train is:
19
The loss for epoch 7
0.8989494352748519
The running loss is:
16.1761021791026
The number of items in train is:
19
The loss for epoch 8
0.8513737989001369
The running loss is:
15.210037291049957
The number of items in train is:
19
The loss for epoch 9
0.8005282784763136
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 1.405954
47 30819 ... 5.021082
48 30820 ... 6.838092
49 30821 ... 13.628771
50 30822 ... 11.002051
51 30823 ... 10.494727
52 30824 ... 8.353095
53 30825 ... 8.039375
54 30826 ... 12.134420
55 30827 ... 13.312056
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wdzwiki2 wandb: Agent Starting Run: 9sw07zmk with config: batch_size: 2 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 9sw07zmk
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.866965148597956
The number of items in train is:
19
The loss for epoch 0
1.1508929025577872
The running loss is:
28.42113022506237
The number of items in train is:
19
The loss for epoch 1
1.495848959213809
The running loss is:
19.687769025564194
The number of items in train is:
19
The loss for epoch 2
1.0361983697665365
The running loss is:
18.45985646545887
The number of items in train is:
19
The loss for epoch 3
0.9715713929188879
The running loss is:
17.097035117447376
The number of items in train is:
19
The loss for epoch 4
0.8998439535498619
The running loss is:
17.411960707977414
The number of items in train is:
19
The loss for epoch 5
0.9164189846303902
The running loss is:
15.815325029194355
The number of items in train is:
19
The loss for epoch 6
0.8323855278523344
The running loss is:
17.199874091893435
The number of items in train is:
19
The loss for epoch 7
0.905256531152286
The running loss is:
15.348654120229185
The number of items in train is:
19
The loss for epoch 8
0.8078239010646939
The running loss is:
16.138024419546127
The number of items in train is:
19
The loss for epoch 9
0.8493697062919014
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.408259
47 30819 Eagle County, Colorado, United States ... 47 4.232812
48 30820 Eagle County, Colorado, United States ... 48 4.682319
49 30821 Eagle County, Colorado, United States ... 49 4.901486
50 30822 Eagle County, Colorado, United States ... 50 5.480176
51 30823 Eagle County, Colorado, United States ... 51 5.034000
52 30824 Eagle County, Colorado, United States ... 52 4.305603
53 30825 Eagle County, Colorado, United States ... 53 6.571662
54 30826 Eagle County, Colorado, United States ... 54 7.423872
55 30827 Eagle County, Colorado, United States ... 55 7.719498
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9sw07zmk wandb: Agent Starting Run: js3qf6my with config: batch_size: 2 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: js3qf6my
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.61895739287138
The number of items in train is:
18
The loss for epoch 0
1.0343865218261878
The running loss is:
32.830586299300194
The number of items in train is:
18
The loss for epoch 1
1.823921461072233
The running loss is:
20.112476214766502
The number of items in train is:
18
The loss for epoch 2
1.1173597897092502
The running loss is:
18.968113116919994
The number of items in train is:
18
The loss for epoch 3
1.0537840620511107
The running loss is:
16.988379642367363
The number of items in train is:
18
The loss for epoch 4
0.9437988690204091
The running loss is:
15.98021186888218
The number of items in train is:
18
The loss for epoch 5
0.8877895482712321
The running loss is:
16.49119970947504
The number of items in train is:
18
The loss for epoch 6
0.9161777616375022
The running loss is:
14.859417550265789
The number of items in train is:
18
The loss for epoch 7
0.8255231972369883
The running loss is:
17.23430199921131
The number of items in train is:
18
The loss for epoch 8
0.9574612221784062
The running loss is:
15.640456855297089
The number of items in train is:
18
The loss for epoch 9
0.8689142697387271
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.227388
47 30819 ... 9.126212
48 30820 ... 10.664755
49 30821 ... 11.284911
50 30822 ... 13.417641
51 30823 ... 14.878563
52 30824 ... 15.908744
53 30825 ... 16.099213
54 30826 ... 17.605251
55 30827 ... 18.707098
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: js3qf6my wandb: Agent Starting Run: a624rlup with config: batch_size: 2 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: a624rlup
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.47774775326252
The number of items in train is:
19
The loss for epoch 0
0.9198814606980273
The running loss is:
34.215459898114204
The number of items in train is:
19
The loss for epoch 1
1.800813678848116
The running loss is:
26.83509284630418
The number of items in train is:
19
The loss for epoch 2
1.4123733077002198
The running loss is:
18.867049887776375
The number of items in train is:
19
The loss for epoch 3
0.9930026256724408
The running loss is:
19.295793317258358
The number of items in train is:
19
The loss for epoch 4
1.0155680693293874
The running loss is:
17.851775374263525
The number of items in train is:
19
The loss for epoch 5
0.9395671249612382
The running loss is:
15.97345557063818
The number of items in train is:
19
The loss for epoch 6
0.8407081879283252
The running loss is:
17.56080763041973
The number of items in train is:
19
The loss for epoch 7
0.9242530331799859
The running loss is:
14.913559079170227
The number of items in train is:
19
The loss for epoch 8
0.7849241620615909
The running loss is:
12.077535170596093
The number of items in train is:
19
The loss for epoch 9
0.6356597458208469
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.444650
47 30819 ... 6.855227
48 30820 ... 9.685863
49 30821 ... 15.988708
50 30822 ... 8.681789
51 30823 ... 9.771622
52 30824 ... 9.542686
53 30825 ... 9.555958
54 30826 ... 13.526699
55 30827 ... 14.681934
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: a624rlup wandb: Agent Starting Run: 40xynftp with config: batch_size: 2 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 40xynftp
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.308471772819757
The number of items in train is:
19
The loss for epoch 0
0.9636037775168294
The running loss is:
30.251929253339767
The number of items in train is:
19
The loss for epoch 1
1.5922068028073562
The running loss is:
24.49585047364235
The number of items in train is:
19
The loss for epoch 2
1.2892552880864394
The running loss is:
19.259405851364136
The number of items in train is:
19
The loss for epoch 3
1.0136529395454807
The running loss is:
18.27196502685547
The number of items in train is:
19
The loss for epoch 4
0.9616823698344984
The running loss is:
19.17086371779442
The number of items in train is:
19
The loss for epoch 5
1.0089928272523379
The running loss is:
17.18504023551941
The number of items in train is:
19
The loss for epoch 6
0.9044758018694425
The running loss is:
18.312036082148552
The number of items in train is:
19
The loss for epoch 7
0.9637913727446606
The running loss is:
16.296567849814892
The number of items in train is:
19
The loss for epoch 8
0.8577140973586785
The running loss is:
17.141273446381092
The number of items in train is:
19
The loss for epoch 9
0.9021722866516364
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.938318
47 30819 Eagle County, Colorado, United States ... 47 5.764008
48 30820 Eagle County, Colorado, United States ... 48 6.388542
49 30821 Eagle County, Colorado, United States ... 49 7.110359
50 30822 Eagle County, Colorado, United States ... 50 7.884383
51 30823 Eagle County, Colorado, United States ... 51 7.342934
52 30824 Eagle County, Colorado, United States ... 52 6.783928
53 30825 Eagle County, Colorado, United States ... 53 8.088088
54 30826 Eagle County, Colorado, United States ... 54 8.484551
55 30827 Eagle County, Colorado, United States ... 55 8.842177
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 40xynftp wandb: Agent Starting Run: x9p0raql with config: batch_size: 2 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: x9p0raql
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.20878306031227
The number of items in train is:
18
The loss for epoch 0
1.0115990589062374
The running loss is:
30.39992317557335
The number of items in train is:
18
The loss for epoch 1
1.688884620865186
The running loss is:
24.892738670110703
The number of items in train is:
18
The loss for epoch 2
1.3829299261172612
The running loss is:
18.693133994936943
The number of items in train is:
18
The loss for epoch 3
1.0385074441631634
The running loss is:
17.386428490281105
The number of items in train is:
18
The loss for epoch 4
0.9659126939045058
The running loss is:
17.251834139227867
The number of items in train is:
18
The loss for epoch 5
0.9584352299571037
The running loss is:
16.990745536983013
The number of items in train is:
18
The loss for epoch 6
0.9439303076101674
The running loss is:
15.523895770311356
The number of items in train is:
18
The loss for epoch 7
0.8624386539061865
The running loss is:
15.15600986033678
The number of items in train is:
18
The loss for epoch 8
0.8420005477964878
The running loss is:
15.994639500975609
The number of items in train is:
18
The loss for epoch 9
0.8885910833875338
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... -3.318589
47 30819 ... 3.843014
48 30820 ... 5.907660
49 30821 ... 8.168655
50 30822 ... 7.266984
51 30823 ... 11.548547
52 30824 ... 12.392776
53 30825 ... 7.730372
54 30826 ... 12.077904
55 30827 ... 15.405001
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: x9p0raql wandb: Agent Starting Run: 1nc5hjpj with config: batch_size: 2 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1nc5hjpj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.01491452753544
The number of items in train is:
19
The loss for epoch 0
1.1586797119755494
The running loss is:
31.853158585727215
The number of items in train is:
19
The loss for epoch 1
1.6764820308277482
The running loss is:
26.29714571684599
The number of items in train is:
19
The loss for epoch 2
1.384060300886631
The running loss is:
26.294843655079603
The number of items in train is:
19
The loss for epoch 3
1.3839391397410317
The running loss is:
19.7319422904402
The number of items in train is:
19
The loss for epoch 4
1.038523278444221
The running loss is:
19.520247725769877
The number of items in train is:
19
The loss for epoch 5
1.0273814592510462
The running loss is:
20.0667427983135
The number of items in train is:
19
The loss for epoch 6
1.0561443578059737
The running loss is:
21.17197396606207
The number of items in train is:
19
The loss for epoch 7
1.1143144192664247
The running loss is:
19.718472911044955
The number of items in train is:
19
The loss for epoch 8
1.037814363739208
The running loss is:
19.412712370976806
The number of items in train is:
19
The loss for epoch 9
1.0217217037356214
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.294752
47 30819 ... 9.692703
48 30820 ... 9.468822
49 30821 ... 9.753605
50 30822 ... 9.970875
51 30823 ... 10.097393
52 30824 ... 10.157984
53 30825 ... 9.429254
54 30826 ... 9.691366
55 30827 ... 9.643483
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1nc5hjpj wandb: Agent Starting Run: 4l4l0izo with config: batch_size: 2 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4l4l0izo
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.050547145307064
The number of items in train is:
19
The loss for epoch 0
1.1605551129108982
The running loss is:
25.80047580599785
The number of items in train is:
19
The loss for epoch 1
1.3579197792630446
The running loss is:
25.028174303472042
The number of items in train is:
19
The loss for epoch 2
1.3172723317616863
The running loss is:
20.451709896326065
The number of items in train is:
19
The loss for epoch 3
1.0764057840171612
The running loss is:
19.47241935878992
The number of items in train is:
19
The loss for epoch 4
1.0248641767784168
The running loss is:
20.091709028929472
The number of items in train is:
19
The loss for epoch 5
1.0574583699436564
The running loss is:
19.807796388864517
The number of items in train is:
19
The loss for epoch 6
1.042515599413922
The running loss is:
19.969597205519676
The number of items in train is:
19
The loss for epoch 7
1.0510314318694567
The running loss is:
19.053783051669598
The number of items in train is:
19
The loss for epoch 8
1.0028306869299788
The running loss is:
20.52410914003849
The number of items in train is:
19
The loss for epoch 9
1.0802162705283416
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 12.075467
47 30819 ... 12.087450
48 30820 ... 12.215178
49 30821 ... 12.526230
50 30822 ... 12.124049
51 30823 ... 12.042738
52 30824 ... 11.950590
53 30825 ... 11.619714
54 30826 ... 11.910013
55 30827 ... 11.983730
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4l4l0izo wandb: Agent Starting Run: 9n09j7mq with config: batch_size: 2 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 9n09j7mq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.33804288506508
The number of items in train is:
18
The loss for epoch 0
1.2410023825036154
The running loss is:
29.3419336527586
The number of items in train is:
18
The loss for epoch 1
1.6301074251532555
The running loss is:
24.344750091433525
The number of items in train is:
18
The loss for epoch 2
1.3524861161907513
The running loss is:
26.355553224682808
The number of items in train is:
18
The loss for epoch 3
1.464197401371267
The running loss is:
19.099645756185055
The number of items in train is:
18
The loss for epoch 4
1.0610914308991697
The running loss is:
18.798252046108246
The number of items in train is:
18
The loss for epoch 5
1.0443473358949025
The running loss is:
18.6990150436759
The number of items in train is:
18
The loss for epoch 6
1.0388341690931056
The running loss is:
18.03596955537796
The number of items in train is:
18
The loss for epoch 7
1.001998308632109
The running loss is:
19.955710768699646
The number of items in train is:
18
The loss for epoch 8
1.1086505982610915
The running loss is:
17.729627013206482
The number of items in train is:
18
The loss for epoch 9
0.9849792785114713
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.881124
47 30819 ... 8.230920
48 30820 ... 9.809904
49 30821 ... 10.729694
50 30822 ... 11.824153
51 30823 ... 12.183820
52 30824 ... 12.874773
53 30825 ... 15.379370
54 30826 ... 11.733409
55 30827 ... 12.554773
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9n09j7mq wandb: Agent Starting Run: syski6rt with config: batch_size: 2 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: syski6rt
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
63.3910943493247
The number of items in train is:
19
The loss for epoch 0
3.3363733868065633
The running loss is:
47.28794980049133
The number of items in train is:
19
The loss for epoch 1
2.4888394631837545
The running loss is:
23.97084303200245
The number of items in train is:
19
The loss for epoch 2
1.2616233174738132
The running loss is:
24.236013285815716
The number of items in train is:
19
The loss for epoch 3
1.2755796466218798
The running loss is:
23.217061527073383
The number of items in train is:
19
The loss for epoch 4
1.2219506066880728
The running loss is:
23.78413737937808
The number of items in train is:
19
The loss for epoch 5
1.2517967041777938
The running loss is:
20.42416459042579
The number of items in train is:
19
The loss for epoch 6
1.0749560310750415
The running loss is:
21.191512526012957
The number of items in train is:
19
The loss for epoch 7
1.1153427645269978
The running loss is:
20.13818071037531
The number of items in train is:
19
The loss for epoch 8
1.05990424791449
The running loss is:
19.909312774660066
The number of items in train is:
19
The loss for epoch 9
1.047858567087372
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.473160
47 30819 ... 10.076666
48 30820 ... 9.667487
49 30821 ... 9.543557
50 30822 ... 9.632355
51 30823 ... 9.628160
52 30824 ... 9.336935
53 30825 ... 9.680449
54 30826 ... 9.660083
55 30827 ... 9.695948
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: syski6rt wandb: Agent Starting Run: 4du6hfng with config: batch_size: 2 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4du6hfng
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
45.15644834935665
The number of items in train is:
19
The loss for epoch 0
2.376655176281929
The running loss is:
24.583040460944176
The number of items in train is:
19
The loss for epoch 1
1.2938442347865355
The running loss is:
24.31435240805149
The number of items in train is:
19
The loss for epoch 2
1.2797027583184994
The running loss is:
19.6933766156435
The number of items in train is:
19
The loss for epoch 3
1.0364935060865001
The running loss is:
22.520604372024536
The number of items in train is:
19
The loss for epoch 4
1.1852949669486599
The running loss is:
20.99607415497303
The number of items in train is:
19
The loss for epoch 5
1.1050565344722647
The running loss is:
21.251499339938164
The number of items in train is:
19
The loss for epoch 6
1.1184999652599033
The running loss is:
18.809990733861923
The number of items in train is:
19
The loss for epoch 7
0.9899995123085222
The running loss is:
21.792427882552147
The number of items in train is:
19
The loss for epoch 8
1.146969888555376
The running loss is:
26.7241814956069
The number of items in train is:
19
The loss for epoch 9
1.4065358681898368
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 13.673933
47 30819 ... 14.546380
48 30820 ... 13.259560
49 30821 ... 12.589678
50 30822 ... 12.516530
51 30823 ... 12.692194
52 30824 ... 12.960377
53 30825 ... 12.941114
54 30826 ... 12.940870
55 30827 ... 12.940939
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4du6hfng wandb: Agent Starting Run: fcgaitxn with config: batch_size: 2 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: fcgaitxn
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
53.720550164580345
The number of items in train is:
18
The loss for epoch 0
2.9844750091433525
The running loss is:
28.512199953198433
The number of items in train is:
18
The loss for epoch 1
1.584011108511024
The running loss is:
27.69733640551567
The number of items in train is:
18
The loss for epoch 2
1.5387409114175372
The running loss is:
21.140835970640182
The number of items in train is:
18
The loss for epoch 3
1.174490887257788
The running loss is:
20.6005170494318
The number of items in train is:
18
The loss for epoch 4
1.1444731694128778
The running loss is:
19.554107524454594
The number of items in train is:
18
The loss for epoch 5
1.086339306914144
The running loss is:
18.478814348578453
The number of items in train is:
18
The loss for epoch 6
1.0266007971432474
The running loss is:
20.78046827018261
The number of items in train is:
18
The loss for epoch 7
1.1544704594545894
The running loss is:
19.102542735636234
The number of items in train is:
18
The loss for epoch 8
1.061252374202013
The running loss is:
18.857495926320553
The number of items in train is:
18
The loss for epoch 9
1.047638662573364
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.976553
47 30819 ... 10.621822
48 30820 ... 10.570047
49 30821 ... 10.549634
50 30822 ... 10.590073
51 30823 ... 10.583848
52 30824 ... 10.555012
53 30825 ... 10.526819
54 30826 ... 10.730923
55 30827 ... 10.765011
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fcgaitxn wandb: Agent Starting Run: q1qyufq3 with config: batch_size: 2 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: q1qyufq3
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.65174242667854
The number of items in train is:
19
The loss for epoch 0
1.2448285487725546
The running loss is:
25.936323020607233
The number of items in train is:
19
The loss for epoch 1
1.3650696326635385
The running loss is:
19.027717442717403
The number of items in train is:
19
The loss for epoch 2
1.0014588127746002
The running loss is:
17.514922223752365
The number of items in train is:
19
The loss for epoch 3
0.9218380117764402
The running loss is:
18.12891899421811
The number of items in train is:
19
The loss for epoch 4
0.9541536312746374
The running loss is:
15.658698424231261
The number of items in train is:
19
The loss for epoch 5
0.8241420223279611
The running loss is:
14.604375790804625
The number of items in train is:
19
The loss for epoch 6
0.7686513574107697
The running loss is:
13.23361701448448
The number of items in train is:
19
The loss for epoch 7
0.6965061586570779
The running loss is:
10.202940588351339
The number of items in train is:
19
The loss for epoch 8
0.5369968730711231
The running loss is:
12.158686246722937
The number of items in train is:
19
The loss for epoch 9
0.6399308550906809
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 -1.166312
47 30819 Eagle County, Colorado, United States ... 47 -1.301611
48 30820 Eagle County, Colorado, United States ... 48 -0.988161
49 30821 Eagle County, Colorado, United States ... 49 -0.737440
50 30822 Eagle County, Colorado, United States ... 50 -0.657340
51 30823 Eagle County, Colorado, United States ... 51 -2.650376
52 30824 Eagle County, Colorado, United States ... 52 -3.321557
53 30825 Eagle County, Colorado, United States ... 53 -5.164228
54 30826 Eagle County, Colorado, United States ... 54 -5.676957
55 30827 Eagle County, Colorado, United States ... 55 -5.217156
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: q1qyufq3 wandb: Agent Starting Run: enziyrl1 with config: batch_size: 2 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: enziyrl1
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.002433963119984
The number of items in train is:
18
The loss for epoch 0
1.055690775728888
The running loss is:
30.960632115602493
The number of items in train is:
18
The loss for epoch 1
1.7200351175334718
The running loss is:
20.485445886850357
The number of items in train is:
18
The loss for epoch 2
1.1380803270472422
The running loss is:
18.922638848423958
The number of items in train is:
18
The loss for epoch 3
1.051257713801331
The running loss is:
17.114296164363623
The number of items in train is:
18
The loss for epoch 4
0.9507942313535346
The running loss is:
16.546244710683823
The number of items in train is:
18
The loss for epoch 5
0.9192358172602124
The running loss is:
15.97559380531311
The number of items in train is:
18
The loss for epoch 6
0.8875329891840616
The running loss is:
15.165507942438126
The number of items in train is:
18
The loss for epoch 7
0.8425282190243403
The running loss is:
16.049193635582924
The number of items in train is:
18
The loss for epoch 8
0.8916218686434958
The running loss is:
14.222302194684744
The number of items in train is:
18
The loss for epoch 9
0.790127899704708
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.894466
47 30819 ... 10.531710
48 30820 ... 8.822516
49 30821 ... 7.990013
50 30822 ... 6.305098
51 30823 ... 10.142908
52 30824 ... 13.165692
53 30825 ... 15.270938
54 30826 ... 19.283394
55 30827 ... 17.361763
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: enziyrl1 wandb: Agent Starting Run: 05s9xxu7 with config: batch_size: 2 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 05s9xxu7
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.876264482736588
The number of items in train is:
18
The loss for epoch 0
1.1597924712631438
The running loss is:
27.826325714588165
The number of items in train is:
18
The loss for epoch 1
1.545906984143787
The running loss is:
20.435464337468147
The number of items in train is:
18
The loss for epoch 2
1.135303574303786
The running loss is:
19.343905992805958
The number of items in train is:
18
The loss for epoch 3
1.0746614440447755
The running loss is:
18.26167470216751
The number of items in train is:
18
The loss for epoch 4
1.0145374834537506
The running loss is:
17.55466791242361
The number of items in train is:
18
The loss for epoch 5
0.9752593284679784
The running loss is:
16.646836515516043
The number of items in train is:
18
The loss for epoch 6
0.9248242508620024
The running loss is:
15.990774627774954
The number of items in train is:
18
The loss for epoch 7
0.8883763682097197
The running loss is:
15.255841538310051
The number of items in train is:
18
The loss for epoch 8
0.8475467521283362
The running loss is:
15.562775813043118
The number of items in train is:
18
The loss for epoch 9
0.8645986562801732
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.490562
47 30819 ... 5.109116
48 30820 ... 4.521112
49 30821 ... 4.500493
50 30822 ... 4.532074
51 30823 ... 7.254538
52 30824 ... 9.073475
53 30825 ... 11.282241
54 30826 ... 12.836247
55 30827 ... 11.248981
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 05s9xxu7 wandb: Agent Starting Run: q1pw4m4o with config: batch_size: 2 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: q1pw4m4o
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.18984922982054
The number of items in train is:
19
The loss for epoch 0
0.9573604857800283
The running loss is:
31.015213429927826
The number of items in train is:
19
The loss for epoch 1
1.6323796542067277
The running loss is:
25.05902342684567
The number of items in train is:
19
The loss for epoch 2
1.3188959698339826
The running loss is:
17.705750689841807
The number of items in train is:
19
The loss for epoch 3
0.9318816152548319
The running loss is:
19.256243493407965
The number of items in train is:
19
The loss for epoch 4
1.0134864996530508
The running loss is:
16.12529268709477
The number of items in train is:
19
The loss for epoch 5
0.848699615110251
The running loss is:
16.88124701194465
The number of items in train is:
19
The loss for epoch 6
0.8884866848391922
The running loss is:
17.862726697698236
The number of items in train is:
19
The loss for epoch 7
0.9401435104051703
The running loss is:
16.728870145976543
The number of items in train is:
19
The loss for epoch 8
0.8804668497882391
The running loss is:
11.848636295646429
The number of items in train is:
19
The loss for epoch 9
0.62361243661297
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.103765
47 30819 Eagle County, Colorado, United States ... 47 1.870756
48 30820 Eagle County, Colorado, United States ... 48 2.080886
49 30821 Eagle County, Colorado, United States ... 49 2.155844
50 30822 Eagle County, Colorado, United States ... 50 2.076065
51 30823 Eagle County, Colorado, United States ... 51 2.572889
52 30824 Eagle County, Colorado, United States ... 52 1.959953
53 30825 Eagle County, Colorado, United States ... 53 3.224896
54 30826 Eagle County, Colorado, United States ... 54 3.106375
55 30827 Eagle County, Colorado, United States ... 55 3.125867
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: q1pw4m4o wandb: Agent Starting Run: 4c1kh057 with config: batch_size: 2 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4c1kh057
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.494125075638294
The number of items in train is:
18
The loss for epoch 0
0.9718958375354608
The running loss is:
28.09664772450924
The number of items in train is:
18
The loss for epoch 1
1.5609248735838466
The running loss is:
24.013664718717337
The number of items in train is:
18
The loss for epoch 2
1.3340924843731854
The running loss is:
18.162125043570995
The number of items in train is:
18
The loss for epoch 3
1.0090069468650553
The running loss is:
16.80295354872942
The number of items in train is:
18
The loss for epoch 4
0.9334974193738567
The running loss is:
17.79146870970726
The number of items in train is:
18
The loss for epoch 5
0.98841492831707
The running loss is:
17.33954283967614
The number of items in train is:
18
The loss for epoch 6
0.9633079355375634
The running loss is:
16.02283275872469
The number of items in train is:
18
The loss for epoch 7
0.890157375484705
The running loss is:
16.078760348260403
The number of items in train is:
18
The loss for epoch 8
0.8932644637922446
The running loss is:
13.699175633490086
The number of items in train is:
18
The loss for epoch 9
0.7610653129716715
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.590535
47 30819 ... 6.649212
48 30820 ... 6.258964
49 30821 ... 6.280522
50 30822 ... 6.141128
51 30823 ... 8.359175
52 30824 ... 8.270262
53 30825 ... 10.945897
54 30826 ... 11.430916
55 30827 ... 11.242756
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4c1kh057 wandb: Agent Starting Run: 84tk4dxu with config: batch_size: 2 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 84tk4dxu
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.54656159132719
The number of items in train is:
18
The loss for epoch 0
1.0303645328515105
The running loss is:
29.21507738530636
The number of items in train is:
18
The loss for epoch 1
1.623059854739242
The running loss is:
23.851110816001892
The number of items in train is:
18
The loss for epoch 2
1.3250617120001051
The running loss is:
19.94340915977955
The number of items in train is:
18
The loss for epoch 3
1.1079671755433083
The running loss is:
19.323927462100983
The number of items in train is:
18
The loss for epoch 4
1.0735515256722767
The running loss is:
18.458923548460007
The number of items in train is:
18
The loss for epoch 5
1.0254957526922226
The running loss is:
17.79984922707081
The number of items in train is:
18
The loss for epoch 6
0.988880512615045
The running loss is:
16.900932855904102
The number of items in train is:
18
The loss for epoch 7
0.9389407142168946
The running loss is:
16.755262605845928
The number of items in train is:
18
The loss for epoch 8
0.930847922546996
The running loss is:
18.575405955314636
The number of items in train is:
18
The loss for epoch 9
1.03196699751748
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 3.838975
47 30819 ... 2.985913
48 30820 ... 4.822277
49 30821 ... 5.249653
50 30822 ... 5.096822
51 30823 ... 7.568799
52 30824 ... 8.716757
53 30825 ... 9.766637
54 30826 ... 9.079391
55 30827 ... 10.247148
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 84tk4dxu wandb: Agent Starting Run: 3cso2ma6 with config: batch_size: 2 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3cso2ma6
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.242283281870186
The number of items in train is:
19
The loss for epoch 0
1.1706464885194834
The running loss is:
24.795687010977417
The number of items in train is:
19
The loss for epoch 1
1.3050361584724957
The running loss is:
27.57364009693265
The number of items in train is:
19
The loss for epoch 2
1.4512442156280343
The running loss is:
20.696718683699146
The number of items in train is:
19
The loss for epoch 3
1.0893009833525866
The running loss is:
20.01832439377904
The number of items in train is:
19
The loss for epoch 4
1.0535960207252126
The running loss is:
21.98695570975542
The number of items in train is:
19
The loss for epoch 5
1.1572081952502853
The running loss is:
20.906687308102846
The number of items in train is:
19
The loss for epoch 6
1.1003519635843604
The running loss is:
19.587092012166977
The number of items in train is:
19
The loss for epoch 7
1.0308995795877356
The running loss is:
18.418085638433695
The number of items in train is:
19
The loss for epoch 8
0.9693729283386155
The running loss is:
16.86983137577772
The number of items in train is:
19
The loss for epoch 9
0.887885861883038
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.581883
47 30819 ... 9.565614
48 30820 ... 9.369929
49 30821 ... 9.071023
50 30822 ... 9.034859
51 30823 ... 10.051611
52 30824 ... 10.008867
53 30825 ... 11.184799
54 30826 ... 11.403122
55 30827 ... 11.031343
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3cso2ma6 wandb: Agent Starting Run: twuvsomh with config: batch_size: 2 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: twuvsomh
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.412616685032845
The number of items in train is:
18
The loss for epoch 0
1.189589815835158
The running loss is:
22.069864347577095
The number of items in train is:
18
The loss for epoch 1
1.2261035748653941
The running loss is:
26.440984159708023
The number of items in train is:
18
The loss for epoch 2
1.4689435644282236
The running loss is:
20.751066893339157
The number of items in train is:
18
The loss for epoch 3
1.1528370496299531
The running loss is:
18.370464075356722
The number of items in train is:
18
The loss for epoch 4
1.0205813375198178
The running loss is:
18.27291965484619
The number of items in train is:
18
The loss for epoch 5
1.0151622030470107
The running loss is:
20.864477939903736
The number of items in train is:
18
The loss for epoch 6
1.1591376633279853
The running loss is:
18.746755480766296
The number of items in train is:
18
The loss for epoch 7
1.0414864155981276
The running loss is:
18.56461740285158
The number of items in train is:
18
The loss for epoch 8
1.0313676334917545
The running loss is:
18.1154655367136
The number of items in train is:
18
The loss for epoch 9
1.0064147520396445
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.008367
47 30819 ... 15.284899
48 30820 ... 12.420164
49 30821 ... 11.182684
50 30822 ... 9.871691
51 30823 ... 10.450293
52 30824 ... 11.239236
53 30825 ... 11.804643
54 30826 ... 14.075599
55 30827 ... 12.123839
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: twuvsomh wandb: Agent Starting Run: 4dfdcpti with config: batch_size: 2 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 4dfdcpti
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.670164734125137
The number of items in train is:
18
The loss for epoch 0
1.20389804078473
The running loss is:
25.513697922229767
The number of items in train is:
18
The loss for epoch 1
1.4174276623460982
The running loss is:
22.322134003043175
The number of items in train is:
18
The loss for epoch 2
1.2401185557246208
The running loss is:
20.4907748401165
The number of items in train is:
18
The loss for epoch 3
1.1383763800064723
The running loss is:
18.35349614918232
The number of items in train is:
18
The loss for epoch 4
1.0196386749545734
The running loss is:
18.696768805384636
The number of items in train is:
18
The loss for epoch 5
1.0387093780769243
The running loss is:
17.7908186763525
The number of items in train is:
18
The loss for epoch 6
0.9883788153529167
The running loss is:
18.77002341300249
The number of items in train is:
18
The loss for epoch 7
1.0427790785001383
The running loss is:
17.80537621676922
The number of items in train is:
18
The loss for epoch 8
0.98918756759829
The running loss is:
18.945369634777308
The number of items in train is:
18
The loss for epoch 9
1.052520535265406
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.815019
47 30819 ... 10.132872
48 30820 ... 9.367234
49 30821 ... 9.324808
50 30822 ... 9.046239
51 30823 ... 10.439740
52 30824 ... 10.854648
53 30825 ... 11.246872
54 30826 ... 10.885998
55 30827 ... 9.790585
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4dfdcpti wandb: Agent Starting Run: z6gn81nx with config: batch_size: 2 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: z6gn81nx
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
54.29879327118397
The number of items in train is:
19
The loss for epoch 0
2.857831224799156
The running loss is:
25.204199893400073
The number of items in train is:
19
The loss for epoch 1
1.3265368364947407
The running loss is:
24.917403297498822
The number of items in train is:
19
The loss for epoch 2
1.3114422788157274
The running loss is:
26.80236802622676
The number of items in train is:
19
The loss for epoch 3
1.4106509487487768
The running loss is:
38.15466159582138
The number of items in train is:
19
The loss for epoch 4
2.008140083990599
The running loss is:
25.13397454470396
The number of items in train is:
19
The loss for epoch 5
1.3228407655107348
The running loss is:
32.146171571686864
The number of items in train is:
19
The loss for epoch 6
1.6919037669308876
The running loss is:
24.309386016801
The number of items in train is:
19
The loss for epoch 7
1.2794413693053157
The running loss is:
22.214474976062775
The number of items in train is:
19
The loss for epoch 8
1.1691828934769881
The running loss is:
20.81675188243389
The number of items in train is:
19
The loss for epoch 9
1.0956185201280995
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.340683
47 30819 ... 11.081213
48 30820 ... 11.072694
49 30821 ... 10.951793
50 30822 ... 10.874124
51 30823 ... 10.559611
52 30824 ... 10.377087
53 30825 ... 10.069571
54 30826 ... 11.455525
55 30827 ... 11.084692
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z6gn81nx wandb: Agent Starting Run: p4yuqpwz with config: batch_size: 2 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: p4yuqpwz
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
58.09991538524628
The number of items in train is:
18
The loss for epoch 0
3.2277730769581265
The running loss is:
29.909697026014328
The number of items in train is:
18
The loss for epoch 1
1.6616498347785738
The running loss is:
23.141397207975388
The number of items in train is:
18
The loss for epoch 2
1.2856331782208548
The running loss is:
19.834211759269238
The number of items in train is:
18
The loss for epoch 3
1.1019006532927353
The running loss is:
17.75834746658802
The number of items in train is:
18
The loss for epoch 4
0.98657485925489
The running loss is:
18.921377703547478
The number of items in train is:
18
The loss for epoch 5
1.051187650197082
The running loss is:
20.49680781364441
The number of items in train is:
18
The loss for epoch 6
1.1387115452024672
The running loss is:
19.066853269934654
The number of items in train is:
18
The loss for epoch 7
1.0592696261074808
The running loss is:
18.26368085294962
The number of items in train is:
18
The loss for epoch 8
1.0146489362749789
The running loss is:
17.676290668547153
The number of items in train is:
18
The loss for epoch 9
0.9820161482526196
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.354430
47 30819 ... 14.269297
48 30820 ... 12.166956
49 30821 ... 11.732918
50 30822 ... 10.295154
51 30823 ... 8.951567
52 30824 ... 10.023297
53 30825 ... 10.744930
54 30826 ... 14.557074
55 30827 ... 12.767807
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: p4yuqpwz wandb: Agent Starting Run: 3pth17fj with config: batch_size: 2 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3pth17fj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
53.13939993083477
The number of items in train is:
18
The loss for epoch 0
2.952188885046376
The running loss is:
23.89207072556019
The number of items in train is:
18
The loss for epoch 1
1.3273372625311215
The running loss is:
21.42414081096649
The number of items in train is:
18
The loss for epoch 2
1.190230045053694
The running loss is:
19.368080615997314
The number of items in train is:
18
The loss for epoch 3
1.0760044786665175
The running loss is:
18.88629299402237
The number of items in train is:
18
The loss for epoch 4
1.0492384996679094
The running loss is:
18.86470042169094
The number of items in train is:
18
The loss for epoch 5
1.0480389123161633
The running loss is:
18.934682935476303
The number of items in train is:
18
The loss for epoch 6
1.0519268297486835
The running loss is:
19.125713765621185
The number of items in train is:
18
The loss for epoch 7
1.0625396536456213
The running loss is:
18.64470000565052
The number of items in train is:
18
The loss for epoch 8
1.0358166669805844
The running loss is:
19.651452392339706
The number of items in train is:
18
The loss for epoch 9
1.0917473551299837
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.818055
47 30819 ... 12.139648
48 30820 ... 11.247300
49 30821 ... 10.832371
50 30822 ... 10.382744
51 30823 ... 10.604967
52 30824 ... 10.664228
53 30825 ... 11.099741
54 30826 ... 11.873261
55 30827 ... 9.890029
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3pth17fj wandb: Agent Starting Run: h3sok6h3 with config: batch_size: 2 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: h3sok6h3
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.83428485947661
The number of items in train is:
18
The loss for epoch 0
1.0463491588598117
The running loss is:
30.694389076903462
The number of items in train is:
18
The loss for epoch 1
1.705243837605748
The running loss is:
22.378335297107697
The number of items in train is:
18
The loss for epoch 2
1.2432408498393164
The running loss is:
19.81809677183628
The number of items in train is:
18
The loss for epoch 3
1.1010053762131267
The running loss is:
17.860943913459778
The number of items in train is:
18
The loss for epoch 4
0.9922746618588766
The running loss is:
17.826664086431265
The number of items in train is:
18
The loss for epoch 5
0.9903702270239592
The running loss is:
16.915876930579543
The number of items in train is:
18
The loss for epoch 6
0.9397709405877523
The running loss is:
16.87274954468012
The number of items in train is:
18
The loss for epoch 7
0.9373749747044511
The running loss is:
16.296894021332264
The number of items in train is:
18
The loss for epoch 8
0.9053830011851258
The running loss is:
15.18472127057612
The number of items in train is:
18
The loss for epoch 9
0.8435956261431178
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.589013
47 30819 ... 5.464175
48 30820 ... 7.635145
49 30821 ... 6.665916
50 30822 ... 6.748456
51 30823 ... 6.279453
52 30824 ... 10.910107
53 30825 ... 10.739932
54 30826 ... 12.164768
55 30827 ... 14.138649
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: h3sok6h3 wandb: Agent Starting Run: ti0jhceq with config: batch_size: 2 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ti0jhceq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.50762452557683
The number of items in train is:
18
The loss for epoch 0
1.028201362532046
The running loss is:
30.229473516345024
The number of items in train is:
18
The loss for epoch 1
1.6794151953525014
The running loss is:
20.547360464930534
The number of items in train is:
18
The loss for epoch 2
1.1415200258294742
The running loss is:
18.828258499503136
The number of items in train is:
18
The loss for epoch 3
1.0460143610835075
The running loss is:
17.361575104296207
The number of items in train is:
18
The loss for epoch 4
0.9645319502386782
The running loss is:
17.0721765011549
The number of items in train is:
18
The loss for epoch 5
0.9484542500641611
The running loss is:
15.66090652346611
The number of items in train is:
18
The loss for epoch 6
0.870050362414784
The running loss is:
16.027198612689972
The number of items in train is:
18
The loss for epoch 7
0.8903999229272207
The running loss is:
15.154059939086437
The number of items in train is:
18
The loss for epoch 8
0.8418922188381354
The running loss is:
14.604415582492948
The number of items in train is:
18
The loss for epoch 9
0.8113564212496082
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.798800
47 30819 ... 4.839271
48 30820 ... 6.942317
49 30821 ... 6.201822
50 30822 ... 6.283172
51 30823 ... 5.738673
52 30824 ... 11.060683
53 30825 ... 12.862118
54 30826 ... 14.975395
55 30827 ... 16.912077
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ti0jhceq wandb: Agent Starting Run: tq5g8c8y with config: batch_size: 2 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: tq5g8c8y
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.326459631323814
The number of items in train is:
17
The loss for epoch 0
1.1956740959602243
The running loss is:
26.52370758354664
The number of items in train is:
17
The loss for epoch 1
1.5602180931498022
The running loss is:
20.00117264688015
The number of items in train is:
17
The loss for epoch 2
1.1765395674635382
The running loss is:
18.83174880594015
The number of items in train is:
17
The loss for epoch 3
1.1077499297611855
The running loss is:
18.203551523387432
The number of items in train is:
17
The loss for epoch 4
1.0707971484345549
The running loss is:
17.697747506201267
The number of items in train is:
17
The loss for epoch 5
1.0410439709530157
The running loss is:
17.05414705723524
The number of items in train is:
17
The loss for epoch 6
1.0031851210138376
The running loss is:
16.714102994650602
The number of items in train is:
17
The loss for epoch 7
0.9831825290970942
The running loss is:
16.31566223502159
The number of items in train is:
17
The loss for epoch 8
0.9597448373542112
The running loss is:
16.255682721734047
The number of items in train is:
17
The loss for epoch 9
0.9562166306902381
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.511676
47 30819 Eagle County, Colorado, United States ... 47 0.885248
48 30820 Eagle County, Colorado, United States ... 48 1.917389
49 30821 Eagle County, Colorado, United States ... 49 1.170372
50 30822 Eagle County, Colorado, United States ... 50 1.376424
51 30823 Eagle County, Colorado, United States ... 51 0.887287
52 30824 Eagle County, Colorado, United States ... 52 5.287897
53 30825 Eagle County, Colorado, United States ... 53 3.549723
54 30826 Eagle County, Colorado, United States ... 54 3.942515
55 30827 Eagle County, Colorado, United States ... 55 5.333583
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tq5g8c8y wandb: Agent Starting Run: onfqi4iq with config: batch_size: 2 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: onfqi4iq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.58739176625386
The number of items in train is:
18
The loss for epoch 0
1.0326328759029921
The running loss is:
25.453700333833694
The number of items in train is:
18
The loss for epoch 1
1.4140944629907608
The running loss is:
24.478219382464886
The number of items in train is:
18
The loss for epoch 2
1.3599010768036048
The running loss is:
18.617552369832993
The number of items in train is:
18
The loss for epoch 3
1.0343084649907217
The running loss is:
18.47619041055441
The number of items in train is:
18
The loss for epoch 4
1.0264550228085783
The running loss is:
17.632004007697105
The number of items in train is:
18
The loss for epoch 5
0.9795557782053947
The running loss is:
17.34126414358616
The number of items in train is:
18
The loss for epoch 6
0.9634035635325644
The running loss is:
17.196547646075487
The number of items in train is:
18
The loss for epoch 7
0.9553637581153048
The running loss is:
16.807551510632038
The number of items in train is:
18
The loss for epoch 8
0.9337528617017798
The running loss is:
15.813888244330883
The number of items in train is:
18
The loss for epoch 9
0.8785493469072713
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.189288
47 30819 ... 6.000010
48 30820 ... 9.140032
49 30821 ... 8.488817
50 30822 ... 7.783149
51 30823 ... 6.252083
52 30824 ... 8.576809
53 30825 ... 8.205903
54 30826 ... 10.083464
55 30827 ... 12.833640
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: onfqi4iq wandb: Agent Starting Run: jaqkg5qo with config: batch_size: 2 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: jaqkg5qo
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.67767819389701
The number of items in train is:
18
The loss for epoch 0
0.9820932329942783
The running loss is:
28.929249703884125
The number of items in train is:
18
The loss for epoch 1
1.6071805391046736
The running loss is:
25.189696937799454
The number of items in train is:
18
The loss for epoch 2
1.3994276076555252
The running loss is:
19.118132956326008
The number of items in train is:
18
The loss for epoch 3
1.062118497573667
The running loss is:
18.119125105440617
The number of items in train is:
18
The loss for epoch 4
1.0066180614133675
The running loss is:
17.72756700590253
The number of items in train is:
18
The loss for epoch 5
0.9848648336612515
The running loss is:
17.2081276550889
The number of items in train is:
18
The loss for epoch 6
0.9560070919493834
The running loss is:
17.779209829866886
The number of items in train is:
18
The loss for epoch 7
0.9877338794370493
The running loss is:
16.979998294264078
The number of items in train is:
18
The loss for epoch 8
0.9433332385702266
The running loss is:
17.875624038279057
The number of items in train is:
18
The loss for epoch 9
0.9930902243488364
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.322368
47 30819 ... 5.418035
48 30820 ... 6.938383
49 30821 ... 6.316636
50 30822 ... 6.411837
51 30823 ... 5.790046
52 30824 ... 9.559429
53 30825 ... 9.863681
54 30826 ... 10.531605
55 30827 ... 11.683816
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jaqkg5qo wandb: Agent Starting Run: 76w7wtbu with config: batch_size: 2 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 76w7wtbu
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.189144864678383
The number of items in train is:
17
The loss for epoch 0
1.0699496979222578
The running loss is:
25.82771911472082
The number of items in train is:
17
The loss for epoch 1
1.5192775949835777
The running loss is:
22.746037542819977
The number of items in train is:
17
The loss for epoch 2
1.3380022084011751
The running loss is:
18.930177986621857
The number of items in train is:
17
The loss for epoch 3
1.1135398815659916
The running loss is:
18.611469365656376
The number of items in train is:
17
The loss for epoch 4
1.0947923156268455
The running loss is:
18.261943750083447
The number of items in train is:
17
The loss for epoch 5
1.0742319852990263
The running loss is:
17.79456951469183
The number of items in train is:
17
The loss for epoch 6
1.0467393832171665
The running loss is:
17.808585457503796
The number of items in train is:
17
The loss for epoch 7
1.0475638504413998
The running loss is:
16.707562319934368
The number of items in train is:
17
The loss for epoch 8
0.982797783525551
The running loss is:
16.852712512016296
The number of items in train is:
17
The loss for epoch 9
0.9913360301186057
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.346636
47 30819 ... 3.546402
48 30820 ... 5.990652
49 30821 ... 4.534712
50 30822 ... 5.614292
51 30823 ... 4.396796
52 30824 ... 10.686534
53 30825 ... 12.141682
54 30826 ... 15.663172
55 30827 ... 16.982374
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 76w7wtbu wandb: Agent Starting Run: 7lzkogad with config: batch_size: 2 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 7lzkogad
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
25.985687144100666
The number of items in train is:
18
The loss for epoch 0
1.4436492857833703
The running loss is:
25.533394917845726
The number of items in train is:
18
The loss for epoch 1
1.4185219398803182
The running loss is:
24.65770325437188
The number of items in train is:
18
The loss for epoch 2
1.3698724030206602
The running loss is:
20.977828606963158
The number of items in train is:
18
The loss for epoch 3
1.1654349226090643
The running loss is:
18.592061333358288
The number of items in train is:
18
The loss for epoch 4
1.0328922962976828
The running loss is:
18.60237979888916
The number of items in train is:
18
The loss for epoch 5
1.0334655443827312
The running loss is:
17.721400048583746
The number of items in train is:
18
The loss for epoch 6
0.9845222249213192
The running loss is:
18.594129770994186
The number of items in train is:
18
The loss for epoch 7
1.033007209499677
The running loss is:
17.56918104365468
The number of items in train is:
18
The loss for epoch 8
0.9760656135363711
The running loss is:
19.658490262925625
The number of items in train is:
18
The loss for epoch 9
1.0921383479403124
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.338434
47 30819 ... 9.948380
48 30820 ... 11.497427
49 30821 ... 10.225165
50 30822 ... 9.329464
51 30823 ... 9.572168
52 30824 ... 10.839942
53 30825 ... 10.214510
54 30826 ... 10.921080
55 30827 ... 12.323168
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7lzkogad wandb: Agent Starting Run: ldu1i9ut with config: batch_size: 2 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ldu1i9ut
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.17583403736353
The number of items in train is:
18
The loss for epoch 0
1.287546335409085
The running loss is:
25.385982364416122
The number of items in train is:
18
The loss for epoch 1
1.4103323535786734
The running loss is:
23.672232568264008
The number of items in train is:
18
The loss for epoch 2
1.3151240315702226
The running loss is:
21.137772634625435
The number of items in train is:
18
The loss for epoch 3
1.1743207019236352
The running loss is:
18.826060451567173
The number of items in train is:
18
The loss for epoch 4
1.0458922473092873
The running loss is:
18.50016212463379
The number of items in train is:
18
The loss for epoch 5
1.0277867847018771
The running loss is:
17.455230563879013
The number of items in train is:
18
The loss for epoch 6
0.9697350313266119
The running loss is:
18.82326005399227
The number of items in train is:
18
The loss for epoch 7
1.0457366696662374
The running loss is:
17.129642881453037
The number of items in train is:
18
The loss for epoch 8
0.951646826747391
The running loss is:
17.606110781431198
The number of items in train is:
18
The loss for epoch 9
0.9781172656350665
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.194985
47 30819 ... 9.862240
48 30820 ... 16.316151
49 30821 ... 12.624606
50 30822 ... 12.543795
51 30823 ... 8.049689
52 30824 ... 13.099211
53 30825 ... 13.100273
54 30826 ... 14.972973
55 30827 ... 17.187275
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ldu1i9ut wandb: Agent Starting Run: z1khalb3 with config: batch_size: 2 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: z1khalb3
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.20541825890541
The number of items in train is:
17
The loss for epoch 0
1.2473775446414948
The running loss is:
26.331035990267992
The number of items in train is:
17
The loss for epoch 1
1.5488844700157642
The running loss is:
21.423548463732004
The number of items in train is:
17
The loss for epoch 2
1.2602087331607061
The running loss is:
19.311860531568527
The number of items in train is:
17
The loss for epoch 3
1.1359917959746193
The running loss is:
18.42611952126026
The number of items in train is:
17
The loss for epoch 4
1.0838893836035448
The running loss is:
18.355855636298656
The number of items in train is:
17
The loss for epoch 5
1.079756213899921
The running loss is:
18.343623392283916
The number of items in train is:
17
The loss for epoch 6
1.0790366701343481
The running loss is:
18.220871716737747
The number of items in train is:
17
The loss for epoch 7
1.0718159833375145
The running loss is:
18.014991000294685
The number of items in train is:
17
The loss for epoch 8
1.059705352958511
The running loss is:
18.06001925468445
The number of items in train is:
17
The loss for epoch 9
1.0623540738049675
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.165402
47 30819 Eagle County, Colorado, United States ... 47 9.069475
48 30820 Eagle County, Colorado, United States ... 48 8.965014
49 30821 Eagle County, Colorado, United States ... 49 8.994439
50 30822 Eagle County, Colorado, United States ... 50 9.027403
51 30823 Eagle County, Colorado, United States ... 51 8.972231
52 30824 Eagle County, Colorado, United States ... 52 9.810741
53 30825 Eagle County, Colorado, United States ... 53 9.936197
54 30826 Eagle County, Colorado, United States ... 54 9.907127
55 30827 Eagle County, Colorado, United States ... 55 9.882858
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z1khalb3 wandb: Agent Starting Run: ok5falth with config: batch_size: 2 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ok5falth
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
91.93867326527834
The number of items in train is:
18
The loss for epoch 0
5.1077040702932415
The running loss is:
41.00077871978283
The number of items in train is:
18
The loss for epoch 1
2.277821039987935
The running loss is:
22.16812052205205
The number of items in train is:
18
The loss for epoch 2
1.2315622512251139
The running loss is:
24.294399526901543
The number of items in train is:
18
The loss for epoch 3
1.3496888626056414
The running loss is:
20.05660403892398
The number of items in train is:
18
The loss for epoch 4
1.114255779940221
The running loss is:
20.849789410829544
The number of items in train is:
18
The loss for epoch 5
1.1583216339349747
The running loss is:
19.57541885972023
The number of items in train is:
18
The loss for epoch 6
1.0875232699844573
The running loss is:
18.560163848102093
The number of items in train is:
18
The loss for epoch 7
1.0311202137834496
The running loss is:
19.261560007929802
The number of items in train is:
18
The loss for epoch 8
1.0700866671072111
The running loss is:
18.674716770648956
The number of items in train is:
18
The loss for epoch 9
1.0374842650360532
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.174484
47 30819 ... 11.524269
48 30820 ... 11.487882
49 30821 ... 11.509277
50 30822 ... 11.597288
51 30823 ... 11.396919
52 30824 ... 11.390881
53 30825 ... 11.174414
54 30826 ... 11.205681
55 30827 ... 11.476442
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ok5falth wandb: Agent Starting Run: jdb0w9lf with config: batch_size: 2 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: jdb0w9lf
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
71.70084895193577
The number of items in train is:
18
The loss for epoch 0
3.983380497329765
The running loss is:
34.523087076842785
The number of items in train is:
18
The loss for epoch 1
1.9179492820468214
The running loss is:
20.573708325624466
The number of items in train is:
18
The loss for epoch 2
1.1429837958680258
The running loss is:
18.896047294139862
The number of items in train is:
18
The loss for epoch 3
1.0497804052299924
The running loss is:
18.512571424245834
The number of items in train is:
18
The loss for epoch 4
1.0284761902358797
The running loss is:
18.70388262718916
The number of items in train is:
18
The loss for epoch 5
1.0391045903993978
The running loss is:
18.608287632465363
The number of items in train is:
18
The loss for epoch 6
1.0337937573591869
The running loss is:
19.012116946280003
The number of items in train is:
18
The loss for epoch 7
1.056228719237778
The running loss is:
18.82577931880951
The number of items in train is:
18
The loss for epoch 8
1.0458766288227506
The running loss is:
18.978907726705074
The number of items in train is:
18
The loss for epoch 9
1.0543837625947263
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.771688
47 30819 ... 10.069174
48 30820 ... 10.424778
49 30821 ... 10.578030
50 30822 ... 9.966643
51 30823 ... 9.754827
52 30824 ... 9.886961
53 30825 ... 9.548673
54 30826 ... 9.559739
55 30827 ... 9.601932
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jdb0w9lf wandb: Agent Starting Run: f8rga1l5 with config: batch_size: 2 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: f8rga1l5
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
60.02559678256512
The number of items in train is:
17
The loss for epoch 0
3.530917457797948
The running loss is:
21.879589214920998
The number of items in train is:
17
The loss for epoch 1
1.2870346597012352
The running loss is:
22.272070422768593
The number of items in train is:
17
The loss for epoch 2
1.310121789574623
The running loss is:
20.273326992988586
The number of items in train is:
17
The loss for epoch 3
1.1925486466463875
The running loss is:
18.233934313058853
The number of items in train is:
17
The loss for epoch 4
1.0725843713564032
The running loss is:
18.1911773532629
The number of items in train is:
17
The loss for epoch 5
1.0700692560742884
The running loss is:
17.973187312483788
The number of items in train is:
17
The loss for epoch 6
1.0572463124990463
The running loss is:
17.894800126552582
The number of items in train is:
17
The loss for epoch 7
1.0526353015619165
The running loss is:
18.38982318341732
The number of items in train is:
17
The loss for epoch 8
1.0817543049069012
The running loss is:
18.14912710338831
The number of items in train is:
17
The loss for epoch 9
1.0675957119640183
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.190907
47 30819 ... 10.166980
48 30820 ... 10.167084
49 30821 ... 9.968959
50 30822 ... 10.873432
51 30823 ... 10.553559
52 30824 ... 10.352334
53 30825 ... 10.250555
54 30826 ... 10.249765
55 30827 ... 10.249871
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f8rga1l5 wandb: Agent Starting Run: gr7vy5x5 with config: batch_size: 2 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: gr7vy5x5
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.120445497334003
The number of items in train is:
18
The loss for epoch 0
1.0066914165185556
The running loss is:
36.88737970899092
The number of items in train is:
18
The loss for epoch 1
2.049298872721718
The running loss is:
25.769994165748358
The number of items in train is:
18
The loss for epoch 2
1.4316663425415754
The running loss is:
22.722472186665982
The number of items in train is:
18
The loss for epoch 3
1.262359565925888
The running loss is:
20.244089771062136
The number of items in train is:
18
The loss for epoch 4
1.1246716539478965
The running loss is:
18.204342804849148
The number of items in train is:
18
The loss for epoch 5
1.011352378047175
The running loss is:
16.84917761210818
The number of items in train is:
18
The loss for epoch 6
0.9360654228948988
The running loss is:
16.967705154791474
The number of items in train is:
18
The loss for epoch 7
0.9426502863773041
The running loss is:
15.167392913252115
The number of items in train is:
18
The loss for epoch 8
0.8426329396251175
The running loss is:
14.847127000335604
The number of items in train is:
18
The loss for epoch 9
0.8248403889075335
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.234351
47 30819 Eagle County, Colorado, United States ... 47 5.589938
48 30820 Eagle County, Colorado, United States ... 48 4.432260
49 30821 Eagle County, Colorado, United States ... 49 3.562717
50 30822 Eagle County, Colorado, United States ... 50 3.846261
51 30823 Eagle County, Colorado, United States ... 51 4.097902
52 30824 Eagle County, Colorado, United States ... 52 4.603130
53 30825 Eagle County, Colorado, United States ... 53 6.944318
54 30826 Eagle County, Colorado, United States ... 54 8.064589
55 30827 Eagle County, Colorado, United States ... 55 7.837166
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gr7vy5x5 wandb: Agent Starting Run: d51fuypy with config: batch_size: 2 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: d51fuypy
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.863892681896687
The number of items in train is:
17
The loss for epoch 0
1.050817216582158
The running loss is:
30.557269416749477
The number of items in train is:
17
The loss for epoch 1
1.797486436279381
The running loss is:
24.31645315885544
The number of items in train is:
17
The loss for epoch 2
1.4303795975797318
The running loss is:
21.716937102377415
The number of items in train is:
17
The loss for epoch 3
1.277466888375142
The running loss is:
18.302996151149273
The number of items in train is:
17
The loss for epoch 4
1.0766468324205454
The running loss is:
17.990163557231426
The number of items in train is:
17
The loss for epoch 5
1.0582449151312603
The running loss is:
17.505731016397476
The number of items in train is:
17
The loss for epoch 6
1.0297488833174986
The running loss is:
16.266479892656207
The number of items in train is:
17
The loss for epoch 7
0.9568517583915416
The running loss is:
14.844720372930169
The number of items in train is:
17
The loss for epoch 8
0.8732188454664805
The running loss is:
13.61546167358756
The number of items in train is:
17
The loss for epoch 9
0.800909510211033
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.055187
47 30819 Eagle County, Colorado, United States ... 47 5.612241
48 30820 Eagle County, Colorado, United States ... 48 4.139591
49 30821 Eagle County, Colorado, United States ... 49 3.982578
50 30822 Eagle County, Colorado, United States ... 50 2.636002
51 30823 Eagle County, Colorado, United States ... 51 3.206338
52 30824 Eagle County, Colorado, United States ... 52 3.745330
53 30825 Eagle County, Colorado, United States ... 53 6.512134
54 30826 Eagle County, Colorado, United States ... 54 8.213514
55 30827 Eagle County, Colorado, United States ... 55 8.196659
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: d51fuypy wandb: Agent Starting Run: fquo39qu with config: batch_size: 2 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: fquo39qu
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.315565809607506
The number of items in train is:
17
The loss for epoch 0
1.1362097535063238
The running loss is:
27.744996145367622
The number of items in train is:
17
The loss for epoch 1
1.6320585967863308
The running loss is:
20.23160046339035
The number of items in train is:
17
The loss for epoch 2
1.1900941449053146
The running loss is:
18.820374861359596
The number of items in train is:
17
The loss for epoch 3
1.1070808741976232
The running loss is:
17.80506058037281
The number of items in train is:
17
The loss for epoch 4
1.0473565047278124
The running loss is:
17.640491649508476
The number of items in train is:
17
The loss for epoch 5
1.0376759793828516
The running loss is:
17.346722543239594
The number of items in train is:
17
The loss for epoch 6
1.020395443719976
The running loss is:
16.878471672534943
The number of items in train is:
17
The loss for epoch 7
0.9928512748549966
The running loss is:
16.163867503404617
The number of items in train is:
17
The loss for epoch 8
0.9508157354943892
The running loss is:
15.284686610102654
The number of items in train is:
17
The loss for epoch 9
0.8990992123589796
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.138500
47 30819 Eagle County, Colorado, United States ... 47 2.068359
48 30820 Eagle County, Colorado, United States ... 48 0.579822
49 30821 Eagle County, Colorado, United States ... 49 0.431010
50 30822 Eagle County, Colorado, United States ... 50 0.268291
51 30823 Eagle County, Colorado, United States ... 51 0.398433
52 30824 Eagle County, Colorado, United States ... 52 0.306655
53 30825 Eagle County, Colorado, United States ... 53 0.049325
54 30826 Eagle County, Colorado, United States ... 54 -0.512394
55 30827 Eagle County, Colorado, United States ... 55 -1.082926
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fquo39qu wandb: Agent Starting Run: nf5ma7q9 with config: batch_size: 2 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: nf5ma7q9
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.964837659150362
The number of items in train is:
18
The loss for epoch 0
1.1647132032861311
The running loss is:
31.43228393420577
The number of items in train is:
18
The loss for epoch 1
1.746237996344765
The running loss is:
27.462910482892767
The number of items in train is:
18
The loss for epoch 2
1.525717249049598
The running loss is:
22.641178257763386
The number of items in train is:
18
The loss for epoch 3
1.2578432365424104
The running loss is:
17.97154197283089
The number of items in train is:
18
The loss for epoch 4
0.9984189984906051
The running loss is:
17.729456153698266
The number of items in train is:
18
The loss for epoch 5
0.9849697863165703
The running loss is:
16.689082900062203
The number of items in train is:
18
The loss for epoch 6
0.927171272225678
The running loss is:
15.960812779143453
The number of items in train is:
18
The loss for epoch 7
0.8867118210635252
The running loss is:
14.336336515843868
The number of items in train is:
18
The loss for epoch 8
0.7964631397691038
The running loss is:
16.482185130473226
The number of items in train is:
18
The loss for epoch 9
0.915676951692957
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.596330
47 30819 ... 8.111716
48 30820 ... 6.830262
49 30821 ... 4.093390
50 30822 ... 4.867238
51 30823 ... 4.692516
52 30824 ... 5.357278
53 30825 ... 9.984414
54 30826 ... 12.083361
55 30827 ... 11.586036
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nf5ma7q9 wandb: Agent Starting Run: c7t70oa7 with config: batch_size: 2 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: c7t70oa7
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.068575020879507
The number of items in train is:
17
The loss for epoch 0
1.1216808835811474
The running loss is:
28.107707070186734
The number of items in train is:
17
The loss for epoch 1
1.6533945335403961
The running loss is:
23.106055334210396
The number of items in train is:
17
The loss for epoch 2
1.359179725541788
The running loss is:
18.721203669905663
The number of items in train is:
17
The loss for epoch 3
1.101247274700333
The running loss is:
17.369276450015604
The number of items in train is:
17
The loss for epoch 4
1.0217221441185649
The running loss is:
16.890567852184176
The number of items in train is:
17
The loss for epoch 5
0.9935628148343634
The running loss is:
14.150886859744787
The number of items in train is:
17
The loss for epoch 6
0.8324051093967522
The running loss is:
14.029157891869545
The number of items in train is:
17
The loss for epoch 7
0.8252445818746791
The running loss is:
20.90973387658596
The number of items in train is:
17
The loss for epoch 8
1.2299843456815271
The running loss is:
16.326852202415466
The number of items in train is:
17
The loss for epoch 9
0.9604030707303215
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 17.318516
47 30819 ... 19.041769
48 30820 ... 18.542461
49 30821 ... 16.740143
50 30822 ... 15.915383
51 30823 ... 16.412432
52 30824 ... 15.848831
53 30825 ... 20.144848
54 30826 ... 20.758886
55 30827 ... 20.443157
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c7t70oa7 wandb: Agent Starting Run: 86o6l336 with config: batch_size: 2 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 86o6l336
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.208781145513058
The number of items in train is:
17
The loss for epoch 0
1.0122812438537092
The running loss is:
27.71545758843422
The number of items in train is:
17
The loss for epoch 1
1.6303210346137775
The running loss is:
22.386159673333168
The number of items in train is:
17
The loss for epoch 2
1.3168329219607746
The running loss is:
18.690160259604454
The number of items in train is:
17
The loss for epoch 3
1.0994211917414385
The running loss is:
18.08047254383564
The number of items in train is:
17
The loss for epoch 4
1.06355720846092
The running loss is:
17.788220658898354
The number of items in train is:
17
The loss for epoch 5
1.0463659211116678
The running loss is:
17.880096539855003
The number of items in train is:
17
The loss for epoch 6
1.0517703846973532
The running loss is:
17.113020420074463
The number of items in train is:
17
The loss for epoch 7
1.0066482600043802
The running loss is:
16.699109718203545
The number of items in train is:
17
The loss for epoch 8
0.9823005716590321
The running loss is:
16.5759494304657
The number of items in train is:
17
The loss for epoch 9
0.9750558488509234
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.256034
47 30819 Eagle County, Colorado, United States ... 47 1.807457
48 30820 Eagle County, Colorado, United States ... 48 2.076961
49 30821 Eagle County, Colorado, United States ... 49 5.788992
50 30822 Eagle County, Colorado, United States ... 50 5.307059
51 30823 Eagle County, Colorado, United States ... 51 4.971756
52 30824 Eagle County, Colorado, United States ... 52 2.691475
53 30825 Eagle County, Colorado, United States ... 53 2.570121
54 30826 Eagle County, Colorado, United States ... 54 1.330946
55 30827 Eagle County, Colorado, United States ... 55 3.026186
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 86o6l336 wandb: Agent Starting Run: 426vphnv with config: batch_size: 2 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 426vphnv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
34.267729624174535
The number of items in train is:
18
The loss for epoch 0
1.9037627568985853
The running loss is:
33.94760421384126
The number of items in train is:
18
The loss for epoch 1
1.88597801188007
The running loss is:
30.238472133874893
The number of items in train is:
18
The loss for epoch 2
1.6799151185486052
The running loss is:
38.51619838178158
The number of items in train is:
18
The loss for epoch 3
2.1397887989878654
The running loss is:
20.47893139347434
The number of items in train is:
18
The loss for epoch 4
1.1377184107485745
The running loss is:
18.94241794757545
The number of items in train is:
18
The loss for epoch 5
1.0523565526430805
The running loss is:
20.30167916836217
The number of items in train is:
18
The loss for epoch 6
1.1278710649090096
The running loss is:
19.38399739563465
The number of items in train is:
18
The loss for epoch 7
1.076888744201925
The running loss is:
19.88887568563223
The number of items in train is:
18
The loss for epoch 8
1.1049375380906794
The running loss is:
19.532415185123682
The number of items in train is:
18
The loss for epoch 9
1.0851341769513156
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.723194
47 30819 Eagle County, Colorado, United States ... 47 9.183539
48 30820 Eagle County, Colorado, United States ... 48 9.319058
49 30821 Eagle County, Colorado, United States ... 49 9.258557
50 30822 Eagle County, Colorado, United States ... 50 9.028840
51 30823 Eagle County, Colorado, United States ... 51 8.666627
52 30824 Eagle County, Colorado, United States ... 52 8.366081
53 30825 Eagle County, Colorado, United States ... 53 8.915517
54 30826 Eagle County, Colorado, United States ... 54 9.048261
55 30827 Eagle County, Colorado, United States ... 55 9.422303
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 426vphnv wandb: Agent Starting Run: scc0pqfm with config: batch_size: 2 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: scc0pqfm
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.23943081498146
The number of items in train is:
17
The loss for epoch 0
1.6611429891165566
The running loss is:
28.07338646426797
The number of items in train is:
17
The loss for epoch 1
1.651375674368704
The running loss is:
23.87537007406354
The number of items in train is:
17
The loss for epoch 2
1.4044335337684435
The running loss is:
21.13710781186819
The number of items in train is:
17
The loss for epoch 3
1.24335928305107
The running loss is:
18.549016206525266
The number of items in train is:
17
The loss for epoch 4
1.0911186003838391
The running loss is:
18.38492915406823
The number of items in train is:
17
The loss for epoch 5
1.081466420827543
The running loss is:
17.49588319659233
The number of items in train is:
17
The loss for epoch 6
1.029169599799549
The running loss is:
17.270923353731632
The number of items in train is:
17
The loss for epoch 7
1.0159366678665667
The running loss is:
16.28042573481798
The number of items in train is:
17
The loss for epoch 8
0.9576721020481166
The running loss is:
14.823214331641793
The number of items in train is:
17
The loss for epoch 9
0.8719537842142231
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.629309
47 30819 ... 8.105134
48 30820 ... 10.640922
49 30821 ... 10.022057
50 30822 ... 8.972525
51 30823 ... 8.227419
52 30824 ... 5.991323
53 30825 ... 9.148765
54 30826 ... 7.008259
55 30827 ... 11.216730
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: scc0pqfm wandb: Agent Starting Run: m3rmcjcn with config: batch_size: 2 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: m3rmcjcn
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.020679511129856
The number of items in train is:
17
The loss for epoch 0
1.2953340888899916
The running loss is:
22.291063234210014
The number of items in train is:
17
The loss for epoch 1
1.3112390137770598
The running loss is:
21.546183705329895
The number of items in train is:
17
The loss for epoch 2
1.2674225709017586
The running loss is:
20.533206969499588
The number of items in train is:
17
The loss for epoch 3
1.207835704088211
The running loss is:
18.27320285141468
The number of items in train is:
17
The loss for epoch 4
1.0748942853773342
The running loss is:
18.226271092891693
The number of items in train is:
17
The loss for epoch 5
1.0721335936995113
The running loss is:
18.01798863708973
The number of items in train is:
17
The loss for epoch 6
1.05988168453469
The running loss is:
18.02622178196907
The number of items in train is:
17
The loss for epoch 7
1.0603659871746511
The running loss is:
17.861629962921143
The number of items in train is:
17
The loss for epoch 8
1.0506841154659496
The running loss is:
18.037888653576374
The number of items in train is:
17
The loss for epoch 9
1.0610522737397867
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.485203
47 30819 ... 9.542734
48 30820 ... 10.885259
49 30821 ... 15.454107
50 30822 ... 12.658281
51 30823 ... 12.965693
52 30824 ... 10.985974
53 30825 ... 9.893891
54 30826 ... 8.056896
55 30827 ... 10.138981
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: m3rmcjcn wandb: Agent Starting Run: yqngqnis with config: batch_size: 2 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yqngqnis
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
137.28573689609766
The number of items in train is:
18
The loss for epoch 0
7.626985383116537
The running loss is:
25.87799007911235
The number of items in train is:
18
The loss for epoch 1
1.4376661155062418
The running loss is:
38.774653896689415
The number of items in train is:
18
The loss for epoch 2
2.1541474387049675
The running loss is:
22.72174153709784
The number of items in train is:
18
The loss for epoch 3
1.2623189742832135
The running loss is:
22.097350671887398
The number of items in train is:
18
The loss for epoch 4
1.2276305928826332
The running loss is:
20.19718218408525
The number of items in train is:
18
The loss for epoch 5
1.122065676893625
The running loss is:
19.485243333270773
The number of items in train is:
18
The loss for epoch 6
1.082513518515043
The running loss is:
17.892029164126143
The number of items in train is:
18
The loss for epoch 7
0.9940016202292301
The running loss is:
18.208995703607798
The number of items in train is:
18
The loss for epoch 8
1.0116108724226553
The running loss is:
17.07296721637249
The number of items in train is:
18
The loss for epoch 9
0.9484981786873605
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.838210
47 30819 Eagle County, Colorado, United States ... 47 3.904054
48 30820 Eagle County, Colorado, United States ... 48 3.808350
49 30821 Eagle County, Colorado, United States ... 49 3.808419
50 30822 Eagle County, Colorado, United States ... 50 3.808272
51 30823 Eagle County, Colorado, United States ... 51 3.810375
52 30824 Eagle County, Colorado, United States ... 52 3.794322
53 30825 Eagle County, Colorado, United States ... 53 5.768596
54 30826 Eagle County, Colorado, United States ... 54 5.768584
55 30827 Eagle County, Colorado, United States ... 55 5.768637
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yqngqnis wandb: Agent Starting Run: me7r4kuv with config: batch_size: 2 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: me7r4kuv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
93.78758010268211
The number of items in train is:
17
The loss for epoch 0
5.51691647662836
The running loss is:
29.59822855144739
The number of items in train is:
17
The loss for epoch 1
1.7410722677321995
The running loss is:
22.846619226038456
The number of items in train is:
17
The loss for epoch 2
1.3439187780022621
The running loss is:
23.303640887141228
The number of items in train is:
17
The loss for epoch 3
1.3708024051259546
The running loss is:
26.486353397369385
The number of items in train is:
17
The loss for epoch 4
1.558020788080552
The running loss is:
20.396254796534777
The number of items in train is:
17
The loss for epoch 5
1.1997796939138103
The running loss is:
19.39982558786869
The number of items in train is:
17
The loss for epoch 6
1.1411662110510994
The running loss is:
18.315881371498108
The number of items in train is:
17
The loss for epoch 7
1.0774047865587122
The running loss is:
19.250380620360374
The number of items in train is:
17
The loss for epoch 8
1.1323753306094337
The running loss is:
17.944953735917807
The number of items in train is:
17
The loss for epoch 9
1.055585513877518
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.394843
47 30819 Eagle County, Colorado, United States ... 47 8.136378
48 30820 Eagle County, Colorado, United States ... 48 9.291075
49 30821 Eagle County, Colorado, United States ... 49 9.697542
50 30822 Eagle County, Colorado, United States ... 50 8.140117
51 30823 Eagle County, Colorado, United States ... 51 8.296720
52 30824 Eagle County, Colorado, United States ... 52 7.882609
53 30825 Eagle County, Colorado, United States ... 53 8.762344
54 30826 Eagle County, Colorado, United States ... 54 8.641793
55 30827 Eagle County, Colorado, United States ... 55 9.389215
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: me7r4kuv wandb: Agent Starting Run: 3wm5l7tj with config: batch_size: 2 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3wm5l7tj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
68.26089033484459
The number of items in train is:
17
The loss for epoch 0
4.015346490284976
The running loss is:
27.4893958568573
The number of items in train is:
17
The loss for epoch 1
1.6170232856974882
The running loss is:
21.516857236623764
The number of items in train is:
17
The loss for epoch 2
1.2656974845072801
The running loss is:
18.865566059947014
The number of items in train is:
17
The loss for epoch 3
1.1097391799968832
The running loss is:
18.153654858469963
The number of items in train is:
17
The loss for epoch 4
1.067862050498233
The running loss is:
18.767946392297745
The number of items in train is:
17
The loss for epoch 5
1.1039968466057497
The running loss is:
17.852910339832306
The number of items in train is:
17
The loss for epoch 6
1.0501711964607239
The running loss is:
18.34410585463047
The number of items in train is:
17
The loss for epoch 7
1.0790650502723806
The running loss is:
18.192266955971718
The number of items in train is:
17
The loss for epoch 8
1.0701333503512775
The running loss is:
18.552403688430786
The number of items in train is:
17
The loss for epoch 9
1.0913178640253403
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.797457
47 30819 ... 10.797460
48 30820 ... 10.797462
49 30821 ... 10.797461
50 30822 ... 10.797450
51 30823 ... 10.771597
52 30824 ... 10.780639
53 30825 ... 10.770386
54 30826 ... 10.770385
55 30827 ... 10.770388
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3wm5l7tj wandb: Agent Starting Run: yefxbgtv with config: batch_size: 2 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yefxbgtv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.462372362613678
The number of items in train is:
17
The loss for epoch 0
1.203668962506687
The running loss is:
27.696742221713066
The number of items in train is:
17
The loss for epoch 1
1.629220130689004
The running loss is:
19.980237632989883
The number of items in train is:
17
The loss for epoch 2
1.1753080960582285
The running loss is:
18.27062140405178
The number of items in train is:
17
The loss for epoch 3
1.0747424355324577
The running loss is:
17.597937013953924
The number of items in train is:
17
The loss for epoch 4
1.0351727655267013
The running loss is:
17.500756841152906
The number of items in train is:
17
The loss for epoch 5
1.0294562847737003
The running loss is:
17.59584029763937
The number of items in train is:
17
The loss for epoch 6
1.0350494292729042
The running loss is:
16.307608522474766
The number of items in train is:
17
The loss for epoch 7
0.9592710895573392
The running loss is:
14.856096312403679
The number of items in train is:
17
The loss for epoch 8
0.873888018376687
The running loss is:
15.076502352952957
The number of items in train is:
17
The loss for epoch 9
0.8868530795854681
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.705813
47 30819 ... 9.390274
48 30820 ... 12.924283
49 30821 ... 10.632058
50 30822 ... 5.007174
51 30823 ... 7.001017
52 30824 ... 7.316066
53 30825 ... 7.175669
54 30826 ... 11.666767
55 30827 ... 16.188978
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yefxbgtv wandb: Agent Starting Run: ptzv63ti with config: batch_size: 2 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ptzv63ti
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.43279777467251
The number of items in train is:
17
The loss for epoch 0
1.2607528102748535
The running loss is:
28.9186382740736
The number of items in train is:
17
The loss for epoch 1
1.701096369063153
The running loss is:
19.826389342546463
The number of items in train is:
17
The loss for epoch 2
1.1662581966203802
The running loss is:
19.31631900370121
The number of items in train is:
17
The loss for epoch 3
1.1362540590412475
The running loss is:
18.248578935861588
The number of items in train is:
17
The loss for epoch 4
1.073445819756564
The running loss is:
18.17185389995575
The number of items in train is:
17
The loss for epoch 5
1.0689325823503382
The running loss is:
17.282859161496162
The number of items in train is:
17
The loss for epoch 6
1.0166387742056566
The running loss is:
17.04989528656006
The number of items in train is:
17
The loss for epoch 7
1.0029350168564741
The running loss is:
15.761375814676285
The number of items in train is:
17
The loss for epoch 8
0.9271397538044873
The running loss is:
15.65200425684452
The number of items in train is:
17
The loss for epoch 9
0.92070613275556
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.450491
47 30819 ... 8.844732
48 30820 ... 14.072254
49 30821 ... 10.256414
50 30822 ... 3.695667
51 30823 ... 7.670989
52 30824 ... 7.494445
53 30825 ... 5.381908
54 30826 ... 11.431887
55 30827 ... 17.711899
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ptzv63ti wandb: Agent Starting Run: 5n23rnej with config: batch_size: 2 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 5n23rnej
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.669841051101685
The number of items in train is:
16
The loss for epoch 0
1.1668650656938553
The running loss is:
28.15961427986622
The number of items in train is:
16
The loss for epoch 1
1.7599758924916387
The running loss is:
20.083170026540756
The number of items in train is:
16
The loss for epoch 2
1.2551981266587973
The running loss is:
18.681346032768488
The number of items in train is:
16
The loss for epoch 3
1.1675841270480305
The running loss is:
17.155792146921158
The number of items in train is:
16
The loss for epoch 4
1.0722370091825724
The running loss is:
17.125128746032715
The number of items in train is:
16
The loss for epoch 5
1.0703205466270447
The running loss is:
16.875126153230667
The number of items in train is:
16
The loss for epoch 6
1.0546953845769167
The running loss is:
16.763597190380096
The number of items in train is:
16
The loss for epoch 7
1.047724824398756
The running loss is:
16.318107686936855
The number of items in train is:
16
The loss for epoch 8
1.0198817304335535
The running loss is:
16.028378427028656
The number of items in train is:
16
The loss for epoch 9
1.001773651689291
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.727273
47 30819 ... 8.141912
48 30820 ... 8.153705
49 30821 ... 7.590404
50 30822 ... 7.745370
51 30823 ... 8.056146
52 30824 ... 8.437635
53 30825 ... 9.068559
54 30826 ... 9.863579
55 30827 ... 10.122281
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5n23rnej wandb: Agent Starting Run: z8wl2mpd with config: batch_size: 2 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: z8wl2mpd
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.78652110695839
The number of items in train is:
17
The loss for epoch 0
1.0462659474681406
The running loss is:
29.496645376086235
The number of items in train is:
17
The loss for epoch 1
1.735096786828602
The running loss is:
21.52673441171646
The number of items in train is:
17
The loss for epoch 2
1.2662784948068506
The running loss is:
18.22583021223545
The number of items in train is:
17
The loss for epoch 3
1.0721076595432617
The running loss is:
17.649071596562862
The number of items in train is:
17
The loss for epoch 4
1.0381806821507567
The running loss is:
16.916042253375053
The number of items in train is:
17
The loss for epoch 5
0.9950613090220619
The running loss is:
17.47312443703413
The number of items in train is:
17
The loss for epoch 6
1.0278308492373018
The running loss is:
16.61391367763281
The number of items in train is:
17
The loss for epoch 7
0.9772890398607534
The running loss is:
16.87849473580718
The number of items in train is:
17
The loss for epoch 8
0.9928526315180695
The running loss is:
17.174730110913515
The number of items in train is:
17
The loss for epoch 9
1.0102782418184422
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.426375
47 30819 ... 10.432105
48 30820 ... 13.992594
49 30821 ... 12.741571
50 30822 ... 6.316299
51 30823 ... 7.661055
52 30824 ... 9.314131
53 30825 ... 8.768213
54 30826 ... 11.098319
55 30827 ... 15.006298
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: z8wl2mpd wandb: Agent Starting Run: klplltl7 with config: batch_size: 2 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: klplltl7
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.754808202385902
The number of items in train is:
17
The loss for epoch 0
1.1032240119050531
The running loss is:
27.57693576812744
The number of items in train is:
17
The loss for epoch 1
1.6221726922427906
The running loss is:
21.580725207924843
The number of items in train is:
17
The loss for epoch 2
1.269454423995579
The running loss is:
19.201142698526382
The number of items in train is:
17
The loss for epoch 3
1.1294789822662579
The running loss is:
17.52506871521473
The number of items in train is:
17
The loss for epoch 4
1.0308863950126312
The running loss is:
16.90795011818409
The number of items in train is:
17
The loss for epoch 5
0.9945853010696524
The running loss is:
14.841296076774597
The number of items in train is:
17
The loss for epoch 6
0.8730174162808586
The running loss is:
17.39919090270996
The number of items in train is:
17
The loss for epoch 7
1.0234818178064682
The running loss is:
13.71133454144001
The number of items in train is:
17
The loss for epoch 8
0.8065490906729418
The running loss is:
15.23483623471111
The number of items in train is:
17
The loss for epoch 9
0.8961668373359477
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.157433
47 30819 ... 8.102160
48 30820 ... 17.461388
49 30821 ... 16.528046
50 30822 ... 2.348297
51 30823 ... 8.818064
52 30824 ... 10.826026
53 30825 ... 5.528331
54 30826 ... 11.029634
55 30827 ... 22.022442
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: klplltl7 wandb: Agent Starting Run: b9vef1w8 with config: batch_size: 2 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: b9vef1w8
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.429183930158615
The number of items in train is:
16
The loss for epoch 0
1.0893239956349134
The running loss is:
25.076544493436813
The number of items in train is:
16
The loss for epoch 1
1.5672840308398008
The running loss is:
21.2126601934433
The number of items in train is:
16
The loss for epoch 2
1.3257912620902061
The running loss is:
17.364732414484024
The number of items in train is:
16
The loss for epoch 3
1.0852957759052515
The running loss is:
17.196853309869766
The number of items in train is:
16
The loss for epoch 4
1.0748033318668604
The running loss is:
16.994296818971634
The number of items in train is:
16
The loss for epoch 5
1.0621435511857271
The running loss is:
17.03663896024227
The number of items in train is:
16
The loss for epoch 6
1.064789935015142
The running loss is:
16.859628692269325
The number of items in train is:
16
The loss for epoch 7
1.0537267932668328
The running loss is:
16.93640587478876
The number of items in train is:
16
The loss for epoch 8
1.0585253671742976
The running loss is:
17.753980338573456
The number of items in train is:
16
The loss for epoch 9
1.109623771160841
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.685909
47 30819 Eagle County, Colorado, United States ... 47 8.640967
48 30820 Eagle County, Colorado, United States ... 48 9.257741
49 30821 Eagle County, Colorado, United States ... 49 8.904490
50 30822 Eagle County, Colorado, United States ... 50 8.397946
51 30823 Eagle County, Colorado, United States ... 51 8.507514
52 30824 Eagle County, Colorado, United States ... 52 8.640145
53 30825 Eagle County, Colorado, United States ... 53 8.585375
54 30826 Eagle County, Colorado, United States ... 54 9.138819
55 30827 Eagle County, Colorado, United States ... 55 9.589720
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b9vef1w8 wandb: Agent Starting Run: gessnckp with config: batch_size: 2 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: gessnckp
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.54187097400427
The number of items in train is:
17
The loss for epoch 0
1.3848159396473099
The running loss is:
24.992527093738317
The number of items in train is:
17
The loss for epoch 1
1.4701486525728422
The running loss is:
21.432729721069336
The number of items in train is:
17
The loss for epoch 2
1.2607488071217257
The running loss is:
18.33254014328122
The number of items in train is:
17
The loss for epoch 3
1.0783847143106602
The running loss is:
16.867909282445908
The number of items in train is:
17
The loss for epoch 4
0.9922299577909357
The running loss is:
17.271138109266758
The number of items in train is:
17
The loss for epoch 5
1.0159493005451035
The running loss is:
17.526262529194355
The number of items in train is:
17
The loss for epoch 6
1.0309566193643738
The running loss is:
17.195260427892208
The number of items in train is:
17
The loss for epoch 7
1.011485907523071
The running loss is:
17.226871080696583
The number of items in train is:
17
The loss for epoch 8
1.0133453576880342
The running loss is:
16.88069112598896
The number of items in train is:
17
The loss for epoch 9
0.992981830940527
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.652255
47 30819 ... 13.184143
48 30820 ... 14.892082
49 30821 ... 14.395442
50 30822 ... 9.526847
51 30823 ... 9.159123
52 30824 ... 10.524038
53 30825 ... 11.447363
54 30826 ... 12.936011
55 30827 ... 14.850525
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gessnckp wandb: Agent Starting Run: ga1qgbm2 with config: batch_size: 2 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ga1qgbm2
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.710720017552376
The number of items in train is:
17
The loss for epoch 0
1.3359247069148457
The running loss is:
25.101445123553276
The number of items in train is:
17
The loss for epoch 1
1.476555595503134
The running loss is:
22.209337458014488
The number of items in train is:
17
The loss for epoch 2
1.3064316151773228
The running loss is:
20.105842724442482
The number of items in train is:
17
The loss for epoch 3
1.1826966308495577
The running loss is:
18.94278684258461
The number of items in train is:
17
The loss for epoch 4
1.1142815789755653
The running loss is:
18.09556182473898
The number of items in train is:
17
The loss for epoch 5
1.06444481321994
The running loss is:
18.789756417274475
The number of items in train is:
17
The loss for epoch 6
1.1052797892514397
The running loss is:
18.20790345966816
The number of items in train is:
17
The loss for epoch 7
1.0710531446863623
The running loss is:
17.90162880718708
The number of items in train is:
17
The loss for epoch 8
1.0530369886580635
The running loss is:
17.974793404340744
The number of items in train is:
17
The loss for epoch 9
1.057340788490632
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.552468
47 30819 ... 13.281707
48 30820 ... 18.242928
49 30821 ... 14.926788
50 30822 ... 5.647899
51 30823 ... 9.067403
52 30824 ... 13.766898
53 30825 ... 10.045872
54 30826 ... 13.696932
55 30827 ... 16.382318
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ga1qgbm2 wandb: Agent Starting Run: 9mwe9odr with config: batch_size: 2 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 9mwe9odr
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
24.058534413576126
The number of items in train is:
16
The loss for epoch 0
1.5036584008485079
The running loss is:
24.180755577981472
The number of items in train is:
16
The loss for epoch 1
1.511297223623842
The running loss is:
20.436290249228477
The number of items in train is:
16
The loss for epoch 2
1.2772681405767798
The running loss is:
18.773078814148903
The number of items in train is:
16
The loss for epoch 3
1.1733174258843064
The running loss is:
17.54651653021574
The number of items in train is:
16
The loss for epoch 4
1.0966572831384838
The running loss is:
17.458857282996178
The number of items in train is:
16
The loss for epoch 5
1.091178580187261
The running loss is:
17.353648215532303
The number of items in train is:
16
The loss for epoch 6
1.084603013470769
wandb: Network error resolved after 0:00:11.333796, resuming normal operation.
The running loss is: 16.79451848566532 The number of items in train is: 16 The loss for epoch 7 1.0496574053540826 The running loss is: 16.56403110176325 The number of items in train is: 16 The loss for epoch 8 1.035251943860203 The running loss is: 18.429389148950577 The number of items in train is: 16 The loss for epoch 9 1.151836821809411 interpolate should be below Now loading and scaling Colorado_Eagle County.csv CSV Path below Colorado_Eagle County.csv torch.Size([1, 8, 3]) Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
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46 30818 ... 9.982271
47 30819 ... 10.173903
48 30820 ... 10.837774
49 30821 ... 10.261594
50 30822 ... 9.828760
51 30823 ... 9.887388
52 30824 ... 9.815040
53 30825 ... 9.642322
54 30826 ... 9.854512
55 30827 ... 10.046807
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9mwe9odr wandb: Agent Starting Run: tpqh9vdt with config: batch_size: 2 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: tpqh9vdt
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
76.73103265464306
The number of items in train is:
17
The loss for epoch 0
4.513590156155474
The running loss is:
31.05447568744421
The number of items in train is:
17
The loss for epoch 1
1.8267338639673065
The running loss is:
20.485956706106663
The number of items in train is:
17
The loss for epoch 2
1.2050562768298037
The running loss is:
21.844449251890182
The number of items in train is:
17
The loss for epoch 3
1.2849676030523636
The running loss is:
18.358333572745323
The number of items in train is:
17
The loss for epoch 4
1.079901974867372
The running loss is:
18.44140242645517
The number of items in train is:
17
The loss for epoch 5
1.0847883780267746
The running loss is:
20.418050155043602
The number of items in train is:
17
The loss for epoch 6
1.2010617738260942
The running loss is:
20.065719813108444
The number of items in train is:
17
The loss for epoch 7
1.1803364595946144
The running loss is:
18.964558770880103
The number of items in train is:
17
The loss for epoch 8
1.115562280640006
The running loss is:
17.706577128730714
The number of items in train is:
17
The loss for epoch 9
1.0415633605135715
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.264996
47 30819 ... 11.263235
48 30820 ... 11.252102
49 30821 ... 11.254551
50 30822 ... 11.251740
51 30823 ... 11.266092
52 30824 ... 11.297521
53 30825 ... 11.289854
54 30826 ... 11.319056
55 30827 ... 11.313751
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tpqh9vdt wandb: Agent Starting Run: 6hn5aa9q with config: batch_size: 2 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 6hn5aa9q
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
64.83852332830429
The number of items in train is:
17
The loss for epoch 0
3.8140307840178993
The running loss is:
24.20455026626587
The number of items in train is:
17
The loss for epoch 1
1.4237970744862276
The running loss is:
19.660972595214844
The number of items in train is:
17
The loss for epoch 2
1.1565277997185202
The running loss is:
19.629955507814884
The number of items in train is:
17
The loss for epoch 3
1.1547032651655815
The running loss is:
19.02102354168892
The number of items in train is:
17
The loss for epoch 4
1.118883737746407
The running loss is:
18.660875782370567
The number of items in train is:
17
The loss for epoch 5
1.0976985754335629
The running loss is:
18.049541860818863
The number of items in train is:
17
The loss for epoch 6
1.0617377565187567
The running loss is:
16.762809321284294
The number of items in train is:
17
The loss for epoch 7
0.9860476071343702
The running loss is:
21.54910632967949
The number of items in train is:
17
The loss for epoch 8
1.2675944899811464
The running loss is:
19.76157969236374
The number of items in train is:
17
The loss for epoch 9
1.1624458642566906
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.821740
47 30819 ... 12.099711
48 30820 ... 12.154493
49 30821 ... 11.972459
50 30822 ... 11.806449
51 30823 ... 12.246671
52 30824 ... 12.140120
53 30825 ... 12.150714
54 30826 ... 12.229416
55 30827 ... 12.229841
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6hn5aa9q wandb: Agent Starting Run: wh54t7pz with config: batch_size: 2 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: wh54t7pz
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
86.34015256166458
The number of items in train is:
16
The loss for epoch 0
5.396259535104036
The running loss is:
21.355846017599106
The number of items in train is:
16
The loss for epoch 1
1.3347403760999441
The running loss is:
26.509278684854507
The number of items in train is:
16
The loss for epoch 2
1.6568299178034067
The running loss is:
18.682842135429382
The number of items in train is:
16
The loss for epoch 3
1.1676776334643364
The running loss is:
17.745087578892708
The number of items in train is:
16
The loss for epoch 4
1.1090679736807942
The running loss is:
17.44467857480049
The number of items in train is:
16
The loss for epoch 5
1.0902924109250307
The running loss is:
17.872719079256058
The number of items in train is:
16
The loss for epoch 6
1.1170449424535036
The running loss is:
17.736331656575203
The number of items in train is:
16
The loss for epoch 7
1.1085207285359502
The running loss is:
17.695459455251694
The number of items in train is:
16
The loss for epoch 8
1.1059662159532309
The running loss is:
17.168903946876526
The number of items in train is:
16
The loss for epoch 9
1.0730564966797829
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 12.047359
47 30819 ... 11.826193
48 30820 ... 9.759015
49 30821 ... 10.301134
50 30822 ... 12.089850
51 30823 ... 11.833580
52 30824 ... 11.614565
53 30825 ... 13.017410
54 30826 ... 11.678865
55 30827 ... 9.747301
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: wh54t7pz wandb: Agent Starting Run: cjk92bph with config: batch_size: 2 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cjk92bph
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.541068863123655
The number of items in train is:
17
The loss for epoch 0
1.1494746390072739
The running loss is:
31.577809385955334
The number of items in train is:
17
The loss for epoch 1
1.8575181991738432
The running loss is:
21.210836698301136
The number of items in train is:
17
The loss for epoch 2
1.2476962763706552
The running loss is:
19.0487511085812
The number of items in train is:
17
The loss for epoch 3
1.1205147710930117
The running loss is:
17.747340630739927
The number of items in train is:
17
The loss for epoch 4
1.0439612135729368
The running loss is:
16.326730091124773
The number of items in train is:
17
The loss for epoch 5
0.9603958877132219
The running loss is:
16.821684509515762
The number of items in train is:
17
The loss for epoch 6
0.9895108535009272
The running loss is:
16.196162899956107
The number of items in train is:
17
The loss for epoch 7
0.9527154647033004
The running loss is:
16.129438281059265
The number of items in train is:
17
The loss for epoch 8
0.9487904871211332
The running loss is:
14.658306866884232
The number of items in train is:
17
The loss for epoch 9
0.8622533451108372
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.140587
47 30819 Eagle County, Colorado, United States ... 47 8.496163
48 30820 Eagle County, Colorado, United States ... 48 8.369562
49 30821 Eagle County, Colorado, United States ... 49 7.550753
50 30822 Eagle County, Colorado, United States ... 50 6.753438
51 30823 Eagle County, Colorado, United States ... 51 7.273794
52 30824 Eagle County, Colorado, United States ... 52 7.213016
53 30825 Eagle County, Colorado, United States ... 53 8.200387
54 30826 Eagle County, Colorado, United States ... 54 9.424652
55 30827 Eagle County, Colorado, United States ... 55 9.819715
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cjk92bph wandb: Agent Starting Run: zbcdwhpq with config: batch_size: 2 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: zbcdwhpq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.168893314898014
The number of items in train is:
16
The loss for epoch 0
1.2605558321811259
The running loss is:
25.939899191260338
The number of items in train is:
16
The loss for epoch 1
1.6212436994537711
The running loss is:
18.034993439912796
The number of items in train is:
16
The loss for epoch 2
1.1271870899945498
The running loss is:
17.39638414233923
The number of items in train is:
16
The loss for epoch 3
1.0872740088962018
The running loss is:
16.87509286403656
The number of items in train is:
16
The loss for epoch 4
1.054693304002285
The running loss is:
16.00445708632469
The number of items in train is:
16
The loss for epoch 5
1.0002785678952932
The running loss is:
16.381498876959085
The number of items in train is:
16
The loss for epoch 6
1.0238436798099428
The running loss is:
15.403928969055414
The number of items in train is:
16
The loss for epoch 7
0.9627455605659634
The running loss is:
14.709752142429352
The number of items in train is:
16
The loss for epoch 8
0.9193595089018345
The running loss is:
14.122410148382187
The number of items in train is:
16
The loss for epoch 9
0.8826506342738867
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.590269
47 30819 Eagle County, Colorado, United States ... 47 6.284689
48 30820 Eagle County, Colorado, United States ... 48 6.673457
49 30821 Eagle County, Colorado, United States ... 49 5.553449
50 30822 Eagle County, Colorado, United States ... 50 4.031074
51 30823 Eagle County, Colorado, United States ... 51 3.671934
52 30824 Eagle County, Colorado, United States ... 52 3.971685
53 30825 Eagle County, Colorado, United States ... 53 5.478973
54 30826 Eagle County, Colorado, United States ... 54 6.330999
55 30827 Eagle County, Colorado, United States ... 55 6.209041
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zbcdwhpq wandb: Agent Starting Run: vo9vk3ik with config: batch_size: 2 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: vo9vk3ik
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.161318197846413
The number of items in train is:
16
The loss for epoch 0
1.1350823873654008
The running loss is:
28.34734532237053
The number of items in train is:
16
The loss for epoch 1
1.771709082648158
The running loss is:
21.952908873558044
The number of items in train is:
16
The loss for epoch 2
1.3720568045973778
The running loss is:
18.008008897304535
The number of items in train is:
16
The loss for epoch 3
1.1255005560815334
The running loss is:
18.31263779103756
The number of items in train is:
16
The loss for epoch 4
1.1445398619398475
The running loss is:
16.959372133016586
The number of items in train is:
16
The loss for epoch 5
1.0599607583135366
The running loss is:
16.71182854473591
The number of items in train is:
16
The loss for epoch 6
1.0444892840459943
The running loss is:
16.340465560555458
The number of items in train is:
16
The loss for epoch 7
1.0212790975347161
The running loss is:
15.99364747107029
The number of items in train is:
16
The loss for epoch 8
0.9996029669418931
The running loss is:
15.350911244750023
The number of items in train is:
16
The loss for epoch 9
0.9594319527968764
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.893581
47 30819 Eagle County, Colorado, United States ... 47 4.652898
48 30820 Eagle County, Colorado, United States ... 48 4.505464
49 30821 Eagle County, Colorado, United States ... 49 3.514089
50 30822 Eagle County, Colorado, United States ... 50 2.621427
51 30823 Eagle County, Colorado, United States ... 51 2.962666
52 30824 Eagle County, Colorado, United States ... 52 2.937756
53 30825 Eagle County, Colorado, United States ... 53 3.398608
54 30826 Eagle County, Colorado, United States ... 54 3.783144
55 30827 Eagle County, Colorado, United States ... 55 3.793390
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vo9vk3ik wandb: Agent Starting Run: m0nfhmwv with config: batch_size: 2 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: m0nfhmwv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.05170270940289
The number of items in train is:
17
The loss for epoch 0
1.179511924082523
The running loss is:
27.10501365410164
The number of items in train is:
17
The loss for epoch 1
1.5944125678883319
The running loss is:
24.45247669145465
The number of items in train is:
17
The loss for epoch 2
1.4383809818502735
The running loss is:
17.12475097551942
The number of items in train is:
17
The loss for epoch 3
1.0073382926776129
The running loss is:
16.83773805736564
The number of items in train is:
17
The loss for epoch 4
0.9904551798450377
The running loss is:
16.38904993236065
The number of items in train is:
17
The loss for epoch 5
0.964061760727097
The running loss is:
16.86034062318504
The number of items in train is:
17
The loss for epoch 6
0.9917847425402964
The running loss is:
17.765443854033947
The number of items in train is:
17
The loss for epoch 7
1.0450261090608204
The running loss is:
16.69217774644494
The number of items in train is:
17
The loss for epoch 8
0.9818928086144083
The running loss is:
15.330347783863544
The number of items in train is:
17
The loss for epoch 9
0.901785163756679
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.371289
47 30819 Eagle County, Colorado, United States ... 47 9.567065
48 30820 Eagle County, Colorado, United States ... 48 9.085946
49 30821 Eagle County, Colorado, United States ... 49 8.364687
50 30822 Eagle County, Colorado, United States ... 50 7.982452
51 30823 Eagle County, Colorado, United States ... 51 8.483797
52 30824 Eagle County, Colorado, United States ... 52 8.248549
53 30825 Eagle County, Colorado, United States ... 53 8.893828
54 30826 Eagle County, Colorado, United States ... 54 9.528422
55 30827 Eagle County, Colorado, United States ... 55 9.468787
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: m0nfhmwv wandb: Agent Starting Run: gx5177rp with config: batch_size: 2 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: gx5177rp
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.488044381141663
The number of items in train is:
16
The loss for epoch 0
1.093002773821354
The running loss is:
23.978667616844177
The number of items in train is:
16
The loss for epoch 1
1.498666726052761
The running loss is:
19.89868026971817
The number of items in train is:
16
The loss for epoch 2
1.2436675168573856
The running loss is:
17.491415731608868
The number of items in train is:
16
The loss for epoch 3
1.0932134832255542
The running loss is:
17.02195332199335
The number of items in train is:
16
The loss for epoch 4
1.0638720826245844
The running loss is:
16.250655472278595
The number of items in train is:
16
The loss for epoch 5
1.0156659670174122
The running loss is:
17.369982078671455
The number of items in train is:
16
The loss for epoch 6
1.085623879916966
The running loss is:
16.19321621209383
The number of items in train is:
16
The loss for epoch 7
1.0120760132558644
The running loss is:
15.575257241725922
The number of items in train is:
16
The loss for epoch 8
0.9734535776078701
The running loss is:
14.779532857239246
The number of items in train is:
16
The loss for epoch 9
0.9237208035774529
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 7.571152
47 30819 Eagle County, Colorado, United States ... 47 5.052190
48 30820 Eagle County, Colorado, United States ... 48 5.632578
49 30821 Eagle County, Colorado, United States ... 49 5.871844
50 30822 Eagle County, Colorado, United States ... 50 3.961731
51 30823 Eagle County, Colorado, United States ... 51 3.108603
52 30824 Eagle County, Colorado, United States ... 52 3.412964
53 30825 Eagle County, Colorado, United States ... 53 4.292527
54 30826 Eagle County, Colorado, United States ... 54 4.116302
55 30827 Eagle County, Colorado, United States ... 55 4.581748
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gx5177rp wandb: Agent Starting Run: 90rqzvhh with config: batch_size: 2 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 90rqzvhh
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.225835099816322
The number of items in train is:
16
The loss for epoch 0
1.3266146937385201
The running loss is:
24.082868233323097
The number of items in train is:
16
The loss for epoch 1
1.5051792645826936
The running loss is:
27.372445285320282
The number of items in train is:
16
The loss for epoch 2
1.7107778303325176
The running loss is:
20.892320051789284
The number of items in train is:
16
The loss for epoch 3
1.3057700032368302
The running loss is:
20.565253868699074
The number of items in train is:
16
The loss for epoch 4
1.2853283667936921
The running loss is:
16.875523328781128
The number of items in train is:
16
The loss for epoch 5
1.0547202080488205
The running loss is:
17.473206147551537
The number of items in train is:
16
The loss for epoch 6
1.092075384221971
The running loss is:
16.84730589389801
The number of items in train is:
16
The loss for epoch 7
1.0529566183686256
The running loss is:
16.792904995381832
The number of items in train is:
16
The loss for epoch 8
1.0495565622113645
The running loss is:
16.68462935835123
The number of items in train is:
16
The loss for epoch 9
1.042789334896952
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.352649
47 30819 Eagle County, Colorado, United States ... 47 6.084286
48 30820 Eagle County, Colorado, United States ... 48 6.090950
49 30821 Eagle County, Colorado, United States ... 49 5.605799
50 30822 Eagle County, Colorado, United States ... 50 5.207687
51 30823 Eagle County, Colorado, United States ... 51 5.319816
52 30824 Eagle County, Colorado, United States ... 52 5.325910
53 30825 Eagle County, Colorado, United States ... 53 5.664911
54 30826 Eagle County, Colorado, United States ... 54 5.746319
55 30827 Eagle County, Colorado, United States ... 55 6.000322
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 90rqzvhh wandb: Agent Starting Run: 5kqgou97 with config: batch_size: 2 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5kqgou97
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.777981208404526
The number of items in train is:
17
The loss for epoch 0
1.6928224240237957
The running loss is:
24.640328461304307
The number of items in train is:
17
The loss for epoch 1
1.4494310859590769
The running loss is:
27.799861981067806
The number of items in train is:
17
The loss for epoch 2
1.6352859988863415
The running loss is:
20.27729516022373
The number of items in train is:
17
The loss for epoch 3
1.1927820682484547
The running loss is:
17.45506318518892
The number of items in train is:
17
The loss for epoch 4
1.0267684226581717
The running loss is:
16.46949014440179
The number of items in train is:
17
The loss for epoch 5
0.9687935379059875
The running loss is:
21.04788029473275
The number of items in train is:
17
The loss for epoch 6
1.2381106055725146
The running loss is:
18.626586033031344
The number of items in train is:
17
The loss for epoch 7
1.095681531354785
The running loss is:
18.9736210629344
The number of items in train is:
17
The loss for epoch 8
1.1160953566432
The running loss is:
17.51461985334754
The number of items in train is:
17
The loss for epoch 9
1.0302717560792671
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.366323
47 30819 Eagle County, Colorado, United States ... 47 5.725136
48 30820 Eagle County, Colorado, United States ... 48 6.439533
49 30821 Eagle County, Colorado, United States ... 49 6.884377
50 30822 Eagle County, Colorado, United States ... 50 6.239933
51 30823 Eagle County, Colorado, United States ... 51 4.986047
52 30824 Eagle County, Colorado, United States ... 52 6.204242
53 30825 Eagle County, Colorado, United States ... 53 6.950147
54 30826 Eagle County, Colorado, United States ... 54 6.047112
55 30827 Eagle County, Colorado, United States ... 55 6.310897
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5kqgou97 wandb: Agent Starting Run: kf0ese4y with config: batch_size: 2 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: kf0ese4y
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.219055324792862
The number of items in train is:
16
The loss for epoch 0
1.3886909577995539
The running loss is:
22.0189621001482
The number of items in train is:
16
The loss for epoch 1
1.3761851312592626
The running loss is:
19.93704141676426
The number of items in train is:
16
The loss for epoch 2
1.2460650885477662
The running loss is:
17.88787931203842
The number of items in train is:
16
The loss for epoch 3
1.1179924570024014
The running loss is:
16.455111406743526
The number of items in train is:
16
The loss for epoch 4
1.0284444629214704
The running loss is:
16.531717360019684
The number of items in train is:
16
The loss for epoch 5
1.0332323350012302
The running loss is:
17.8481187466532
The number of items in train is:
16
The loss for epoch 6
1.115507421665825
The running loss is:
17.158546946942806
The number of items in train is:
16
The loss for epoch 7
1.0724091841839254
The running loss is:
17.001652263104916
The number of items in train is:
16
The loss for epoch 8
1.0626032664440572
The running loss is:
16.163067802786827
The number of items in train is:
16
The loss for epoch 9
1.0101917376741767
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.685339
47 30819 ... 9.254963
48 30820 ... 9.078858
49 30821 ... 9.091250
50 30822 ... 9.344090
51 30823 ... 9.539142
52 30824 ... 8.981033
53 30825 ... 9.279771
54 30826 ... 9.038018
55 30827 ... 9.276935
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: kf0ese4y wandb: Agent Starting Run: krqw3ydc with config: batch_size: 2 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: krqw3ydc
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
35.509117022156715
The number of items in train is:
16
The loss for epoch 0
2.2193198138847947
The running loss is:
27.793827712535858
The number of items in train is:
16
The loss for epoch 1
1.7371142320334911
The running loss is:
27.488479807972908
The number of items in train is:
16
The loss for epoch 2
1.7180299879983068
The running loss is:
21.062721334397793
The number of items in train is:
16
The loss for epoch 3
1.316420083399862
The running loss is:
17.644332513213158
The number of items in train is:
16
The loss for epoch 4
1.1027707820758224
The running loss is:
17.82902693748474
The number of items in train is:
16
The loss for epoch 5
1.1143141835927963
The running loss is:
17.82366769760847
The number of items in train is:
16
The loss for epoch 6
1.1139792311005294
The running loss is:
16.8096736446023
The number of items in train is:
16
The loss for epoch 7
1.0506046027876437
The running loss is:
16.60496674105525
The number of items in train is:
16
The loss for epoch 8
1.0378104213159531
The running loss is:
16.044241465628147
The number of items in train is:
16
The loss for epoch 9
1.0027650916017592
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.428545
47 30819 Eagle County, Colorado, United States ... 47 5.813026
48 30820 Eagle County, Colorado, United States ... 48 5.347736
49 30821 Eagle County, Colorado, United States ... 49 4.646779
50 30822 Eagle County, Colorado, United States ... 50 3.470057
51 30823 Eagle County, Colorado, United States ... 51 4.449368
52 30824 Eagle County, Colorado, United States ... 52 4.113334
53 30825 Eagle County, Colorado, United States ... 53 3.690783
54 30826 Eagle County, Colorado, United States ... 54 4.221715
55 30827 Eagle County, Colorado, United States ... 55 4.104982
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: krqw3ydc wandb: Agent Starting Run: sh72of1b with config: batch_size: 2 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: sh72of1b
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
103.1626292373985
The number of items in train is:
17
The loss for epoch 0
6.068389955141089
The running loss is:
32.25590829923749
The number of items in train is:
17
The loss for epoch 1
1.8974063705433817
The running loss is:
23.828247282654047
The number of items in train is:
17
The loss for epoch 2
1.4016616048620028
The running loss is:
31.835000079125166
The number of items in train is:
17
The loss for epoch 3
1.8726470634779508
The running loss is:
20.61502874654252
The number of items in train is:
17
The loss for epoch 4
1.212648749796619
The running loss is:
19.363679410889745
The number of items in train is:
17
The loss for epoch 5
1.1390399653464556
The running loss is:
19.635973207186908
The number of items in train is:
17
The loss for epoch 6
1.1550572474815828
The running loss is:
18.29618028178811
The number of items in train is:
17
The loss for epoch 7
1.0762458989287125
The running loss is:
19.22706305421889
The number of items in train is:
17
The loss for epoch 8
1.1310037090716993
The running loss is:
18.380500946193933
The number of items in train is:
17
The loss for epoch 9
1.0812059380114079
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.151937
47 30819 ... 7.935369
48 30820 ... 8.738775
49 30821 ... 10.614862
50 30822 ... 9.969593
51 30823 ... 7.311244
52 30824 ... 7.801637
53 30825 ... 7.693194
54 30826 ... 6.158726
55 30827 ... 9.466553
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sh72of1b wandb: Agent Starting Run: b05a558h with config: batch_size: 2 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: b05a558h
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
78.69877743721008
The number of items in train is:
16
The loss for epoch 0
4.91867358982563
The running loss is:
25.414799951016903
The number of items in train is:
16
The loss for epoch 1
1.5884249969385564
The running loss is:
20.38876563310623
The number of items in train is:
16
The loss for epoch 2
1.2742978520691395
The running loss is:
19.538819804787636
The number of items in train is:
16
The loss for epoch 3
1.2211762377992272
The running loss is:
16.742633998394012
The number of items in train is:
16
The loss for epoch 4
1.0464146248996258
The running loss is:
17.317697145044804
The number of items in train is:
16
The loss for epoch 5
1.0823560715653002
The running loss is:
17.5643428042531
The number of items in train is:
16
The loss for epoch 6
1.0977714252658188
The running loss is:
17.789347365498543
The number of items in train is:
16
The loss for epoch 7
1.111834210343659
The running loss is:
17.489750310778618
The number of items in train is:
16
The loss for epoch 8
1.0931093944236636
The running loss is:
17.39979489147663
The number of items in train is:
16
The loss for epoch 9
1.0874871807172894
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.857318
47 30819 ... 10.542280
48 30820 ... 13.393419
49 30821 ... 12.905228
50 30822 ... 13.987958
51 30823 ... 9.857606
52 30824 ... 9.617988
53 30825 ... 11.862918
54 30826 ... 12.504917
55 30827 ... 12.476783
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b05a558h wandb: Agent Starting Run: b42edysj with config: batch_size: 2 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: b42edysj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
129.31433825194836
The number of items in train is:
16
The loss for epoch 0
8.082146140746772
The running loss is:
33.838866889476776
The number of items in train is:
16
The loss for epoch 1
2.1149291805922985
The running loss is:
32.69537399709225
The number of items in train is:
16
The loss for epoch 2
2.0434608748182654
The running loss is:
20.72595465183258
The number of items in train is:
16
The loss for epoch 3
1.2953721657395363
The running loss is:
18.550900161266327
The number of items in train is:
16
The loss for epoch 4
1.1594312600791454
The running loss is:
18.944357007741928
The number of items in train is:
16
The loss for epoch 5
1.1840223129838705
The running loss is:
16.659233570098877
The number of items in train is:
16
The loss for epoch 6
1.0412020981311798
The running loss is:
16.95862276852131
The number of items in train is:
16
The loss for epoch 7
1.0599139230325818
The running loss is:
17.480562835931778
The number of items in train is:
16
The loss for epoch 8
1.0925351772457361
The running loss is:
16.70482873916626
The number of items in train is:
16
The loss for epoch 9
1.0440517961978912
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.223022
47 30819 Eagle County, Colorado, United States ... 47 9.480515
48 30820 Eagle County, Colorado, United States ... 48 9.003038
49 30821 Eagle County, Colorado, United States ... 49 7.573602
50 30822 Eagle County, Colorado, United States ... 50 8.637365
51 30823 Eagle County, Colorado, United States ... 51 9.787563
52 30824 Eagle County, Colorado, United States ... 52 9.713055
53 30825 Eagle County, Colorado, United States ... 53 9.106526
54 30826 Eagle County, Colorado, United States ... 54 8.233118
55 30827 Eagle County, Colorado, United States ... 55 8.937274
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b42edysj wandb: Agent Starting Run: 0y4dvzek with config: batch_size: 2 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0y4dvzek
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.024294704198837
The number of items in train is:
16
The loss for epoch 0
1.1890184190124273
The running loss is:
28.17329168319702
The number of items in train is:
16
The loss for epoch 1
1.7608307301998138
The running loss is:
19.229630678892136
The number of items in train is:
16
The loss for epoch 2
1.2018519174307585
The running loss is:
18.052614729851484
The number of items in train is:
16
The loss for epoch 3
1.1282884206157178
The running loss is:
16.58875320851803
The number of items in train is:
16
The loss for epoch 4
1.0367970755323768
The running loss is:
16.503416620194912
The number of items in train is:
16
The loss for epoch 5
1.031463538762182
The running loss is:
15.970246095210314
The number of items in train is:
16
The loss for epoch 6
0.9981403809506446
The running loss is:
15.178171835839748
The number of items in train is:
16
The loss for epoch 7
0.9486357397399843
The running loss is:
15.022873431444168
The number of items in train is:
16
The loss for epoch 8
0.9389295894652605
The running loss is:
14.425640754401684
The number of items in train is:
16
The loss for epoch 9
0.9016025471501052
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.330852
47 30819 ... 9.025394
48 30820 ... 10.150417
49 30821 ... 8.791727
50 30822 ... 8.136430
51 30823 ... 6.754112
52 30824 ... 6.621983
53 30825 ... 7.065903
54 30826 ... 9.010159
55 30827 ... 10.120397
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0y4dvzek wandb: Agent Starting Run: n6y0nnnv with config: batch_size: 2 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: n6y0nnnv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.83935895562172
The number of items in train is:
16
The loss for epoch 0
1.2399599347263575
The running loss is:
28.57678074762225
The number of items in train is:
16
The loss for epoch 1
1.7860487967263907
The running loss is:
19.893600448966026
The number of items in train is:
16
The loss for epoch 2
1.2433500280603766
The running loss is:
19.118501737713814
The number of items in train is:
16
The loss for epoch 3
1.1949063586071134
The running loss is:
17.059373825788498
The number of items in train is:
16
The loss for epoch 4
1.0662108641117811
The running loss is:
17.05972745269537
The number of items in train is:
16
The loss for epoch 5
1.0662329657934606
The running loss is:
16.174344236031175
The number of items in train is:
16
The loss for epoch 6
1.0108965147519484
The running loss is:
16.34573794156313
The number of items in train is:
16
The loss for epoch 7
1.0216086213476956
The running loss is:
15.519824489951134
The number of items in train is:
16
The loss for epoch 8
0.9699890306219459
The running loss is:
15.651652056723833
The number of items in train is:
16
The loss for epoch 9
0.9782282535452396
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.513955
47 30819 Eagle County, Colorado, United States ... 47 4.736606
48 30820 Eagle County, Colorado, United States ... 48 5.299429
49 30821 Eagle County, Colorado, United States ... 49 4.227453
50 30822 Eagle County, Colorado, United States ... 50 3.256231
51 30823 Eagle County, Colorado, United States ... 51 1.791030
52 30824 Eagle County, Colorado, United States ... 52 1.133979
53 30825 Eagle County, Colorado, United States ... 53 1.495904
54 30826 Eagle County, Colorado, United States ... 54 2.602427
55 30827 Eagle County, Colorado, United States ... 55 3.637704
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n6y0nnnv wandb: Agent Starting Run: n0i03nbs with config: batch_size: 2 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: n0i03nbs
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.348762914538383
The number of items in train is:
15
The loss for epoch 0
1.2232508609692256
The running loss is:
25.289881259202957
The number of items in train is:
15
The loss for epoch 1
1.6859920839468638
The running loss is:
17.352391123771667
The number of items in train is:
15
The loss for epoch 2
1.1568260749181112
The running loss is:
17.013499923050404
The number of items in train is:
15
The loss for epoch 3
1.1342333282033603
The running loss is:
16.516328513622284
The number of items in train is:
15
The loss for epoch 4
1.101088567574819
The running loss is:
16.258019223809242
The number of items in train is:
15
The loss for epoch 5
1.0838679482539495
The running loss is:
15.751357644796371
The number of items in train is:
15
The loss for epoch 6
1.0500905096530915
The running loss is:
15.609124556183815
The number of items in train is:
15
The loss for epoch 7
1.0406083037455878
The running loss is:
15.097268715500832
The number of items in train is:
15
The loss for epoch 8
1.0064845810333887
The running loss is:
14.87123168259859
The number of items in train is:
15
The loss for epoch 9
0.9914154455065727
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.172585
47 30819 Eagle County, Colorado, United States ... 47 8.545061
48 30820 Eagle County, Colorado, United States ... 48 8.406359
49 30821 Eagle County, Colorado, United States ... 49 7.705727
50 30822 Eagle County, Colorado, United States ... 50 7.680320
51 30823 Eagle County, Colorado, United States ... 51 5.664755
52 30824 Eagle County, Colorado, United States ... 52 3.960229
53 30825 Eagle County, Colorado, United States ... 53 4.914542
54 30826 Eagle County, Colorado, United States ... 54 7.783839
55 30827 Eagle County, Colorado, United States ... 55 8.135820
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n0i03nbs wandb: Agent Starting Run: yjybu031 with config: batch_size: 2 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yjybu031
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.16425657272339
The number of items in train is:
16
The loss for epoch 0
1.1977660357952118
The running loss is:
24.791586220264435
The number of items in train is:
16
The loss for epoch 1
1.5494741387665272
The running loss is:
21.69253620505333
The number of items in train is:
16
The loss for epoch 2
1.355783512815833
The running loss is:
16.800780154764652
The number of items in train is:
16
The loss for epoch 3
1.0500487596727908
The running loss is:
16.302987061440945
The number of items in train is:
16
The loss for epoch 4
1.018936691340059
The running loss is:
15.405229218304157
The number of items in train is:
16
The loss for epoch 5
0.9628268261440098
The running loss is:
14.881639704108238
The number of items in train is:
16
The loss for epoch 6
0.9301024815067649
The running loss is:
14.712513819336891
The number of items in train is:
16
The loss for epoch 7
0.9195321137085557
The running loss is:
15.10964523628354
The number of items in train is:
16
The loss for epoch 8
0.9443528272677213
The running loss is:
16.02715666871518
The number of items in train is:
16
The loss for epoch 9
1.0016972917946987
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.599871
47 30819 ... 10.097055
48 30820 ... 8.892070
49 30821 ... 7.969182
50 30822 ... 8.750723
51 30823 ... 7.703031
52 30824 ... 6.274693
53 30825 ... 6.066268
54 30826 ... 8.236106
55 30827 ... 8.333554
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yjybu031 wandb: Agent Starting Run: miyu4pi3 with config: batch_size: 2 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: miyu4pi3
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.28632080554962
The number of items in train is:
16
The loss for epoch 0
1.2678950503468513
The running loss is:
24.294055610895157
The number of items in train is:
16
The loss for epoch 1
1.5183784756809473
The running loss is:
21.431798800826073
The number of items in train is:
16
The loss for epoch 2
1.3394874250516295
The running loss is:
16.71895857900381
The number of items in train is:
16
The loss for epoch 3
1.0449349111877382
The running loss is:
16.85727497190237
The number of items in train is:
16
The loss for epoch 4
1.0535796857438982
The running loss is:
16.236333053559065
The number of items in train is:
16
The loss for epoch 5
1.0147708158474416
The running loss is:
15.517197554931045
The number of items in train is:
16
The loss for epoch 6
0.9698248471831903
The running loss is:
15.630752064287663
The number of items in train is:
16
The loss for epoch 7
0.9769220040179789
The running loss is:
14.89614998549223
The number of items in train is:
16
The loss for epoch 8
0.9310093740932643
The running loss is:
18.13109051436186
The number of items in train is:
16
The loss for epoch 9
1.1331931571476161
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.372117
47 30819 Eagle County, Colorado, United States ... 47 6.291941
48 30820 Eagle County, Colorado, United States ... 48 8.174136
49 30821 Eagle County, Colorado, United States ... 49 6.047145
50 30822 Eagle County, Colorado, United States ... 50 5.574130
51 30823 Eagle County, Colorado, United States ... 51 4.054066
52 30824 Eagle County, Colorado, United States ... 52 4.882196
53 30825 Eagle County, Colorado, United States ... 53 4.373847
54 30826 Eagle County, Colorado, United States ... 54 4.788294
55 30827 Eagle County, Colorado, United States ... 55 5.587177
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: miyu4pi3 wandb: Agent Starting Run: 6l418pc3 with config: batch_size: 2 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 6l418pc3
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.847505494952202
The number of items in train is:
15
The loss for epoch 0
1.1898336996634802
The running loss is:
22.748151302337646
The number of items in train is:
15
The loss for epoch 1
1.5165434201558432
The running loss is:
18.75277553498745
The number of items in train is:
15
The loss for epoch 2
1.25018503566583
The running loss is:
16.23998997360468
The number of items in train is:
15
The loss for epoch 3
1.082665998240312
The running loss is:
16.405739322304726
The number of items in train is:
15
The loss for epoch 4
1.093715954820315
The running loss is:
15.832581028342247
The number of items in train is:
15
The loss for epoch 5
1.0555054018894832
The running loss is:
14.198189176619053
The number of items in train is:
15
The loss for epoch 6
0.9465459451079369
The running loss is:
14.678221568465233
The number of items in train is:
15
The loss for epoch 7
0.9785481045643488
The running loss is:
14.704874739050865
The number of items in train is:
15
The loss for epoch 8
0.980324982603391
The running loss is:
13.837015897035599
The number of items in train is:
15
The loss for epoch 9
0.92246772646904
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.811941
47 30819 Eagle County, Colorado, United States ... 47 7.373936
48 30820 Eagle County, Colorado, United States ... 48 6.976442
49 30821 Eagle County, Colorado, United States ... 49 6.321370
50 30822 Eagle County, Colorado, United States ... 50 6.951790
51 30823 Eagle County, Colorado, United States ... 51 3.973511
52 30824 Eagle County, Colorado, United States ... 52 2.230998
53 30825 Eagle County, Colorado, United States ... 53 1.945158
54 30826 Eagle County, Colorado, United States ... 54 5.537347
55 30827 Eagle County, Colorado, United States ... 55 4.562379
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 6l418pc3 wandb: Agent Starting Run: 2lswnnys with config: batch_size: 2 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 2lswnnys
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
28.321928784251213
The number of items in train is:
16
The loss for epoch 0
1.7701205490157008
The running loss is:
23.84320007637143
The number of items in train is:
16
The loss for epoch 1
1.4902000047732145
The running loss is:
22.800938323140144
The number of items in train is:
16
The loss for epoch 2
1.425058645196259
The running loss is:
16.60193409025669
The number of items in train is:
16
The loss for epoch 3
1.0376208806410432
The running loss is:
16.297849643044174
The number of items in train is:
16
The loss for epoch 4
1.0186156026902609
The running loss is:
15.142806701362133
The number of items in train is:
16
The loss for epoch 5
0.9464254188351333
The running loss is:
15.968816300854087
The number of items in train is:
16
The loss for epoch 6
0.9980510188033804
The running loss is:
18.68184170126915
The number of items in train is:
16
The loss for epoch 7
1.1676151063293219
The running loss is:
17.71508727967739
The number of items in train is:
16
The loss for epoch 8
1.107192954979837
The running loss is:
17.00942861661315
The number of items in train is:
16
The loss for epoch 9
1.0630892885383219
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 12.924442
47 30819 ... 11.307852
48 30820 ... 11.383236
49 30821 ... 11.235537
50 30822 ... 10.485743
51 30823 ... 10.882519
52 30824 ... 12.352532
53 30825 ... 11.872038
54 30826 ... 10.437772
55 30827 ... 12.334542
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2lswnnys wandb: Agent Starting Run: s96dsy11 with config: batch_size: 2 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: s96dsy11
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
29.96261489391327
The number of items in train is:
16
The loss for epoch 0
1.8726634308695793
The running loss is:
27.067424595355988
The number of items in train is:
16
The loss for epoch 1
1.6917140372097492
The running loss is:
20.166864212602377
The number of items in train is:
16
The loss for epoch 2
1.2604290132876486
The running loss is:
17.68713990226388
The number of items in train is:
16
The loss for epoch 3
1.1054462438914925
The running loss is:
16.726590804755688
The number of items in train is:
16
The loss for epoch 4
1.0454119252972305
The running loss is:
16.821392374113202
The number of items in train is:
16
The loss for epoch 5
1.0513370233820751
The running loss is:
15.821807194501162
The number of items in train is:
16
The loss for epoch 6
0.9888629496563226
The running loss is:
15.549790024757385
The number of items in train is:
16
The loss for epoch 7
0.9718618765473366
The running loss is:
17.553053379058838
The number of items in train is:
16
The loss for epoch 8
1.0970658361911774
The running loss is:
16.198522921651602
The number of items in train is:
16
The loss for epoch 9
1.0124076826032251
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 7.124155
47 30819 Eagle County, Colorado, United States ... 47 7.601325
48 30820 Eagle County, Colorado, United States ... 48 7.351948
49 30821 Eagle County, Colorado, United States ... 49 6.322805
50 30822 Eagle County, Colorado, United States ... 50 7.087974
51 30823 Eagle County, Colorado, United States ... 51 6.653691
52 30824 Eagle County, Colorado, United States ... 52 6.018229
53 30825 Eagle County, Colorado, United States ... 53 5.255400
54 30826 Eagle County, Colorado, United States ... 54 6.463150
55 30827 Eagle County, Colorado, United States ... 55 6.508754
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: s96dsy11 wandb: Agent Starting Run: ox8sw2mt with config: batch_size: 2 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ox8sw2mt
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
24.2190171033144
The number of items in train is:
15
The loss for epoch 0
1.61460114022096
The running loss is:
23.19199651479721
The number of items in train is:
15
The loss for epoch 1
1.5461331009864807
The running loss is:
19.841294646263123
The number of items in train is:
15
The loss for epoch 2
1.3227529764175414
The running loss is:
16.733892038464546
The number of items in train is:
15
The loss for epoch 3
1.1155928025643032
The running loss is:
16.701290532946587
The number of items in train is:
15
The loss for epoch 4
1.1134193688631058
The running loss is:
16.376007974147797
The number of items in train is:
15
The loss for epoch 5
1.0917338649431865
The running loss is:
15.544721752405167
The number of items in train is:
15
The loss for epoch 6
1.0363147834936777
The running loss is:
14.802310332655907
The number of items in train is:
15
The loss for epoch 7
0.9868206888437271
The running loss is:
16.197223231196404
The number of items in train is:
15
The loss for epoch 8
1.0798148820797602
The running loss is:
17.143785387277603
The number of items in train is:
15
The loss for epoch 9
1.142919025818507
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.421041
47 30819 ... 10.157938
48 30820 ... 9.647425
49 30821 ... 9.630416
50 30822 ... 10.029798
51 30823 ... 9.603886
52 30824 ... 7.974997
53 30825 ... 8.477596
54 30826 ... 9.787393
55 30827 ... 8.910323
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ox8sw2mt wandb: Agent Starting Run: 1j4ina8x with config: batch_size: 2 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1j4ina8x
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
108.48466435819864
The number of items in train is:
16
The loss for epoch 0
6.780291522387415
The running loss is:
37.332396514713764
The number of items in train is:
16
The loss for epoch 1
2.3332747821696103
The running loss is:
20.24184750393033
The number of items in train is:
16
The loss for epoch 2
1.2651154689956456
The running loss is:
19.149915374815464
The number of items in train is:
16
The loss for epoch 3
1.1968697109259665
The running loss is:
19.72006557881832
The number of items in train is:
16
The loss for epoch 4
1.232504098676145
The running loss is:
17.883113749325275
The number of items in train is:
16
The loss for epoch 5
1.1176946093328297
The running loss is:
17.11849595978856
The number of items in train is:
16
The loss for epoch 6
1.069905997486785
The running loss is:
16.509005554020405
The number of items in train is:
16
The loss for epoch 7
1.0318128471262753
The running loss is:
18.953058928251266
The number of items in train is:
16
The loss for epoch 8
1.1845661830157042
The running loss is:
19.251508221030235
The number of items in train is:
16
The loss for epoch 9
1.2032192638143897
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.076435
47 30819 ... 11.008322
48 30820 ... 11.043419
49 30821 ... 11.140252
50 30822 ... 11.340688
51 30823 ... 11.105280
52 30824 ... 10.863495
53 30825 ... 11.017091
54 30826 ... 10.999365
55 30827 ... 10.982702
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1j4ina8x wandb: Agent Starting Run: l32pcy0y with config: batch_size: 2 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: l32pcy0y
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
106.40463045239449
The number of items in train is:
16
The loss for epoch 0
6.650289403274655
The running loss is:
32.68300420045853
The number of items in train is:
16
The loss for epoch 1
2.042687762528658
The running loss is:
21.02730058133602
The number of items in train is:
16
The loss for epoch 2
1.3142062863335013
The running loss is:
22.76759300008416
The number of items in train is:
16
The loss for epoch 3
1.42297456250526
The running loss is:
20.224891159683466
The number of items in train is:
16
The loss for epoch 4
1.2640556974802166
The running loss is:
20.061361081898212
The number of items in train is:
16
The loss for epoch 5
1.2538350676186383
The running loss is:
18.02659384161234
The number of items in train is:
16
The loss for epoch 6
1.1266621151007712
The running loss is:
17.840649589896202
The number of items in train is:
16
The loss for epoch 7
1.1150405993685126
The running loss is:
17.845503389835358
The number of items in train is:
16
The loss for epoch 8
1.1153439618647099
The running loss is:
18.144714556634426
The number of items in train is:
16
The loss for epoch 9
1.1340446597896516
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.451546
47 30819 Eagle County, Colorado, United States ... 47 9.509930
48 30820 Eagle County, Colorado, United States ... 48 9.710898
49 30821 Eagle County, Colorado, United States ... 49 9.667391
50 30822 Eagle County, Colorado, United States ... 50 9.587912
51 30823 Eagle County, Colorado, United States ... 51 9.663891
52 30824 Eagle County, Colorado, United States ... 52 9.581569
53 30825 Eagle County, Colorado, United States ... 53 9.588292
54 30826 Eagle County, Colorado, United States ... 54 9.580448
55 30827 Eagle County, Colorado, United States ... 55 9.681818
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l32pcy0y wandb: Agent Starting Run: e65jo2m6 with config: batch_size: 2 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: e65jo2m6
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 2
dataset_params:
desc: null
value:
batch_size: 2
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 2
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
80.18639262020588
The number of items in train is:
15
The loss for epoch 0
5.3457595080137255
The running loss is:
28.25533753633499
The number of items in train is:
15
The loss for epoch 1
1.8836891690889994
The running loss is:
18.94506999105215
The number of items in train is:
15
The loss for epoch 2
1.2630046660701433
The running loss is:
17.882804982364178
The number of items in train is:
15
The loss for epoch 3
1.1921869988242786
The running loss is:
17.178523786365986
The number of items in train is:
15
The loss for epoch 4
1.1452349190910658
The running loss is:
19.025928854942322
The number of items in train is:
15
The loss for epoch 5
1.2683952569961547
The running loss is:
17.12258891016245
The number of items in train is:
15
The loss for epoch 6
1.1415059273441632
The running loss is:
16.434594467282295
The number of items in train is:
15
The loss for epoch 7
1.095639631152153
The running loss is:
17.38167379796505
The number of items in train is:
15
The loss for epoch 8
1.15877825319767
The running loss is:
17.034118846058846
The number of items in train is:
15
The loss for epoch 9
1.1356079230705898
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.681185
47 30819 ... 10.923750
48 30820 ... 8.556581
49 30821 ... 8.627446
50 30822 ... 8.821712
51 30823 ... 8.461462
52 30824 ... 8.276463
53 30825 ... 8.955903
54 30826 ... 9.159882
55 30827 ... 8.890931
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: e65jo2m6 wandb: Agent Starting Run: r2moei7q with config: batch_size: 3 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: r2moei7q
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.59494494833052
The number of items in train is:
14
The loss for epoch 0
1.32821035345218
The running loss is:
14.932796542532742
The number of items in train is:
14
The loss for epoch 1
1.0666283244666244
The running loss is:
14.904814524576068
The number of items in train is:
14
The loss for epoch 2
1.0646296088982905
The running loss is:
14.451682602986693
The number of items in train is:
14
The loss for epoch 3
1.032263043070478
The running loss is:
13.970589200034738
The number of items in train is:
14
The loss for epoch 4
0.9978992285739098
The running loss is:
14.210589300841093
The number of items in train is:
14
The loss for epoch 5
1.015042092917221
The running loss is:
13.587398022413254
The number of items in train is:
14
The loss for epoch 6
0.9705284301723752
The running loss is:
14.565642356872559
The number of items in train is:
14
The loss for epoch 7
1.0404030254908971
The running loss is:
14.67211166024208
The number of items in train is:
14
The loss for epoch 8
1.0480079757315772
The running loss is:
14.311140194535255
The number of items in train is:
14
The loss for epoch 9
1.022224299609661
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 10.055877
47 30819 ... 11.829143
48 30820 ... 11.898178
49 30821 ... 11.568399
50 30822 ... 11.145294
51 30823 ... 10.700349
52 30824 ... 10.250292
53 30825 ... 12.220572
54 30826 ... 12.335711
55 30827 ... 12.016722
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r2moei7q wandb: Agent Starting Run: fximbnf8 with config: batch_size: 3 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fximbnf8
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.81448957324028
The number of items in train is:
14
The loss for epoch 0
1.6296063980885915
The running loss is:
20.114689007401466
The number of items in train is:
14
The loss for epoch 1
1.436763500528676
The running loss is:
19.003370255231857
The number of items in train is:
14
The loss for epoch 2
1.3573835896594184
The running loss is:
18.38408713042736
The number of items in train is:
14
The loss for epoch 3
1.3131490807448114
The running loss is:
18.05182459950447
The number of items in train is:
14
The loss for epoch 4
1.2894160428217478
The running loss is:
18.1113803088665
The number of items in train is:
14
The loss for epoch 5
1.2936700220618929
The running loss is:
18.247668206691742
The number of items in train is:
14
The loss for epoch 6
1.303404871906553
The running loss is:
17.699394717812538
The number of items in train is:
14
The loss for epoch 7
1.2642424798437528
The running loss is:
17.261331766843796
The number of items in train is:
14
The loss for epoch 8
1.2329522690602712
The running loss is:
17.405240193009377
The number of items in train is:
14
The loss for epoch 9
1.2432314423578126
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 15.450606
47 30819 ... 19.255352
48 30820 ... 19.566013
49 30821 ... 18.729879
50 30822 ... 17.517355
51 30823 ... 16.181293
52 30824 ... 14.804688
53 30825 ... 19.981453
54 30826 ... 20.742424
55 30827 ... 20.054089
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fximbnf8 wandb: Agent Starting Run: 76xgyieq with config: batch_size: 3 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 76xgyieq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.649044513702393
The number of items in train is:
13
The loss for epoch 0
1.6653111164386456
The running loss is:
20.08183240890503
The number of items in train is:
13
The loss for epoch 1
1.5447563391465406
The running loss is:
18.43745982646942
The number of items in train is:
13
The loss for epoch 2
1.4182661404976478
The running loss is:
17.936023265123367
The number of items in train is:
13
The loss for epoch 3
1.379694097317182
The running loss is:
17.735933303833008
The number of items in train is:
13
The loss for epoch 4
1.3643025618333082
The running loss is:
17.864655077457428
The number of items in train is:
13
The loss for epoch 5
1.3742042367274945
The running loss is:
17.435856461524963
The number of items in train is:
13
The loss for epoch 6
1.3412197278096125
The running loss is:
17.46800085902214
The number of items in train is:
13
The loss for epoch 7
1.3436923737709339
The running loss is:
17.538733899593353
The number of items in train is:
13
The loss for epoch 8
1.3491333768917964
The running loss is:
17.084585398435593
The number of items in train is:
13
The loss for epoch 9
1.314198876802738
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 1.993502
47 30819 Eagle County, Colorado, United States ... 47 1.660632
48 30820 Eagle County, Colorado, United States ... 48 1.195935
49 30821 Eagle County, Colorado, United States ... 49 0.718136
50 30822 Eagle County, Colorado, United States ... 50 0.239035
51 30823 Eagle County, Colorado, United States ... 51 -0.240196
52 30824 Eagle County, Colorado, United States ... 52 -0.719441
53 30825 Eagle County, Colorado, United States ... 53 1.822607
54 30826 Eagle County, Colorado, United States ... 54 1.643647
55 30827 Eagle County, Colorado, United States ... 55 1.194247
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 76xgyieq wandb: Agent Starting Run: 0yngjqqa with config: batch_size: 3 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0yngjqqa
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.013466119766235
The number of items in train is:
14
The loss for epoch 0
1.143819008554731
The running loss is:
29.16191405057907
The number of items in train is:
14
The loss for epoch 1
2.0829938607556477
The running loss is:
17.242529824376106
The number of items in train is:
14
The loss for epoch 2
1.231609273169722
The running loss is:
15.2852763235569
The number of items in train is:
14
The loss for epoch 3
1.0918054516826357
The running loss is:
13.825423995032907
The number of items in train is:
14
The loss for epoch 4
0.9875302853594933
The running loss is:
14.278043230995536
The number of items in train is:
14
The loss for epoch 5
1.0198602307853954
The running loss is:
13.592282935976982
The number of items in train is:
14
The loss for epoch 6
0.9708773525697845
The running loss is:
14.36550104059279
The number of items in train is:
14
The loss for epoch 7
1.0261072171851993
The running loss is:
14.437449997290969
The number of items in train is:
14
The loss for epoch 8
1.0312464283779263
The running loss is:
14.289774606004357
The number of items in train is:
14
The loss for epoch 9
1.0206981861431683
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 10.096048
47 30819 ... 11.764206
48 30820 ... 11.783741
49 30821 ... 11.437365
50 30822 ... 11.009774
51 30823 ... 10.564157
52 30824 ... 10.114541
53 30825 ... 12.119022
54 30826 ... 12.213205
55 30827 ... 11.883397
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0yngjqqa wandb: Agent Starting Run: fjhq2m63 with config: batch_size: 3 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fjhq2m63
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.899971932172775
The number of items in train is:
14
The loss for epoch 0
1.4214265665837698
The running loss is:
30.802632376551628
The number of items in train is:
14
The loss for epoch 1
2.200188026896545
The running loss is:
19.786646991968155
The number of items in train is:
14
The loss for epoch 2
1.4133319279977254
The running loss is:
18.989270001649857
The number of items in train is:
14
The loss for epoch 3
1.3563764286892754
The running loss is:
17.26893775165081
The number of items in train is:
14
The loss for epoch 4
1.2334955536893435
The running loss is:
17.307947099208832
The number of items in train is:
14
The loss for epoch 5
1.2362819356577737
The running loss is:
17.254249587655067
The number of items in train is:
14
The loss for epoch 6
1.232446399118219
The running loss is:
16.732941687107086
The number of items in train is:
14
The loss for epoch 7
1.195210120507649
The running loss is:
16.49874599277973
The number of items in train is:
14
The loss for epoch 8
1.1784818566271238
The running loss is:
16.410493820905685
The number of items in train is:
14
The loss for epoch 9
1.1721781300646918
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 14.413111
47 30819 ... 17.841599
48 30820 ... 18.107571
49 30821 ... 17.371849
50 30822 ... 16.318855
51 30823 ... 15.165368
52 30824 ... 13.980051
53 30825 ... 18.524395
54 30826 ... 19.143803
55 30827 ... 18.520027
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fjhq2m63 wandb: Agent Starting Run: cptzspm9 with config: batch_size: 3 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: cptzspm9
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.011935591697693
The number of items in train is:
13
The loss for epoch 0
1.3855335070536687
The running loss is:
31.434290528297424
The number of items in train is:
13
The loss for epoch 1
2.418022348330571
The running loss is:
19.867827773094177
The number of items in train is:
13
The loss for epoch 2
1.5282944440841675
The running loss is:
18.71837419271469
The number of items in train is:
13
The loss for epoch 3
1.4398749379011302
The running loss is:
17.043402820825577
The number of items in train is:
13
The loss for epoch 4
1.3110309862173521
The running loss is:
17.26927536725998
The number of items in train is:
13
The loss for epoch 5
1.3284057974815369
The running loss is:
16.922881990671158
The number of items in train is:
13
The loss for epoch 6
1.3017601531285505
The running loss is:
16.785142093896866
The number of items in train is:
13
The loss for epoch 7
1.2911647764536052
The running loss is:
16.733474850654602
The number of items in train is:
13
The loss for epoch 8
1.2871903731272771
The running loss is:
16.36581662297249
The number of items in train is:
13
The loss for epoch 9
1.2589089709978838
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.694916
47 30819 Eagle County, Colorado, United States ... 47 2.521640
48 30820 Eagle County, Colorado, United States ... 48 2.190051
49 30821 Eagle County, Colorado, United States ... 49 1.845047
50 30822 Eagle County, Colorado, United States ... 50 1.498905
51 30823 Eagle County, Colorado, United States ... 51 1.152667
52 30824 Eagle County, Colorado, United States ... 52 0.806421
53 30825 Eagle County, Colorado, United States ... 53 2.678512
54 30826 Eagle County, Colorado, United States ... 54 2.520250
55 30827 Eagle County, Colorado, United States ... 55 2.189933
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cptzspm9 wandb: Agent Starting Run: v3ynd9po with config: batch_size: 3 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: v3ynd9po
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.401278633624315
The number of items in train is:
14
The loss for epoch 0
1.2429484738303083
The running loss is:
20.994035825133324
The number of items in train is:
14
The loss for epoch 1
1.499573987509523
The running loss is:
20.901939246803522
The number of items in train is:
14
The loss for epoch 2
1.4929956604859658
The running loss is:
17.49182690680027
The number of items in train is:
14
The loss for epoch 3
1.2494162076285906
The running loss is:
14.579859712161124
The number of items in train is:
14
The loss for epoch 4
1.0414185508686518
The running loss is:
14.753086706623435
The number of items in train is:
14
The loss for epoch 5
1.0537919076159596
The running loss is:
13.997532527893782
The number of items in train is:
14
The loss for epoch 6
0.999823751992413
The running loss is:
14.817034468054771
The number of items in train is:
14
The loss for epoch 7
1.058359604861055
The running loss is:
14.553301157429814
The number of items in train is:
14
The loss for epoch 8
1.0395215112449867
The running loss is:
14.703020714223385
The number of items in train is:
14
The loss for epoch 9
1.0502157653016704
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 10.369466
47 30819 ... 11.836428
48 30820 ... 11.770448
49 30821 ... 11.407104
50 30822 ... 10.986075
51 30823 ... 10.553859
52 30824 ... 10.119472
53 30825 ... 12.138479
54 30826 ... 12.179585
55 30827 ... 11.837014
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: v3ynd9po wandb: Agent Starting Run: 30q9ac39 with config: batch_size: 3 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 30q9ac39
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.857100248336792
The number of items in train is:
14
The loss for epoch 0
1.418364303452628
The running loss is:
26.54387801885605
The number of items in train is:
14
The loss for epoch 1
1.8959912870611464
The running loss is:
23.77830880880356
The number of items in train is:
14
The loss for epoch 2
1.6984506292002541
The running loss is:
20.03038616478443
The number of items in train is:
14
The loss for epoch 3
1.4307418689131737
The running loss is:
17.19534194469452
The number of items in train is:
14
The loss for epoch 4
1.2282387103353227
The running loss is:
16.544086322188377
The number of items in train is:
14
The loss for epoch 5
1.181720451584884
The running loss is:
16.140186935663223
The number of items in train is:
14
The loss for epoch 6
1.152870495404516
The running loss is:
15.713112562894821
The number of items in train is:
14
The loss for epoch 7
1.1223651830639159
The running loss is:
15.244650691747665
The number of items in train is:
14
The loss for epoch 8
1.088903620839119
The running loss is:
14.965971872210503
The number of items in train is:
14
The loss for epoch 9
1.0689979908721787
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 13.930508
47 30819 ... 16.271799
48 30820 ... 16.045662
49 30821 ... 15.197029
50 30822 ... 14.197470
51 30823 ... 13.161317
52 30824 ... 12.116292
53 30825 ... 16.625732
54 30826 ... 16.925278
55 30827 ... 16.204102
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 30q9ac39 wandb: Agent Starting Run: fcdxmr7c with config: batch_size: 3 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: fcdxmr7c
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.934100329875946
The number of items in train is:
13
The loss for epoch 0
1.4564692561443036
The running loss is:
27.40670943260193
The number of items in train is:
13
The loss for epoch 1
2.108208417892456
The running loss is:
23.129272490739822
The number of items in train is:
13
The loss for epoch 2
1.7791748069799864
The running loss is:
19.054784208536148
The number of items in train is:
13
The loss for epoch 3
1.4657526314258575
The running loss is:
16.83181044459343
The number of items in train is:
13
The loss for epoch 4
1.29475464958411
The running loss is:
16.373175472021103
The number of items in train is:
13
The loss for epoch 5
1.2594750363093157
The running loss is:
15.920186161994934
The number of items in train is:
13
The loss for epoch 6
1.224629704768841
The running loss is:
15.883338451385498
The number of items in train is:
13
The loss for epoch 7
1.221795265491192
The running loss is:
15.632668197154999
The number of items in train is:
13
The loss for epoch 8
1.2025129382426922
The running loss is:
15.228438049554825
The number of items in train is:
13
The loss for epoch 9
1.1714183115042174
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.237244
47 30819 Eagle County, Colorado, United States ... 47 4.232128
48 30820 Eagle County, Colorado, United States ... 48 3.997910
49 30821 Eagle County, Colorado, United States ... 49 3.747505
50 30822 Eagle County, Colorado, United States ... 50 3.495956
51 30823 Eagle County, Colorado, United States ... 51 3.244326
52 30824 Eagle County, Colorado, United States ... 52 2.992691
53 30825 Eagle County, Colorado, United States ... 53 4.378044
54 30826 Eagle County, Colorado, United States ... 54 4.242076
55 30827 Eagle County, Colorado, United States ... 55 3.998613
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fcdxmr7c wandb: Agent Starting Run: t1l0vtle with config: batch_size: 3 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: t1l0vtle
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
34.37906017899513
The number of items in train is:
14
The loss for epoch 0
2.4556471556425095
The running loss is:
26.15366743505001
The number of items in train is:
14
The loss for epoch 1
1.8681191025035722
The running loss is:
25.3820013217628
The number of items in train is:
14
The loss for epoch 2
1.8130000944116287
The running loss is:
28.283599134534597
The number of items in train is:
14
The loss for epoch 3
2.0202570810381855
The running loss is:
33.98149111866951
The number of items in train is:
14
The loss for epoch 4
2.4272493656192506
The running loss is:
17.64745257794857
The number of items in train is:
14
The loss for epoch 5
1.2605323269963264
The running loss is:
15.027765817940235
The number of items in train is:
14
The loss for epoch 6
1.0734118441385883
The running loss is:
14.682047221809626
The number of items in train is:
14
The loss for epoch 7
1.0487176587006874
The running loss is:
14.17528066970408
The number of items in train is:
14
The loss for epoch 8
1.0125200478360057
The running loss is:
14.080418163910508
The number of items in train is:
14
The loss for epoch 9
1.0057441545650363
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 9.958035
47 30819 ... 11.445734
48 30820 ... 11.345182
49 30821 ... 10.906959
50 30822 ... 10.396943
51 30823 ... 9.871664
52 30824 ... 9.343140
53 30825 ... 11.731848
54 30826 ... 11.822859
55 30827 ... 11.425363
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: t1l0vtle wandb: Agent Starting Run: zwxvm8ym with config: batch_size: 3 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: zwxvm8ym
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
37.94893169403076
The number of items in train is:
14
The loss for epoch 0
2.7106379781450545
The running loss is:
27.68363320827484
The number of items in train is:
14
The loss for epoch 1
1.9774023720196314
The running loss is:
26.667637139558792
The number of items in train is:
14
The loss for epoch 2
1.9048312242541994
The running loss is:
27.63523341715336
The number of items in train is:
14
The loss for epoch 3
1.9739452440823828
The running loss is:
21.57915799319744
The number of items in train is:
14
The loss for epoch 4
1.5413684280855315
The running loss is:
21.874824732542038
The number of items in train is:
14
The loss for epoch 5
1.5624874808958598
The running loss is:
14.983947649598122
The number of items in train is:
14
The loss for epoch 6
1.0702819749712944
The running loss is:
14.43506047129631
The number of items in train is:
14
The loss for epoch 7
1.0310757479497366
The running loss is:
14.08886642754078
The number of items in train is:
14
The loss for epoch 8
1.0063476019671984
The running loss is:
13.513579778373241
The number of items in train is:
14
The loss for epoch 9
0.9652556984552315
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 12.079294
47 30819 ... 14.102061
48 30820 ... 13.870899
49 30821 ... 13.078794
50 30822 ... 12.147085
51 30823 ... 11.180633
52 30824 ... 10.205533
53 30825 ... 14.370306
54 30826 ... 14.672234
55 30827 ... 14.012800
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: zwxvm8ym wandb: Agent Starting Run: 0ns4eryb with config: batch_size: 3 forecast_history: 1 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 0ns4eryb
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
45.304227113723755
The number of items in train is:
13
The loss for epoch 0
3.4849405472095194
The running loss is:
31.466166585683823
The number of items in train is:
13
The loss for epoch 1
2.4204743527449093
The running loss is:
27.548714011907578
The number of items in train is:
13
The loss for epoch 2
2.1191318470698137
The running loss is:
22.79436346888542
The number of items in train is:
13
The loss for epoch 3
1.7534125745296478
The running loss is:
17.69319573044777
The number of items in train is:
13
The loss for epoch 4
1.3610150561882899
The running loss is:
16.08399274945259
The number of items in train is:
13
The loss for epoch 5
1.2372302114963531
The running loss is:
15.254592299461365
The number of items in train is:
13
The loss for epoch 6
1.1734301768816435
The running loss is:
16.17251518368721
The number of items in train is:
13
The loss for epoch 7
1.2440396295144007
The running loss is:
15.37093037366867
The number of items in train is:
13
The loss for epoch 8
1.1823792595129747
The running loss is:
14.669757455587387
The number of items in train is:
13
The loss for epoch 9
1.1284428811990297
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 7.828729
47 30819 Eagle County, Colorado, United States ... 47 8.117490
48 30820 Eagle County, Colorado, United States ... 48 7.883338
49 30821 Eagle County, Colorado, United States ... 49 7.607377
50 30822 Eagle County, Colorado, United States ... 50 7.328072
51 30823 Eagle County, Colorado, United States ... 51 7.048500
52 30824 Eagle County, Colorado, United States ... 52 6.768906
53 30825 Eagle County, Colorado, United States ... 53 8.289990
54 30826 Eagle County, Colorado, United States ... 54 8.154371
55 30827 Eagle County, Colorado, United States ... 55 7.886288
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0ns4eryb wandb: Agent Starting Run: 8e0eacod with config: batch_size: 3 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 8e0eacod
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
19.603286884725094
The number of items in train is:
14
The loss for epoch 0
1.4002347774803638
The running loss is:
16.837858743965626
The number of items in train is:
14
The loss for epoch 1
1.2027041959975446
The running loss is:
13.142932513728738
The number of items in train is:
14
The loss for epoch 2
0.938780893837767
The running loss is:
12.648434773087502
The number of items in train is:
14
The loss for epoch 3
0.9034596266491073
The running loss is:
12.131098728626966
The number of items in train is:
14
The loss for epoch 4
0.8665070520447833
The running loss is:
12.628641948103905
The number of items in train is:
14
The loss for epoch 5
0.9020458534359932
The running loss is:
11.111840911209583
The number of items in train is:
14
The loss for epoch 6
0.793702922229256
The running loss is:
12.15914048999548
The number of items in train is:
14
The loss for epoch 7
0.8685100349996772
The running loss is:
10.403061028569937
The number of items in train is:
14
The loss for epoch 8
0.7430757877549955
The running loss is:
11.373059086501598
The number of items in train is:
14
The loss for epoch 9
0.8123613633215427
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.309699
47 30819 Eagle County, Colorado, United States ... 47 5.267597
48 30820 Eagle County, Colorado, United States ... 48 6.171280
49 30821 Eagle County, Colorado, United States ... 49 5.798432
50 30822 Eagle County, Colorado, United States ... 50 4.700201
51 30823 Eagle County, Colorado, United States ... 51 3.081073
52 30824 Eagle County, Colorado, United States ... 52 1.101784
53 30825 Eagle County, Colorado, United States ... 53 0.857389
54 30826 Eagle County, Colorado, United States ... 54 5.437455
55 30827 Eagle County, Colorado, United States ... 55 6.270850
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8e0eacod wandb: Agent Starting Run: 9bth5gk6 with config: batch_size: 3 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 9bth5gk6
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.307483822107315
The number of items in train is:
13
The loss for epoch 0
1.2544218324697936
The running loss is:
16.8885560631752
The number of items in train is:
13
The loss for epoch 1
1.2991196971673231
The running loss is:
14.11893281340599
The number of items in train is:
13
The loss for epoch 2
1.086071754877384
The running loss is:
13.040117263793945
The number of items in train is:
13
The loss for epoch 3
1.003085943368765
The running loss is:
12.399544507265091
The number of items in train is:
13
The loss for epoch 4
0.9538111159434686
The running loss is:
12.317954629659653
The number of items in train is:
13
The loss for epoch 5
0.9475349715122809
The running loss is:
12.517528355121613
The number of items in train is:
13
The loss for epoch 6
0.9628867965478164
The running loss is:
11.37213283777237
The number of items in train is:
13
The loss for epoch 7
0.8747794490594131
The running loss is:
11.30318507552147
The number of items in train is:
13
The loss for epoch 8
0.869475775040113
The running loss is:
11.03271347284317
The number of items in train is:
13
The loss for epoch 9
0.8486702671417823
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... -1.502937
47 30819 ... 10.155432
48 30820 ... 10.315764
49 30821 ... 9.580840
50 30822 ... 6.320834
51 30823 ... 2.762872
52 30824 ... -2.164825
53 30825 ... -2.477209
54 30826 ... 8.475018
55 30827 ... 9.378270
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9bth5gk6 wandb: Agent Starting Run: 8xkfkomp with config: batch_size: 3 forecast_history: 2 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8xkfkomp
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.484009578824043
The number of items in train is:
13
The loss for epoch 0
1.4218468906787725
The running loss is:
16.133168160915375
The number of items in train is:
13
The loss for epoch 1
1.2410129354550288
The running loss is:
14.021970570087433
The number of items in train is:
13
The loss for epoch 2
1.0786131207759564
The running loss is:
13.871418491005898
The number of items in train is:
13
The loss for epoch 3
1.0670321916158383
The running loss is:
13.513418480753899
The number of items in train is:
13
The loss for epoch 4
1.0394937292887614
The running loss is:
13.288902163505554
The number of items in train is:
13
The loss for epoch 5
1.022223243346581
The running loss is:
13.067702129483223
The number of items in train is:
13
The loss for epoch 6
1.005207856114094
The running loss is:
12.999311462044716
The number of items in train is:
13
The loss for epoch 7
0.9999470355419012
The running loss is:
13.027460411190987
The number of items in train is:
13
The loss for epoch 8
1.0021123393223836
The running loss is:
12.958777263760567
The number of items in train is:
13
The loss for epoch 9
0.9968290202892743
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.103645
47 30819 ... 10.392696
48 30820 ... 11.688851
49 30821 ... 12.198536
50 30822 ... 11.687592
51 30823 ... 10.778344
52 30824 ... 9.438768
53 30825 ... 10.621546
54 30826 ... 13.821482
55 30827 ... 13.794540
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8xkfkomp wandb: Agent Starting Run: d240mu9g with config: batch_size: 3 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: d240mu9g
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.578325545415282
The number of items in train is:
14
The loss for epoch 0
1.1127375389582344
The running loss is:
31.160696268081665
The number of items in train is:
14
The loss for epoch 1
2.2257640191486905
The running loss is:
20.564725056290627
The number of items in train is:
14
The loss for epoch 2
1.4689089325921876
The running loss is:
14.949720822274685
The number of items in train is:
14
The loss for epoch 3
1.067837201591049
The running loss is:
14.392907034605742
The number of items in train is:
14
The loss for epoch 4
1.0280647881861245
The running loss is:
13.032162211835384
The number of items in train is:
14
The loss for epoch 5
0.9308687294168132
The running loss is:
11.537305176258087
The number of items in train is:
14
The loss for epoch 6
0.8240932268755776
The running loss is:
12.44920339807868
The number of items in train is:
14
The loss for epoch 7
0.8892288141484771
The running loss is:
11.219495192170143
The number of items in train is:
14
The loss for epoch 8
0.8013925137264388
The running loss is:
12.205912753939629
The number of items in train is:
14
The loss for epoch 9
0.8718509109956878
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.222100
47 30819 Eagle County, Colorado, United States ... 47 8.353811
48 30820 Eagle County, Colorado, United States ... 48 9.090399
49 30821 Eagle County, Colorado, United States ... 49 8.430327
50 30822 Eagle County, Colorado, United States ... 50 7.221142
51 30823 Eagle County, Colorado, United States ... 51 5.685931
52 30824 Eagle County, Colorado, United States ... 52 3.982207
53 30825 Eagle County, Colorado, United States ... 53 4.731750
54 30826 Eagle County, Colorado, United States ... 54 9.085600
55 30827 Eagle County, Colorado, United States ... 55 9.379979
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: d240mu9g wandb: Agent Starting Run: ekya2hyl with config: batch_size: 3 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ekya2hyl
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.734347730875015
The number of items in train is:
13
The loss for epoch 0
1.1334113639134626
The running loss is:
24.244850277900696
The number of items in train is:
13
The loss for epoch 1
1.8649884829154382
The running loss is:
16.024796843528748
The number of items in train is:
13
The loss for epoch 2
1.2326766802714422
The running loss is:
14.830536425113678
The number of items in train is:
13
The loss for epoch 3
1.1408104942395136
The running loss is:
12.796163737773895
The number of items in train is:
13
The loss for epoch 4
0.9843202875210688
The running loss is:
12.205731242895126
The number of items in train is:
13
The loss for epoch 5
0.9389024032996252
The running loss is:
11.800627201795578
The number of items in train is:
13
The loss for epoch 6
0.9077405539842752
The running loss is:
11.113345444202423
The number of items in train is:
13
The loss for epoch 7
0.8548727264771094
The running loss is:
11.361089408397675
The number of items in train is:
13
The loss for epoch 8
0.8739299544921288
The running loss is:
10.799745172262192
The number of items in train is:
13
The loss for epoch 9
0.8307496286355532
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... -0.377296
47 30819 ... 11.099423
48 30820 ... 11.109451
49 30821 ... 10.542838
50 30822 ... 7.268153
51 30823 ... 4.264411
52 30824 ... -0.463730
53 30825 ... -0.160548
54 30826 ... 10.614574
55 30827 ... 10.970974
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ekya2hyl wandb: Agent Starting Run: xuiv1iir with config: batch_size: 3 forecast_history: 2 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: xuiv1iir
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.830458275973797
The number of items in train is:
13
The loss for epoch 0
1.2177275596902921
The running loss is:
24.721736907958984
The number of items in train is:
13
The loss for epoch 1
1.9016720698429987
The running loss is:
15.899764001369476
The number of items in train is:
13
The loss for epoch 2
1.2230587693361135
The running loss is:
14.821087464690208
The number of items in train is:
13
The loss for epoch 3
1.140083651130016
The running loss is:
13.545907482504845
The number of items in train is:
13
The loss for epoch 4
1.0419928832696035
The running loss is:
13.130958944559097
The number of items in train is:
13
The loss for epoch 5
1.0100737649660845
The running loss is:
12.650900229811668
The number of items in train is:
13
The loss for epoch 6
0.9731461715239745
The running loss is:
12.674515426158905
The number of items in train is:
13
The loss for epoch 7
0.9749627250891465
The running loss is:
12.911895290017128
The number of items in train is:
13
The loss for epoch 8
0.9932227146167022
The running loss is:
13.055136889219284
The number of items in train is:
13
The loss for epoch 9
1.0042412991707141
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.861941
47 30819 ... 10.400677
48 30820 ... 11.311898
49 30821 ... 11.339298
50 30822 ... 10.857693
51 30823 ... 10.027314
52 30824 ... 8.962327
53 30825 ... 11.340019
54 30826 ... 12.713752
55 30827 ... 12.687253
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xuiv1iir wandb: Agent Starting Run: yae7j9w0 with config: batch_size: 3 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: yae7j9w0
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.342230960726738
The number of items in train is:
14
The loss for epoch 0
1.2387307829090528
The running loss is:
20.26045072078705
The number of items in train is:
14
The loss for epoch 1
1.4471750514847892
The running loss is:
22.982472449541092
The number of items in train is:
14
The loss for epoch 2
1.641605174967221
The running loss is:
20.817503929138184
The number of items in train is:
14
The loss for epoch 3
1.486964566367013
The running loss is:
14.470415085554123
The number of items in train is:
14
The loss for epoch 4
1.0336010775395803
The running loss is:
14.11274079978466
The number of items in train is:
14
The loss for epoch 5
1.008052914270333
The running loss is:
11.834928281605244
The number of items in train is:
14
The loss for epoch 6
0.8453520201146603
The running loss is:
13.143593035638332
The number of items in train is:
14
The loss for epoch 7
0.9388280739741666
The running loss is:
11.413032311946154
The number of items in train is:
14
The loss for epoch 8
0.8152165937104395
The running loss is:
13.267729237675667
The number of items in train is:
14
The loss for epoch 9
0.947694945548262
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.227926
47 30819 ... 9.815310
48 30820 ... 10.582678
49 30821 ... 10.106319
50 30822 ... 9.210567
51 30823 ... 8.057738
52 30824 ... 6.792384
53 30825 ... 6.137255
54 30826 ... 10.829433
55 30827 ... 10.909749
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yae7j9w0 wandb: Agent Starting Run: p0mhmney with config: batch_size: 3 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: p0mhmney
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.95596632361412
The number of items in train is:
13
The loss for epoch 0
1.227382024893394
The running loss is:
19.904814451932907
The number of items in train is:
13
The loss for epoch 1
1.5311395732256083
The running loss is:
17.617246568202972
The number of items in train is:
13
The loss for epoch 2
1.3551728129386902
The running loss is:
14.285056918859482
The number of items in train is:
13
The loss for epoch 3
1.0988505322199602
The running loss is:
13.227111101150513
The number of items in train is:
13
The loss for epoch 4
1.0174700847038856
The running loss is:
12.499546140432358
The number of items in train is:
13
The loss for epoch 5
0.9615035492640275
The running loss is:
13.50512745976448
The number of items in train is:
13
The loss for epoch 6
1.0388559584434216
The running loss is:
12.428839951753616
The number of items in train is:
13
The loss for epoch 7
0.9560646116733551
The running loss is:
11.402258604764938
The number of items in train is:
13
The loss for epoch 8
0.8770968157511491
The running loss is:
12.398717015981674
The number of items in train is:
13
The loss for epoch 9
0.9537474627678211
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.122801
47 30819 ... 10.667910
48 30820 ... 10.910122
49 30821 ... 9.676403
50 30822 ... 8.409630
51 30823 ... 6.942024
52 30824 ... 5.444630
53 30825 ... 4.966450
54 30826 ... 10.898521
55 30827 ... 10.963875
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: p0mhmney wandb: Agent Starting Run: qfsxslfo with config: batch_size: 3 forecast_history: 2 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: qfsxslfo
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.105710506439209
The number of items in train is:
13
The loss for epoch 0
1.1619777312645545
The running loss is:
21.77917169034481
The number of items in train is:
13
The loss for epoch 1
1.6753208992572932
The running loss is:
18.279946982860565
The number of items in train is:
13
The loss for epoch 2
1.4061497679123511
The running loss is:
16.003442779183388
The number of items in train is:
13
The loss for epoch 3
1.2310340599371836
The running loss is:
13.852836847305298
The number of items in train is:
13
The loss for epoch 4
1.0656028344080999
The running loss is:
13.569828808307648
The number of items in train is:
13
The loss for epoch 5
1.0438329852544344
The running loss is:
13.323665149509907
The number of items in train is:
13
The loss for epoch 6
1.0248973191930697
The running loss is:
12.957750007510185
The number of items in train is:
13
The loss for epoch 7
0.9967500005777066
The running loss is:
13.089145131409168
The number of items in train is:
13
The loss for epoch 8
1.0068573178007052
The running loss is:
12.660584628582
The number of items in train is:
13
The loss for epoch 9
0.9738911252755386
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.720401
47 30819 ... 14.553340
48 30820 ... 12.440676
49 30821 ... 12.086861
50 30822 ... 10.753763
51 30823 ... 10.002252
52 30824 ... 8.860445
53 30825 ... 11.386908
54 30826 ... 13.338316
55 30827 ... 12.476912
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: qfsxslfo wandb: Agent Starting Run: ma3rhz4r with config: batch_size: 3 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ma3rhz4r
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
49.51860047876835
The number of items in train is:
14
The loss for epoch 0
3.5370428913405965
The running loss is:
28.901946112513542
The number of items in train is:
14
The loss for epoch 1
2.064424722322396
The running loss is:
41.28298529610038
The number of items in train is:
14
The loss for epoch 2
2.94878466400717
The running loss is:
22.289564080536366
The number of items in train is:
14
The loss for epoch 3
1.592111720038312
The running loss is:
36.36759194731712
The number of items in train is:
14
The loss for epoch 4
2.59768513909408
The running loss is:
18.98034718632698
The number of items in train is:
14
The loss for epoch 5
1.3557390847376414
The running loss is:
12.218269184231758
The number of items in train is:
14
The loss for epoch 6
0.8727335131594113
The running loss is:
13.551307149231434
The number of items in train is:
14
The loss for epoch 7
0.9679505106593881
The running loss is:
11.265797924250364
The number of items in train is:
14
The loss for epoch 8
0.8046998517321688
The running loss is:
13.734506249427795
The number of items in train is:
14
The loss for epoch 9
0.9810361606734139
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.114567
47 30819 ... 10.723621
48 30820 ... 11.053820
49 30821 ... 10.402370
50 30822 ... 9.422271
51 30823 ... 8.319467
52 30824 ... 7.169548
53 30825 ... 7.787798
54 30826 ... 11.268772
55 30827 ... 11.166240
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ma3rhz4r wandb: Agent Starting Run: lu4h4r69 with config: batch_size: 3 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: lu4h4r69
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
33.13056826591492
The number of items in train is:
13
The loss for epoch 0
2.5485052512242246
The running loss is:
24.387350022792816
The number of items in train is:
13
The loss for epoch 1
1.8759500017532935
The running loss is:
17.332179129123688
The number of items in train is:
13
The loss for epoch 2
1.3332445483941298
The running loss is:
15.971165239810944
The number of items in train is:
13
The loss for epoch 3
1.2285511722931495
The running loss is:
15.627148747444153
The number of items in train is:
13
The loss for epoch 4
1.2020883651880117
The running loss is:
15.911345362663269
The number of items in train is:
13
The loss for epoch 5
1.22394964328179
The running loss is:
16.257684774696827
The number of items in train is:
13
The loss for epoch 6
1.2505911365151405
The running loss is:
18.721322864294052
The number of items in train is:
13
The loss for epoch 7
1.44010175879185
The running loss is:
15.539374977350235
The number of items in train is:
13
The loss for epoch 8
1.1953365367192488
The running loss is:
13.293075650930405
The number of items in train is:
13
The loss for epoch 9
1.0225442808408003
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.132831
47 30819 ... 11.071928
48 30820 ... 11.549405
49 30821 ... 11.268209
50 30822 ... 10.758427
51 30823 ... 10.136646
52 30824 ... 9.477319
53 30825 ... 9.136482
54 30826 ... 11.781645
55 30827 ... 11.742226
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: lu4h4r69 wandb: Agent Starting Run: 8s2c6etq with config: batch_size: 3 forecast_history: 2 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8s2c6etq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 2
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 2
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 2
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 2
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
37.826194524765015
The number of items in train is:
13
The loss for epoch 0
2.9097072711357703
The running loss is:
25.056023612618446
The number of items in train is:
13
The loss for epoch 1
1.9273864317398806
The running loss is:
19.604462698101997
The number of items in train is:
13
The loss for epoch 2
1.5080355921616921
The running loss is:
23.130129784345627
The number of items in train is:
13
The loss for epoch 3
1.7792407526419713
The running loss is:
19.19932833313942
The number of items in train is:
13
The loss for epoch 4
1.4768714102414937
The running loss is:
21.637010172009468
The number of items in train is:
13
The loss for epoch 5
1.664385397846882
The running loss is:
14.966464698314667
The number of items in train is:
13
The loss for epoch 6
1.1512665152549744
The running loss is:
14.04200291633606
The number of items in train is:
13
The loss for epoch 7
1.080154070487389
The running loss is:
13.40083523094654
The number of items in train is:
13
The loss for epoch 8
1.03083347930358
The running loss is:
13.39405021071434
The number of items in train is:
13
The loss for epoch 9
1.0303115546703339
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 2, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.445221
47 30819 ... 10.774174
48 30820 ... 10.911117
49 30821 ... 10.884237
50 30822 ... 10.770847
51 30823 ... 10.652215
52 30824 ... 10.530463
53 30825 ... 8.822457
54 30826 ... 11.169335
55 30827 ... 10.922230
[12 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8s2c6etq wandb: Agent Starting Run: kz9apop8 with config: batch_size: 3 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: kz9apop8
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.368877775967121
The number of items in train is:
13
The loss for epoch 0
0.9514521366128554
The running loss is:
34.86844050884247
The number of items in train is:
13
The loss for epoch 1
2.6821877314494205
The running loss is:
15.270158976316452
The number of items in train is:
13
The loss for epoch 2
1.174627613562804
The running loss is:
13.466378290206194
The number of items in train is:
13
The loss for epoch 3
1.0358752530927842
The running loss is:
12.005736976861954
The number of items in train is:
13
The loss for epoch 4
0.9235182289893811
The running loss is:
11.864228069782257
The number of items in train is:
13
The loss for epoch 5
0.912632928444789
The running loss is:
11.420268423855305
The number of items in train is:
13
The loss for epoch 6
0.8784821864504081
The running loss is:
10.192750919610262
The number of items in train is:
13
The loss for epoch 7
0.7840577630469432
The running loss is:
10.271923331543803
The number of items in train is:
13
The loss for epoch 8
0.7901479485802926
The running loss is:
11.089218605309725
The number of items in train is:
13
The loss for epoch 9
0.8530168157930558
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 -0.889949
47 30819 Eagle County, Colorado, United States ... 47 0.066653
48 30820 Eagle County, Colorado, United States ... 48 7.502620
49 30821 Eagle County, Colorado, United States ... 49 5.934364
50 30822 Eagle County, Colorado, United States ... 50 4.769490
51 30823 Eagle County, Colorado, United States ... 51 3.567657
52 30824 Eagle County, Colorado, United States ... 52 0.390301
53 30825 Eagle County, Colorado, United States ... 53 -0.119038
54 30826 Eagle County, Colorado, United States ... 54 0.273140
55 30827 Eagle County, Colorado, United States ... 55 7.478982
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: kz9apop8 wandb: Agent Starting Run: yd8h1fzr with config: batch_size: 3 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: yd8h1fzr
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.579489664174616
The number of items in train is:
13
The loss for epoch 0
1.2753453587826629
The running loss is:
19.769059717655182
The number of items in train is:
13
The loss for epoch 1
1.5206969013580909
The running loss is:
13.712854489684105
The number of items in train is:
13
The loss for epoch 2
1.0548349607449312
The running loss is:
13.466788783669472
The number of items in train is:
13
The loss for epoch 3
1.0359068295130363
The running loss is:
12.41582890599966
The number of items in train is:
13
The loss for epoch 4
0.9550637619999739
The running loss is:
11.723669052124023
The number of items in train is:
13
The loss for epoch 5
0.9018206963172326
The running loss is:
12.135962635278702
The number of items in train is:
13
The loss for epoch 6
0.9335355873291309
The running loss is:
10.866565614938736
The number of items in train is:
13
The loss for epoch 7
0.8358896626875951
The running loss is:
10.691195979714394
The number of items in train is:
13
The loss for epoch 8
0.822399690747261
The running loss is:
10.159182950854301
The number of items in train is:
13
The loss for epoch 9
0.781475611604177
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... -0.968152
47 30819 ... -0.342819
48 30820 ... 13.105046
49 30821 ... 8.941922
50 30822 ... 8.937499
51 30823 ... 7.656468
52 30824 ... 1.802312
53 30825 ... 2.238525
54 30826 ... 1.972946
55 30827 ... 14.276954
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yd8h1fzr wandb: Agent Starting Run: 3osejg4o with config: batch_size: 3 forecast_history: 3 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 3osejg4o
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.370196998119354
The number of items in train is:
13
The loss for epoch 0
1.1053997690861042
The running loss is:
19.316490292549133
The number of items in train is:
13
The loss for epoch 1
1.4858838686576257
The running loss is:
12.656078651547432
The number of items in train is:
13
The loss for epoch 2
0.9735445116574948
The running loss is:
12.666808053851128
The number of items in train is:
13
The loss for epoch 3
0.9743698502962406
The running loss is:
12.39689488708973
The number of items in train is:
13
The loss for epoch 4
0.9536072990069022
The running loss is:
11.922403216362
The number of items in train is:
13
The loss for epoch 5
0.9171079397201538
The running loss is:
11.341399416327477
The number of items in train is:
13
The loss for epoch 6
0.8724153397174982
The running loss is:
10.815890714526176
The number of items in train is:
13
The loss for epoch 7
0.8319915934250905
The running loss is:
11.103736594319344
The number of items in train is:
13
The loss for epoch 8
0.854133584178411
The running loss is:
10.415005251765251
The number of items in train is:
13
The loss for epoch 9
0.8011542501357886
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 0.309899
47 30819 ... 0.997727
48 30820 ... 9.866085
49 30821 ... 7.090917
50 30822 ... 6.927128
51 30823 ... 9.617968
52 30824 ... 5.897040
53 30825 ... 6.094452
54 30826 ... 7.577441
55 30827 ... 14.233065
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3osejg4o wandb: Agent Starting Run: 59unu0sl with config: batch_size: 3 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 59unu0sl
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.963503643870354
The number of items in train is:
13
The loss for epoch 0
0.9971925879900272
The running loss is:
37.13133166730404
The number of items in train is:
13
The loss for epoch 1
2.856256282100311
The running loss is:
21.90416258573532
The number of items in train is:
13
The loss for epoch 2
1.6849355835181017
The running loss is:
18.790213316679
The number of items in train is:
13
The loss for epoch 3
1.4454010243599231
The running loss is:
16.947905987501144
The number of items in train is:
13
The loss for epoch 4
1.3036850759616265
The running loss is:
13.11191101744771
The number of items in train is:
13
The loss for epoch 5
1.00860853980367
The running loss is:
11.513894490897655
The number of items in train is:
13
The loss for epoch 6
0.885684191607512
The running loss is:
11.091134123504162
The number of items in train is:
13
The loss for epoch 7
0.8531641633464739
The running loss is:
11.206058628857136
The number of items in train is:
13
The loss for epoch 8
0.8620045099120873
The running loss is:
11.77466919273138
The number of items in train is:
13
The loss for epoch 9
0.90574378405626
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.223539
47 30819 Eagle County, Colorado, United States ... 47 1.187161
48 30820 Eagle County, Colorado, United States ... 48 5.947976
49 30821 Eagle County, Colorado, United States ... 49 5.060910
50 30822 Eagle County, Colorado, United States ... 50 3.930160
51 30823 Eagle County, Colorado, United States ... 51 2.693713
52 30824 Eagle County, Colorado, United States ... 52 0.396199
53 30825 Eagle County, Colorado, United States ... 53 0.830643
54 30826 Eagle County, Colorado, United States ... 54 1.344829
55 30827 Eagle County, Colorado, United States ... 55 5.947390
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 59unu0sl wandb: Agent Starting Run: gsblnief with config: batch_size: 3 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: gsblnief
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.455913960933685
The number of items in train is:
13
The loss for epoch 0
1.1119933816102834
The running loss is:
22.357890762388706
The number of items in train is:
13
The loss for epoch 1
1.7198377509529774
The running loss is:
17.738923609256744
The number of items in train is:
13
The loss for epoch 2
1.364532585327442
The running loss is:
13.448972549289465
The number of items in train is:
13
The loss for epoch 3
1.0345363499453435
The running loss is:
14.64394161105156
The number of items in train is:
13
The loss for epoch 4
1.126457047003966
The running loss is:
11.938052050769329
The number of items in train is:
13
The loss for epoch 5
0.9183116962130253
The running loss is:
11.660171031951904
The number of items in train is:
13
The loss for epoch 6
0.8969362332270696
The running loss is:
10.605362512171268
The number of items in train is:
13
The loss for epoch 7
0.8157971163208668
The running loss is:
10.263663992285728
The number of items in train is:
13
The loss for epoch 8
0.7895126147912099
The running loss is:
9.898155242204666
The number of items in train is:
13
The loss for epoch 9
0.7613965570926666
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... -3.512244
47 30819 ... -4.168801
48 30820 ... 16.331560
49 30821 ... 7.215089
50 30822 ... 6.654920
51 30823 ... 7.448952
52 30824 ... -0.154256
53 30825 ... -2.483047
54 30826 ... -3.068379
55 30827 ... 14.678398
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gsblnief wandb: Agent Starting Run: yf2arj2o with config: batch_size: 3 forecast_history: 3 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: yf2arj2o
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.937836900353432
The number of items in train is:
13
The loss for epoch 0
0.9952182231041101
The running loss is:
23.048843041062355
The number of items in train is:
13
The loss for epoch 1
1.7729879262355657
The running loss is:
14.899169534444809
The number of items in train is:
13
The loss for epoch 2
1.1460899641880622
The running loss is:
13.64275423437357
The number of items in train is:
13
The loss for epoch 3
1.0494426334133515
The running loss is:
13.533750593662262
The number of items in train is:
13
The loss for epoch 4
1.0410577379740202
The running loss is:
12.572618752717972
The number of items in train is:
13
The loss for epoch 5
0.967124519439844
The running loss is:
11.828686103224754
The number of items in train is:
13
The loss for epoch 6
0.9098989310172888
The running loss is:
11.33057525753975
The number of items in train is:
13
The loss for epoch 7
0.8715827121184423
The running loss is:
11.64349377155304
The number of items in train is:
13
The loss for epoch 8
0.8956533670425415
The running loss is:
10.891612857580185
The number of items in train is:
13
The loss for epoch 9
0.8378163736600143
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 -0.278797
47 30819 Eagle County, Colorado, United States ... 47 -0.085567
48 30820 Eagle County, Colorado, United States ... 48 7.881258
49 30821 Eagle County, Colorado, United States ... 49 4.568991
50 30822 Eagle County, Colorado, United States ... 50 3.322025
51 30823 Eagle County, Colorado, United States ... 51 4.989382
52 30824 Eagle County, Colorado, United States ... 52 0.591432
53 30825 Eagle County, Colorado, United States ... 53 -0.368374
54 30826 Eagle County, Colorado, United States ... 54 -0.109885
55 30827 Eagle County, Colorado, United States ... 55 7.602907
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: yf2arj2o wandb: Agent Starting Run: f4an0eks with config: batch_size: 3 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: f4an0eks
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
24.400188378989697
The number of items in train is:
13
The loss for epoch 0
1.876937567614592
The running loss is:
31.185614429414272
The number of items in train is:
13
The loss for epoch 1
2.3988934176472516
The running loss is:
32.44879423826933
The number of items in train is:
13
The loss for epoch 2
2.496061095251487
The running loss is:
18.573741644620895
The number of items in train is:
13
The loss for epoch 3
1.4287493572785304
The running loss is:
13.560782168060541
The number of items in train is:
13
The loss for epoch 4
1.0431370898508108
The running loss is:
12.45004703849554
The number of items in train is:
13
The loss for epoch 5
0.9576959260381185
The running loss is:
12.11960457265377
The number of items in train is:
13
The loss for epoch 6
0.9322772748195208
The running loss is:
11.551337949931622
The number of items in train is:
13
The loss for epoch 7
0.8885644576870478
The running loss is:
12.185599125921726
The number of items in train is:
13
The loss for epoch 8
0.9373537789170558
The running loss is:
12.21959825605154
The number of items in train is:
13
The loss for epoch 9
0.9399690966193492
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.386969
47 30819 Eagle County, Colorado, United States ... 47 6.692326
48 30820 Eagle County, Colorado, United States ... 48 7.089355
49 30821 Eagle County, Colorado, United States ... 49 7.698109
50 30822 Eagle County, Colorado, United States ... 50 6.623402
51 30823 Eagle County, Colorado, United States ... 51 5.599646
52 30824 Eagle County, Colorado, United States ... 52 4.635734
53 30825 Eagle County, Colorado, United States ... 53 7.907625
54 30826 Eagle County, Colorado, United States ... 54 7.940404
55 30827 Eagle County, Colorado, United States ... 55 8.319972
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: f4an0eks wandb: Agent Starting Run: kwvkpv1h with config: batch_size: 3 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: kwvkpv1h
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.458874687552452
The number of items in train is:
13
The loss for epoch 0
1.3429903605809579
The running loss is:
18.81114272773266
The number of items in train is:
13
The loss for epoch 1
1.4470109790563583
The running loss is:
18.729552567005157
The number of items in train is:
13
The loss for epoch 2
1.4407348128465505
The running loss is:
14.729724779725075
The number of items in train is:
13
The loss for epoch 3
1.1330557522865443
The running loss is:
13.426510781049728
The number of items in train is:
13
The loss for epoch 4
1.0328085216192098
The running loss is:
12.910267278552055
The number of items in train is:
13
The loss for epoch 5
0.9930974829655427
The running loss is:
11.92785045132041
The number of items in train is:
13
The loss for epoch 6
0.9175269577938777
The running loss is:
12.008645549416542
The number of items in train is:
13
The loss for epoch 7
0.923741965339734
The running loss is:
12.661383390426636
The number of items in train is:
13
The loss for epoch 8
0.9739525684943566
The running loss is:
12.345752455294132
The number of items in train is:
13
The loss for epoch 9
0.9496732657918563
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.849866
47 30819 ... 7.589612
48 30820 ... 14.580077
49 30821 ... 13.545156
50 30822 ... 12.456741
51 30823 ... 10.941383
52 30824 ... 7.304590
53 30825 ... 9.950720
54 30826 ... 9.130615
55 30827 ... 17.259148
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: kwvkpv1h wandb: Agent Starting Run: hktgvt1n with config: batch_size: 3 forecast_history: 3 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: hktgvt1n
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.013039693236351
The number of items in train is:
13
The loss for epoch 0
1.154849207172027
The running loss is:
21.378779768943787
The number of items in train is:
13
The loss for epoch 1
1.6445215206879835
The running loss is:
16.609514646232128
The number of items in train is:
13
The loss for epoch 2
1.2776549727870867
The running loss is:
14.250408738851547
The number of items in train is:
13
The loss for epoch 3
1.0961852876039653
The running loss is:
12.660884097218513
The number of items in train is:
13
The loss for epoch 4
0.973914161324501
The running loss is:
12.710350036621094
The number of items in train is:
13
The loss for epoch 5
0.977719233586238
The running loss is:
12.260607942938805
The number of items in train is:
13
The loss for epoch 6
0.9431236879183695
The running loss is:
11.451108917593956
The number of items in train is:
13
The loss for epoch 7
0.880854532122612
The running loss is:
11.240634605288506
The number of items in train is:
13
The loss for epoch 8
0.8646642004068081
The running loss is:
11.278469979763031
The number of items in train is:
13
The loss for epoch 9
0.8675746138279254
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.299133
47 30819 Eagle County, Colorado, United States ... 47 -1.036485
48 30820 Eagle County, Colorado, United States ... 48 7.932483
49 30821 Eagle County, Colorado, United States ... 49 5.500789
50 30822 Eagle County, Colorado, United States ... 50 3.142856
51 30823 Eagle County, Colorado, United States ... 51 4.422402
52 30824 Eagle County, Colorado, United States ... 52 0.140528
53 30825 Eagle County, Colorado, United States ... 53 0.239170
54 30826 Eagle County, Colorado, United States ... 54 -1.041948
55 30827 Eagle County, Colorado, United States ... 55 7.568707
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hktgvt1n wandb: Agent Starting Run: 5tagpuju with config: batch_size: 3 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5tagpuju
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
115.17622379213572
The number of items in train is:
13
The loss for epoch 0
8.859709522471977
The running loss is:
40.81747505068779
The number of items in train is:
13
The loss for epoch 1
3.13980577312983
The running loss is:
32.038784205913544
The number of items in train is:
13
The loss for epoch 2
2.4645218619933495
The running loss is:
44.92502377741039
The number of items in train is:
13
The loss for epoch 3
3.455771059800799
The running loss is:
36.635310769081116
The number of items in train is:
13
The loss for epoch 4
2.818100828390855
The running loss is:
46.61492267251015
The number of items in train is:
13
The loss for epoch 5
3.5857632825007806
The running loss is:
13.955021470785141
The number of items in train is:
13
The loss for epoch 6
1.0734631900603955
The running loss is:
14.969138577580452
The number of items in train is:
13
The loss for epoch 7
1.1514721982754195
The running loss is:
16.040683686733246
The number of items in train is:
13
The loss for epoch 8
1.2338987451333265
The running loss is:
16.49948103353381
The number of items in train is:
13
The loss for epoch 9
1.26919084873337
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.704542
47 30819 Eagle County, Colorado, United States ... 47 4.672008
48 30820 Eagle County, Colorado, United States ... 48 5.456105
49 30821 Eagle County, Colorado, United States ... 49 5.308846
50 30822 Eagle County, Colorado, United States ... 50 4.914132
51 30823 Eagle County, Colorado, United States ... 51 4.560124
52 30824 Eagle County, Colorado, United States ... 52 4.158611
53 30825 Eagle County, Colorado, United States ... 53 4.864852
54 30826 Eagle County, Colorado, United States ... 54 4.867615
55 30827 Eagle County, Colorado, United States ... 55 5.671974
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5tagpuju wandb: Agent Starting Run: nif4icxc with config: batch_size: 3 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: nif4icxc
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
66.03357294201851
The number of items in train is:
13
The loss for epoch 0
5.0795056109245005
The running loss is:
26.760784819722176
The number of items in train is:
13
The loss for epoch 1
2.0585219092093983
The running loss is:
22.731184750795364
The number of items in train is:
13
The loss for epoch 2
1.748552673138105
The running loss is:
20.40171890705824
The number of items in train is:
13
The loss for epoch 3
1.5693629928506339
The running loss is:
17.968903437256813
The number of items in train is:
13
The loss for epoch 4
1.3822233413274472
The running loss is:
15.660512588918209
The number of items in train is:
13
The loss for epoch 5
1.2046548145321698
The running loss is:
15.091655969619751
The number of items in train is:
13
The loss for epoch 6
1.1608966130476732
The running loss is:
13.655773513019085
The number of items in train is:
13
The loss for epoch 7
1.0504441163860834
The running loss is:
13.347086157649755
The number of items in train is:
13
The loss for epoch 8
1.0266989352038274
The running loss is:
12.99965537339449
The number of items in train is:
13
The loss for epoch 9
0.9999734902611146
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.025051
47 30819 ... 8.513655
48 30820 ... 11.325939
49 30821 ... 10.518827
50 30822 ... 9.861224
51 30823 ... 9.223644
52 30824 ... 8.587379
53 30825 ... 8.185777
54 30826 ... 8.146936
55 30827 ... 10.996994
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nif4icxc wandb: Agent Starting Run: thu9a8mz with config: batch_size: 3 forecast_history: 3 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: thu9a8mz
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 3
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 3
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 3
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 3
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
44.96720665693283
The number of items in train is:
13
The loss for epoch 0
3.459015896687141
The running loss is:
22.17994412779808
The number of items in train is:
13
The loss for epoch 1
1.70614954829216
The running loss is:
14.762777239084244
The number of items in train is:
13
The loss for epoch 2
1.1355982491603265
The running loss is:
14.303692415356636
The number of items in train is:
13
The loss for epoch 3
1.1002840319505105
The running loss is:
13.229048073291779
The number of items in train is:
13
The loss for epoch 4
1.017619082560906
The running loss is:
13.303537771105766
The number of items in train is:
13
The loss for epoch 5
1.023349059315828
The running loss is:
13.995450779795647
The number of items in train is:
13
The loss for epoch 6
1.0765731369073575
The running loss is:
12.943494260311127
The number of items in train is:
13
The loss for epoch 7
0.9956534046393174
The running loss is:
13.159868687391281
The number of items in train is:
13
The loss for epoch 8
1.012297591337791
The running loss is:
13.365740969777107
The number of items in train is:
13
The loss for epoch 9
1.0281339207520852
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 3, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.087015
47 30819 Eagle County, Colorado, United States ... 47 8.132568
48 30820 Eagle County, Colorado, United States ... 48 8.483716
49 30821 Eagle County, Colorado, United States ... 49 8.753112
50 30822 Eagle County, Colorado, United States ... 50 7.402977
51 30823 Eagle County, Colorado, United States ... 51 6.481536
52 30824 Eagle County, Colorado, United States ... 52 5.727474
53 30825 Eagle County, Colorado, United States ... 53 8.094894
54 30826 Eagle County, Colorado, United States ... 54 8.747983
55 30827 Eagle County, Colorado, United States ... 55 9.392281
[13 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: thu9a8mz wandb: Agent Starting Run: ky4qam1f with config: batch_size: 3 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ky4qam1f
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.872004628414288
The number of items in train is:
13
The loss for epoch 0
1.2209234329549452
The running loss is:
17.338138416409492
The number of items in train is:
13
The loss for epoch 1
1.3337029551084225
The running loss is:
12.708929975517094
The number of items in train is:
13
The loss for epoch 2
0.9776099981166996
The running loss is:
12.215490847826004
The number of items in train is:
13
The loss for epoch 3
0.9396531421404618
The running loss is:
12.03363348171115
The number of items in train is:
13
The loss for epoch 4
0.9256641139777807
The running loss is:
11.642251981422305
The number of items in train is:
13
The loss for epoch 5
0.8955578447247927
The running loss is:
10.20832685381174
The number of items in train is:
13
The loss for epoch 6
0.7852559118316724
The running loss is:
10.859044075012207
The number of items in train is:
13
The loss for epoch 7
0.8353110826932467
The running loss is:
10.322055157274008
The number of items in train is:
13
The loss for epoch 8
0.7940042428672314
The running loss is:
11.003573529422283
The number of items in train is:
13
The loss for epoch 9
0.8464287330324833
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 -0.346429
47 30819 Eagle County, Colorado, United States ... 47 0.829351
48 30820 Eagle County, Colorado, United States ... 48 1.952672
49 30821 Eagle County, Colorado, United States ... 49 9.118698
50 30822 Eagle County, Colorado, United States ... 50 5.451615
51 30823 Eagle County, Colorado, United States ... 51 3.901324
52 30824 Eagle County, Colorado, United States ... 52 2.318013
53 30825 Eagle County, Colorado, United States ... 53 2.697446
54 30826 Eagle County, Colorado, United States ... 54 2.428525
55 30827 Eagle County, Colorado, United States ... 55 3.743862
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ky4qam1f wandb: Agent Starting Run: 8ni0jy4b with config: batch_size: 3 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 8ni0jy4b
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.790921412408352
The number of items in train is:
13
The loss for epoch 0
1.291609339416027
The running loss is:
15.056650847196579
The number of items in train is:
13
The loss for epoch 1
1.1582039113228138
The running loss is:
12.714531168341637
The number of items in train is:
13
The loss for epoch 2
0.9780408591032028
The running loss is:
11.838263422250748
The number of items in train is:
13
The loss for epoch 3
0.9106356478654422
The running loss is:
11.716195069253445
The number of items in train is:
13
The loss for epoch 4
0.9012457745579573
The running loss is:
11.06982884556055
The number of items in train is:
13
The loss for epoch 5
0.85152529581235
The running loss is:
11.064709179103374
The number of items in train is:
13
The loss for epoch 6
0.8511314753156441
The running loss is:
10.000222440809011
The number of items in train is:
13
The loss for epoch 7
0.7692478800622317
The running loss is:
9.306559957563877
The number of items in train is:
13
The loss for epoch 8
0.7158892275049136
The running loss is:
9.157860904932022
The number of items in train is:
13
The loss for epoch 9
0.7044508388409247
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 1.791902
47 30819 ... 5.654204
48 30820 ... 8.961608
49 30821 ... 11.700377
50 30822 ... 10.315681
51 30823 ... 10.420052
52 30824 ... 9.844280
53 30825 ... 11.127863
54 30826 ... 15.757866
55 30827 ... 18.537880
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8ni0jy4b wandb: Agent Starting Run: w9sexr89 with config: batch_size: 3 forecast_history: 4 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: w9sexr89
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.78814585506916
The number of items in train is:
12
The loss for epoch 0
1.23234548792243
The running loss is:
18.438936561346054
The number of items in train is:
12
The loss for epoch 1
1.536578046778838
The running loss is:
12.376275420188904
The number of items in train is:
12
The loss for epoch 2
1.031356285015742
The running loss is:
12.264208257198334
The number of items in train is:
12
The loss for epoch 3
1.0220173547665279
The running loss is:
11.700051099061966
The number of items in train is:
12
The loss for epoch 4
0.9750042582551638
The running loss is:
10.987978845834732
The number of items in train is:
12
The loss for epoch 5
0.915664903819561
The running loss is:
10.582637771964073
The number of items in train is:
12
The loss for epoch 6
0.8818864809970061
The running loss is:
10.795451432466507
The number of items in train is:
12
The loss for epoch 7
0.8996209527055422
The running loss is:
10.955302745103836
The number of items in train is:
12
The loss for epoch 8
0.9129418954253197
The running loss is:
10.035184428095818
The number of items in train is:
12
The loss for epoch 9
0.8362653690079848
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.124487
47 30819 ... 8.182631
48 30820 ... 8.625867
49 30821 ... 8.606244
50 30822 ... 11.974076
51 30823 ... 12.952820
52 30824 ... 13.684759
53 30825 ... 16.254524
54 30826 ... 16.794670
55 30827 ... 17.070047
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: w9sexr89 wandb: Agent Starting Run: gkffdz2w with config: batch_size: 3 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: gkffdz2w
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.34749260544777
The number of items in train is:
13
The loss for epoch 0
1.0267302004190593
The running loss is:
25.4431431889534
The number of items in train is:
13
The loss for epoch 1
1.957164860688723
The running loss is:
14.405924782156944
The number of items in train is:
13
The loss for epoch 2
1.1081480601659188
The running loss is:
13.430022314190865
The number of items in train is:
13
The loss for epoch 3
1.0330786395531435
The running loss is:
12.23273740336299
The number of items in train is:
13
The loss for epoch 4
0.9409798002586915
The running loss is:
11.577613770961761
The number of items in train is:
13
The loss for epoch 5
0.8905856746893662
The running loss is:
10.150533594191074
The number of items in train is:
13
The loss for epoch 6
0.7808102764762365
The running loss is:
9.9775076135993
The number of items in train is:
13
The loss for epoch 7
0.7675005856614846
The running loss is:
10.126881934702396
The number of items in train is:
13
The loss for epoch 8
0.7789909180540305
The running loss is:
12.508168563246727
The number of items in train is:
13
The loss for epoch 9
0.9621668125574405
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 3.007489
47 30819 ... 2.314451
48 30820 ... 2.569708
49 30821 ... 12.613434
50 30822 ... 7.784388
51 30823 ... 6.070034
52 30824 ... 5.322172
53 30825 ... 9.416172
54 30826 ... 5.446332
55 30827 ... 7.896643
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gkffdz2w wandb: Agent Starting Run: hv9fm6aa with config: batch_size: 3 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: hv9fm6aa
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.490479558706284
The number of items in train is:
13
The loss for epoch 0
1.0377291968235602
The running loss is:
23.68451225757599
The number of items in train is:
13
The loss for epoch 1
1.8218855582750761
The running loss is:
14.904601812362671
The number of items in train is:
13
The loss for epoch 2
1.1465078317202055
The running loss is:
13.458257734775543
The number of items in train is:
13
The loss for epoch 3
1.0352505949827342
The running loss is:
12.307238146662712
The number of items in train is:
13
The loss for epoch 4
0.9467106266663625
The running loss is:
11.53241079300642
The number of items in train is:
13
The loss for epoch 5
0.8871085225389554
The running loss is:
11.265225373208523
The number of items in train is:
13
The loss for epoch 6
0.8665557979391172
The running loss is:
11.613157991319895
The number of items in train is:
13
The loss for epoch 7
0.8933198454861457
The running loss is:
10.200320366770029
The number of items in train is:
13
The loss for epoch 8
0.7846400282130792
The running loss is:
9.388746418058872
The number of items in train is:
13
The loss for epoch 9
0.7222112629276055
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.511043
47 30819 ... 6.511939
48 30820 ... 7.458131
49 30821 ... 9.090449
50 30822 ... 9.168793
51 30823 ... 10.198345
52 30824 ... 9.923094
53 30825 ... 8.366743
54 30826 ... 13.076762
55 30827 ... 13.979200
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: hv9fm6aa wandb: Agent Starting Run: gh5ouzzl with config: batch_size: 3 forecast_history: 4 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: gh5ouzzl
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.004660785198212
The number of items in train is:
12
The loss for epoch 0
1.083721732099851
The running loss is:
23.263212963938713
The number of items in train is:
12
The loss for epoch 1
1.938601080328226
The running loss is:
15.897933334112167
The number of items in train is:
12
The loss for epoch 2
1.3248277778426807
The running loss is:
13.413813337683678
The number of items in train is:
12
The loss for epoch 3
1.1178177781403065
The running loss is:
12.639265418052673
The number of items in train is:
12
The loss for epoch 4
1.053272118171056
The running loss is:
11.460458725690842
The number of items in train is:
12
The loss for epoch 5
0.9550382271409035
The running loss is:
11.300244197249413
The number of items in train is:
12
The loss for epoch 6
0.941687016437451
The running loss is:
10.694719895720482
The number of items in train is:
12
The loss for epoch 7
0.8912266579767069
The running loss is:
9.931787982583046
The number of items in train is:
12
The loss for epoch 8
0.8276489985485872
The running loss is:
9.597246825695038
The number of items in train is:
12
The loss for epoch 9
0.7997705688079199
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 1.344791
47 30819 ... 6.949912
48 30820 ... 7.202622
49 30821 ... 7.324420
50 30822 ... 8.290039
51 30823 ... 11.569249
52 30824 ... 12.225736
53 30825 ... 7.409237
54 30826 ... 13.821341
55 30827 ... 13.868330
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gh5ouzzl wandb: Agent Starting Run: 7mnzgjkp with config: batch_size: 3 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 7mnzgjkp
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.340472156181931
The number of items in train is:
13
The loss for epoch 0
1.1031132427832255
The running loss is:
23.359602227807045
The number of items in train is:
13
The loss for epoch 1
1.7968924790620804
The running loss is:
17.2289652582258
The number of items in train is:
13
The loss for epoch 2
1.325305019863523
The running loss is:
12.503187745809555
The number of items in train is:
13
The loss for epoch 3
0.9617836727545812
The running loss is:
12.070784609764814
The number of items in train is:
13
The loss for epoch 4
0.9285218930588319
The running loss is:
11.330001890659332
The number of items in train is:
13
The loss for epoch 5
0.8715386069737948
The running loss is:
11.012930020689964
The number of items in train is:
13
The loss for epoch 6
0.8471484631299973
The running loss is:
13.838854122906923
The number of items in train is:
13
The loss for epoch 7
1.0645272402236094
The running loss is:
10.799162855371833
The number of items in train is:
13
The loss for epoch 8
0.8307048350286025
The running loss is:
9.654880156274885
The number of items in train is:
13
The loss for epoch 9
0.742683088944222
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.577109
47 30819 Eagle County, Colorado, United States ... 47 1.884349
48 30820 Eagle County, Colorado, United States ... 48 2.142425
49 30821 Eagle County, Colorado, United States ... 49 7.987684
50 30822 Eagle County, Colorado, United States ... 50 5.628455
51 30823 Eagle County, Colorado, United States ... 51 5.215091
52 30824 Eagle County, Colorado, United States ... 52 4.537104
53 30825 Eagle County, Colorado, United States ... 53 5.395092
54 30826 Eagle County, Colorado, United States ... 54 5.019588
55 30827 Eagle County, Colorado, United States ... 55 5.951438
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 7mnzgjkp wandb: Agent Starting Run: y662r8p1 with config: batch_size: 3 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: y662r8p1
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.1878132969141
The number of items in train is:
13
The loss for epoch 0
1.0144471766857
The running loss is:
23.06560629606247
The number of items in train is:
13
The loss for epoch 1
1.7742774073894207
The running loss is:
16.96458823233843
The number of items in train is:
13
The loss for epoch 2
1.3049683255644946
The running loss is:
12.846139311790466
The number of items in train is:
13
The loss for epoch 3
0.9881645624454205
The running loss is:
12.694834038615227
The number of items in train is:
13
The loss for epoch 4
0.9765256952780944
The running loss is:
12.656872421503067
The number of items in train is:
13
The loss for epoch 5
0.9736055708848513
The running loss is:
13.498041197657585
The number of items in train is:
13
The loss for epoch 6
1.0383108613582759
The running loss is:
13.583044543862343
The number of items in train is:
13
The loss for epoch 7
1.0448495802971034
The running loss is:
13.378036141395569
The number of items in train is:
13
The loss for epoch 8
1.0290797031842744
The running loss is:
12.795019581913948
The number of items in train is:
13
The loss for epoch 9
0.9842322755318421
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.474936
47 30819 ... 10.948586
48 30820 ... 11.335421
49 30821 ... 10.313191
50 30822 ... 11.425502
51 30823 ... 11.269561
52 30824 ... 11.183122
53 30825 ... 11.199656
54 30826 ... 11.811131
55 30827 ... 12.008145
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: y662r8p1 wandb: Agent Starting Run: c4r1ypl4 with config: batch_size: 3 forecast_history: 4 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: c4r1ypl4
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.688956126570702
The number of items in train is:
12
The loss for epoch 0
1.1407463438808918
The running loss is:
21.444616466760635
The number of items in train is:
12
The loss for epoch 1
1.787051372230053
The running loss is:
19.336486667394638
The number of items in train is:
12
The loss for epoch 2
1.6113738889495532
The running loss is:
14.048754200339317
The number of items in train is:
12
The loss for epoch 3
1.1707295166949432
The running loss is:
12.343533247709274
The number of items in train is:
12
The loss for epoch 4
1.0286277706424396
The running loss is:
11.741394221782684
The number of items in train is:
12
The loss for epoch 5
0.9784495184818903
The running loss is:
11.405920177698135
The number of items in train is:
12
The loss for epoch 6
0.9504933481415113
The running loss is:
10.7405776232481
The number of items in train is:
12
The loss for epoch 7
0.8950481352706751
The running loss is:
10.536985754966736
The number of items in train is:
12
The loss for epoch 8
0.878082146247228
The running loss is:
12.78399670124054
The number of items in train is:
12
The loss for epoch 9
1.0653330584367116
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.240464
47 30819 ... 6.391535
48 30820 ... 7.531720
49 30821 ... 8.155801
50 30822 ... 9.021329
51 30823 ... 9.722328
52 30824 ... 10.298412
53 30825 ... 7.822366
54 30826 ... 9.580545
55 30827 ... 11.042983
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c4r1ypl4 wandb: Agent Starting Run: 5al65xub with config: batch_size: 3 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 5al65xub
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
50.24515789747238
The number of items in train is:
13
The loss for epoch 0
3.865012145959414
The running loss is:
23.777228504419327
The number of items in train is:
13
The loss for epoch 1
1.829017577263025
The running loss is:
15.574093259871006
The number of items in train is:
13
The loss for epoch 2
1.1980071738362312
The running loss is:
12.103242687880993
The number of items in train is:
13
The loss for epoch 3
0.931018668298538
The running loss is:
15.460729956626892
The number of items in train is:
13
The loss for epoch 4
1.1892869197405302
The running loss is:
13.119429018348455
The number of items in train is:
13
The loss for epoch 5
1.0091868475652659
The running loss is:
13.760254144668579
The number of items in train is:
13
The loss for epoch 6
1.0584810880514293
The running loss is:
14.075625222176313
The number of items in train is:
13
The loss for epoch 7
1.0827404017058702
The running loss is:
14.208767905831337
The number of items in train is:
13
The loss for epoch 8
1.0929821466024106
The running loss is:
13.554820150136948
The number of items in train is:
13
The loss for epoch 9
1.0426784730874574
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.039810
47 30819 Eagle County, Colorado, United States ... 47 8.730705
48 30820 Eagle County, Colorado, United States ... 48 8.790469
49 30821 Eagle County, Colorado, United States ... 49 9.177441
50 30822 Eagle County, Colorado, United States ... 50 9.388792
51 30823 Eagle County, Colorado, United States ... 51 9.147300
52 30824 Eagle County, Colorado, United States ... 52 8.993916
53 30825 Eagle County, Colorado, United States ... 53 6.918562
54 30826 Eagle County, Colorado, United States ... 54 8.720302
55 30827 Eagle County, Colorado, United States ... 55 8.799322
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5al65xub wandb: Agent Starting Run: 5s37jqge with config: batch_size: 3 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 5s37jqge
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
39.261084854602814
The number of items in train is:
13
The loss for epoch 0
3.0200834503540626
The running loss is:
22.115912914276123
The number of items in train is:
13
The loss for epoch 1
1.7012240703289325
The running loss is:
14.952192202210426
The number of items in train is:
13
The loss for epoch 2
1.1501686309392636
The running loss is:
13.682401984930038
The number of items in train is:
13
The loss for epoch 3
1.0524924603792338
The running loss is:
14.396343678236008
The number of items in train is:
13
The loss for epoch 4
1.1074110521720006
The running loss is:
13.456236526370049
The number of items in train is:
13
The loss for epoch 5
1.0350951174130807
The running loss is:
13.37515278160572
The number of items in train is:
13
The loss for epoch 6
1.028857906277363
The running loss is:
12.367682307958603
The number of items in train is:
13
The loss for epoch 7
0.9513601775352771
The running loss is:
12.126630112528801
The number of items in train is:
13
The loss for epoch 8
0.9328177009637539
The running loss is:
16.020440727472305
The number of items in train is:
13
The loss for epoch 9
1.2323415944209466
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.693578
47 30819 ... 11.420332
48 30820 ... 11.478680
49 30821 ... 11.421338
50 30822 ... 12.134402
51 30823 ... 12.323503
52 30824 ... 12.366034
53 30825 ... 11.342683
54 30826 ... 11.622007
55 30827 ... 12.030426
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5s37jqge wandb: Agent Starting Run: jw74vpwp with config: batch_size: 3 forecast_history: 4 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: jw74vpwp
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 4
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 4
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 4
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 4
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
41.467525988817215
The number of items in train is:
12
The loss for epoch 0
3.455627165734768
The running loss is:
20.88641083240509
The number of items in train is:
12
The loss for epoch 1
1.7405342360337575
The running loss is:
12.568571835756302
The number of items in train is:
12
The loss for epoch 2
1.0473809863130252
The running loss is:
12.954892814159393
The number of items in train is:
12
The loss for epoch 3
1.0795744011799495
The running loss is:
13.821066796779633
The number of items in train is:
12
The loss for epoch 4
1.1517555663983028
The running loss is:
12.612691268324852
The number of items in train is:
12
The loss for epoch 5
1.0510576056937377
The running loss is:
12.604485049843788
The number of items in train is:
12
The loss for epoch 6
1.050373754153649
The running loss is:
11.31302846968174
The number of items in train is:
12
The loss for epoch 7
0.9427523724734783
The running loss is:
11.463112786412239
The number of items in train is:
12
The loss for epoch 8
0.9552593988676866
The running loss is:
12.560555011034012
The number of items in train is:
12
The loss for epoch 9
1.0467129175861676
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 4, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 9.026195
47 30819 ... 10.410426
48 30820 ... 11.938659
49 30821 ... 10.415281
50 30822 ... 10.345819
51 30823 ... 10.234818
52 30824 ... 10.661693
53 30825 ... 10.597783
54 30826 ... 11.888622
55 30827 ... 11.954378
[14 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: jw74vpwp wandb: Agent Starting Run: sa751o4d with config: batch_size: 3 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: sa751o4d
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.105641320347786
The number of items in train is:
13
The loss for epoch 0
1.3927416400267527
The running loss is:
14.012058325111866
The number of items in train is:
13
The loss for epoch 1
1.0778506403932204
The running loss is:
12.297234199941158
The number of items in train is:
13
The loss for epoch 2
0.945941092303166
The running loss is:
11.648973919451237
The number of items in train is:
13
The loss for epoch 3
0.8960749168808644
The running loss is:
10.411581374704838
The number of items in train is:
13
The loss for epoch 4
0.8008908749772952
The running loss is:
9.843764215707779
The number of items in train is:
13
The loss for epoch 5
0.7572126319775214
The running loss is:
8.586901139467955
The number of items in train is:
13
The loss for epoch 6
0.6605308568821504
The running loss is:
8.218328204005957
The number of items in train is:
13
The loss for epoch 7
0.6321790926158428
The running loss is:
8.143619112670422
The number of items in train is:
13
The loss for epoch 8
0.6264322394361863
The running loss is:
8.618214875459671
The number of items in train is:
13
The loss for epoch 9
0.6629396058045901
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 4.038171
47 30819 ... 7.117307
48 30820 ... 6.792751
49 30821 ... 6.664652
50 30822 ... 7.004401
51 30823 ... 7.854282
52 30824 ... 8.201924
53 30825 ... 11.353144
54 30826 ... 15.248468
55 30827 ... 14.364745
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sa751o4d wandb: Agent Starting Run: 4c7m3af5 with config: batch_size: 3 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4c7m3af5
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.804713547229767
The number of items in train is:
12
The loss for epoch 0
1.233726128935814
The running loss is:
16.97213351726532
The number of items in train is:
12
The loss for epoch 1
1.41434445977211
The running loss is:
11.822531819343567
The number of items in train is:
12
The loss for epoch 2
0.9852109849452972
The running loss is:
11.416342198848724
The number of items in train is:
12
The loss for epoch 3
0.9513618499040604
The running loss is:
10.902691811323166
The number of items in train is:
12
The loss for epoch 4
0.9085576509435972
The running loss is:
9.671414703130722
The number of items in train is:
12
The loss for epoch 5
0.8059512252608935
The running loss is:
9.385768637061119
The number of items in train is:
12
The loss for epoch 6
0.78214738642176
The running loss is:
8.309829585254192
The number of items in train is:
12
The loss for epoch 7
0.6924857987711827
The running loss is:
8.777955651283264
The number of items in train is:
12
The loss for epoch 8
0.7314963042736053
The running loss is:
9.56509893387556
The number of items in train is:
12
The loss for epoch 9
0.7970915778229634
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.180499
47 30819 ... 7.501813
48 30820 ... 7.126774
49 30821 ... 7.140279
50 30822 ... 7.065376
51 30823 ... 9.210360
52 30824 ... 9.250754
53 30825 ... 13.100918
54 30826 ... 14.399408
55 30827 ... 13.769780
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4c7m3af5 wandb: Agent Starting Run: mx7gqnu2 with config: batch_size: 3 forecast_history: 5 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: mx7gqnu2
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.415991149842739
The number of items in train is:
12
The loss for epoch 0
1.2846659291535616
The running loss is:
15.498348452150822
The number of items in train is:
12
The loss for epoch 1
1.2915290376792352
The running loss is:
12.637772336602211
The number of items in train is:
12
The loss for epoch 2
1.053147694716851
The running loss is:
12.26582846045494
The number of items in train is:
12
The loss for epoch 3
1.0221523717045784
The running loss is:
11.29976324737072
The number of items in train is:
12
The loss for epoch 4
0.9416469372808933
The running loss is:
11.394211154431105
The number of items in train is:
12
The loss for epoch 5
0.949517596202592
The running loss is:
10.832007095217705
The number of items in train is:
12
The loss for epoch 6
0.9026672579348087
The running loss is:
10.655730500817299
The number of items in train is:
12
The loss for epoch 7
0.8879775417347749
The running loss is:
10.479210518300533
The number of items in train is:
12
The loss for epoch 8
0.8732675431917111
The running loss is:
10.922551706433296
The number of items in train is:
12
The loss for epoch 9
0.9102126422027746
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.188203
47 30819 ... 6.379559
48 30820 ... 5.693151
49 30821 ... 5.827620
50 30822 ... 6.130767
51 30823 ... 8.003571
52 30824 ... 9.042922
53 30825 ... 10.781850
54 30826 ... 12.356435
55 30827 ... 11.059150
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: mx7gqnu2 wandb: Agent Starting Run: nb7otgv0 with config: batch_size: 3 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: nb7otgv0
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.261770632117987
The number of items in train is:
13
The loss for epoch 0
1.1739823563167682
The running loss is:
22.147419825196266
The number of items in train is:
13
The loss for epoch 1
1.7036476788612513
The running loss is:
14.186409682035446
The number of items in train is:
13
The loss for epoch 2
1.091262283233496
The running loss is:
11.937791492789984
The number of items in train is:
13
The loss for epoch 3
0.9182916532915372
The running loss is:
10.14401987195015
The number of items in train is:
13
The loss for epoch 4
0.7803092209192423
The running loss is:
8.372021302580833
The number of items in train is:
13
The loss for epoch 5
0.6440016386600641
The running loss is:
7.423566944897175
The number of items in train is:
13
The loss for epoch 6
0.5710436111459365
The running loss is:
9.638437408953905
The number of items in train is:
13
The loss for epoch 7
0.7414182622272235
The running loss is:
11.166652858257294
The number of items in train is:
13
The loss for epoch 8
0.8589732967890226
The running loss is:
9.7910625487566
The number of items in train is:
13
The loss for epoch 9
0.7531586575966615
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.026867
47 30819 Eagle County, Colorado, United States ... 47 4.579353
48 30820 Eagle County, Colorado, United States ... 48 4.504891
49 30821 Eagle County, Colorado, United States ... 49 4.475537
50 30822 Eagle County, Colorado, United States ... 50 4.397957
51 30823 Eagle County, Colorado, United States ... 51 5.628908
52 30824 Eagle County, Colorado, United States ... 52 5.737713
53 30825 Eagle County, Colorado, United States ... 53 6.915092
54 30826 Eagle County, Colorado, United States ... 54 7.359157
55 30827 Eagle County, Colorado, United States ... 55 7.099442
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: nb7otgv0 wandb: Agent Starting Run: 4l7cv9be with config: batch_size: 3 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4l7cv9be
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.323792949318886
The number of items in train is:
12
The loss for epoch 0
1.026982745776574
The running loss is:
23.155533269047737
The number of items in train is:
12
The loss for epoch 1
1.9296277724206448
The running loss is:
14.94628620147705
The number of items in train is:
12
The loss for epoch 2
1.2455238501230876
The running loss is:
13.859730526804924
The number of items in train is:
12
The loss for epoch 3
1.1549775439004104
The running loss is:
11.672522738575935
The number of items in train is:
12
The loss for epoch 4
0.9727102282146612
The running loss is:
10.797379478812218
The number of items in train is:
12
The loss for epoch 5
0.8997816232343515
The running loss is:
10.294382557272911
The number of items in train is:
12
The loss for epoch 6
0.8578652131060759
The running loss is:
8.327066399157047
The number of items in train is:
12
The loss for epoch 7
0.6939221999297539
The running loss is:
8.611333400011063
The number of items in train is:
12
The loss for epoch 8
0.7176111166675886
The running loss is:
9.300903491675854
The number of items in train is:
12
The loss for epoch 9
0.7750752909729878
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.034604
47 30819 Eagle County, Colorado, United States ... 47 5.016776
48 30820 Eagle County, Colorado, United States ... 48 4.942604
49 30821 Eagle County, Colorado, United States ... 49 4.718325
50 30822 Eagle County, Colorado, United States ... 50 4.520617
51 30823 Eagle County, Colorado, United States ... 51 6.344130
52 30824 Eagle County, Colorado, United States ... 52 6.747848
53 30825 Eagle County, Colorado, United States ... 53 8.362752
54 30826 Eagle County, Colorado, United States ... 54 9.566703
55 30827 Eagle County, Colorado, United States ... 55 9.242714
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4l7cv9be wandb: Agent Starting Run: za86wxrm with config: batch_size: 3 forecast_history: 5 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: za86wxrm
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.776227623224258
The number of items in train is:
12
The loss for epoch 0
1.1480189686020215
The running loss is:
21.34618742763996
The number of items in train is:
12
The loss for epoch 1
1.7788489523033302
The running loss is:
14.572952851653099
The number of items in train is:
12
The loss for epoch 2
1.2144127376377583
The running loss is:
13.57256968319416
The number of items in train is:
12
The loss for epoch 3
1.1310474735995133
The running loss is:
12.092315569519997
The number of items in train is:
12
The loss for epoch 4
1.0076929641266663
The running loss is:
12.090366944670677
The number of items in train is:
12
The loss for epoch 5
1.0075305787225564
The running loss is:
11.1148621737957
The number of items in train is:
12
The loss for epoch 6
0.926238514482975
The running loss is:
10.491286784410477
The number of items in train is:
12
The loss for epoch 7
0.874273898700873
The running loss is:
10.797590360045433
The number of items in train is:
12
The loss for epoch 8
0.8997991966704527
The running loss is:
11.091501705348492
The number of items in train is:
12
The loss for epoch 9
0.9242918087790409
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.309795
47 30819 Eagle County, Colorado, United States ... 47 5.539655
48 30820 Eagle County, Colorado, United States ... 48 5.529214
49 30821 Eagle County, Colorado, United States ... 49 5.521837
50 30822 Eagle County, Colorado, United States ... 50 5.204870
51 30823 Eagle County, Colorado, United States ... 51 7.370545
52 30824 Eagle County, Colorado, United States ... 52 8.238771
53 30825 Eagle County, Colorado, United States ... 53 9.005033
54 30826 Eagle County, Colorado, United States ... 54 9.360201
55 30827 Eagle County, Colorado, United States ... 55 9.028099
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: za86wxrm wandb: Agent Starting Run: cbkj9g21 with config: batch_size: 3 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cbkj9g21
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.15755881369114
The number of items in train is:
13
The loss for epoch 0
1.0121199087454722
The running loss is:
23.383041262626648
The number of items in train is:
13
The loss for epoch 1
1.7986954817405114
The running loss is:
20.34821653366089
The number of items in train is:
13
The loss for epoch 2
1.565247425666222
The running loss is:
13.35105698555708
The number of items in train is:
13
The loss for epoch 3
1.0270043835043907
The running loss is:
12.55769258737564
The number of items in train is:
13
The loss for epoch 4
0.9659763528750493
The running loss is:
10.44101019948721
The number of items in train is:
13
The loss for epoch 5
0.8031546307297853
The running loss is:
10.786027267575264
The number of items in train is:
13
The loss for epoch 6
0.8296944051980972
The running loss is:
11.164955213665962
The number of items in train is:
13
The loss for epoch 7
0.8588427087435355
The running loss is:
9.287103720009327
The number of items in train is:
13
The loss for epoch 8
0.7143925938468713
The running loss is:
8.763795241713524
The number of items in train is:
13
The loss for epoch 9
0.6741380955164249
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.958946
47 30819 Eagle County, Colorado, United States ... 47 6.848919
48 30820 Eagle County, Colorado, United States ... 48 6.667441
49 30821 Eagle County, Colorado, United States ... 49 6.700452
50 30822 Eagle County, Colorado, United States ... 50 3.761921
51 30823 Eagle County, Colorado, United States ... 51 7.074552
52 30824 Eagle County, Colorado, United States ... 52 7.613464
53 30825 Eagle County, Colorado, United States ... 53 9.098127
54 30826 Eagle County, Colorado, United States ... 54 9.997087
55 30827 Eagle County, Colorado, United States ... 55 8.320040
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cbkj9g21 wandb: Agent Starting Run: pab0srgj with config: batch_size: 3 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: pab0srgj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.774470299482346
The number of items in train is:
12
The loss for epoch 0
1.0645391916235287
The running loss is:
20.98992669582367
The number of items in train is:
12
The loss for epoch 1
1.7491605579853058
The running loss is:
17.23653557896614
The number of items in train is:
12
The loss for epoch 2
1.436377964913845
The running loss is:
13.365149036049843
The number of items in train is:
12
The loss for epoch 3
1.1137624196708202
The running loss is:
12.378368452191353
The number of items in train is:
12
The loss for epoch 4
1.0315307043492794
The running loss is:
11.96500751376152
The number of items in train is:
12
The loss for epoch 5
0.9970839594801267
The running loss is:
10.989426091313362
The number of items in train is:
12
The loss for epoch 6
0.9157855076094469
The running loss is:
9.780941367149353
The number of items in train is:
12
The loss for epoch 7
0.815078447262446
The running loss is:
16.21955992281437
The number of items in train is:
12
The loss for epoch 8
1.3516299935678642
The running loss is:
11.701737195253372
The number of items in train is:
12
The loss for epoch 9
0.9751447662711143
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.694775
47 30819 ... 11.760224
48 30820 ... 11.690811
49 30821 ... 11.608275
50 30822 ... 11.581036
51 30823 ... 11.688101
52 30824 ... 11.740479
53 30825 ... 11.747087
54 30826 ... 11.845592
55 30827 ... 11.739115
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: pab0srgj wandb: Agent Starting Run: 8h8obozd with config: batch_size: 3 forecast_history: 5 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8h8obozd
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.32255271077156
The number of items in train is:
12
The loss for epoch 0
1.11021272589763
The running loss is:
22.797952115535736
The number of items in train is:
12
The loss for epoch 1
1.8998293429613113
The running loss is:
16.07163879275322
The number of items in train is:
12
The loss for epoch 2
1.339303232729435
The running loss is:
13.264043867588043
The number of items in train is:
12
The loss for epoch 3
1.1053369889656703
The running loss is:
12.219512164592743
The number of items in train is:
12
The loss for epoch 4
1.0182926803827286
The running loss is:
11.778143614530563
The number of items in train is:
12
The loss for epoch 5
0.9815119678775469
The running loss is:
11.204492971301079
The number of items in train is:
12
The loss for epoch 6
0.9337077476084232
The running loss is:
11.166005790233612
The number of items in train is:
12
The loss for epoch 7
0.9305004825194677
The running loss is:
11.464188620448112
The number of items in train is:
12
The loss for epoch 8
0.9553490517040094
The running loss is:
10.929433912038803
The number of items in train is:
12
The loss for epoch 9
0.9107861593365669
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... -0.247660
47 30819 ... 9.233921
48 30820 ... 5.277986
49 30821 ... 6.317695
50 30822 ... 5.119556
51 30823 ... 4.109658
52 30824 ... 4.720734
53 30825 ... 2.022248
54 30826 ... 12.015410
55 30827 ... 8.368930
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8h8obozd wandb: Agent Starting Run: ayz6fdqn with config: batch_size: 3 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ayz6fdqn
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
43.19867384433746
The number of items in train is:
13
The loss for epoch 0
3.322974911102882
The running loss is:
20.882086783647537
The number of items in train is:
13
The loss for epoch 1
1.6063143679728875
The running loss is:
15.9086195230484
The number of items in train is:
13
The loss for epoch 2
1.2237399633114154
The running loss is:
17.856110900640488
The number of items in train is:
13
The loss for epoch 3
1.3735469923569605
The running loss is:
14.558780506253242
The number of items in train is:
13
The loss for epoch 4
1.119906192788711
The running loss is:
15.64150284230709
The number of items in train is:
13
The loss for epoch 5
1.2031925263313146
The running loss is:
15.482542432844639
The number of items in train is:
13
The loss for epoch 6
1.1909648025265107
The running loss is:
14.537198841571808
The number of items in train is:
13
The loss for epoch 7
1.1182460647362928
The running loss is:
13.648285038943868
The number of items in train is:
13
The loss for epoch 8
1.0498680799187592
The running loss is:
11.561186537146568
The number of items in train is:
13
The loss for epoch 9
0.8893220413189667
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.534576
47 30819 ... 12.769893
48 30820 ... 11.421350
49 30821 ... 10.561858
50 30822 ... 9.610747
51 30823 ... 7.076689
52 30824 ... 6.741565
53 30825 ... 5.326016
54 30826 ... 13.664184
55 30827 ... 11.970482
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ayz6fdqn wandb: Agent Starting Run: fhblqpew with config: batch_size: 3 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: fhblqpew
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
44.207919269800186
The number of items in train is:
12
The loss for epoch 0
3.683993272483349
The running loss is:
20.536793023347855
The number of items in train is:
12
The loss for epoch 1
1.7113994186123211
The running loss is:
14.74533599615097
The number of items in train is:
12
The loss for epoch 2
1.2287779996792476
The running loss is:
12.315197795629501
The number of items in train is:
12
The loss for epoch 3
1.026266482969125
The running loss is:
12.204134806990623
The number of items in train is:
12
The loss for epoch 4
1.0170112339158852
The running loss is:
11.466395795345306
The number of items in train is:
12
The loss for epoch 5
0.9555329829454422
The running loss is:
11.339310720562935
The number of items in train is:
12
The loss for epoch 6
0.9449425600469112
The running loss is:
9.619177401065826
The number of items in train is:
12
The loss for epoch 7
0.8015981167554855
The running loss is:
12.089902177453041
The number of items in train is:
12
The loss for epoch 8
1.0074918481210868
The running loss is:
13.646132752299309
The number of items in train is:
12
The loss for epoch 9
1.1371777293582757
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.995404
47 30819 ... 9.003286
48 30820 ... 8.999191
49 30821 ... 9.000885
50 30822 ... 8.894744
51 30823 ... 10.436748
52 30824 ... 10.697165
53 30825 ... 10.588944
54 30826 ... 10.588954
55 30827 ... 10.588938
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fhblqpew wandb: Agent Starting Run: 1t6pbtgz with config: batch_size: 3 forecast_history: 5 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 1t6pbtgz
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 5
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 5
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 5
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 5
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
38.5756913125515
The number of items in train is:
12
The loss for epoch 0
3.214640942712625
The running loss is:
18.708413749933243
The number of items in train is:
12
The loss for epoch 1
1.5590344791611035
The running loss is:
13.634418800473213
The number of items in train is:
12
The loss for epoch 2
1.1362015667061012
The running loss is:
13.00131143629551
The number of items in train is:
12
The loss for epoch 3
1.0834426196912925
The running loss is:
12.16117537021637
The number of items in train is:
12
The loss for epoch 4
1.0134312808513641
The running loss is:
12.743264377117157
The number of items in train is:
12
The loss for epoch 5
1.0619386980930965
The running loss is:
12.74788312613964
The number of items in train is:
12
The loss for epoch 6
1.06232359384497
The running loss is:
12.327722936868668
The number of items in train is:
12
The loss for epoch 7
1.0273102447390556
The running loss is:
11.793324664235115
The number of items in train is:
12
The loss for epoch 8
0.9827770553529263
The running loss is:
12.077590823173523
The number of items in train is:
12
The loss for epoch 9
1.0064659019311268
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 5, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.219585
47 30819 Eagle County, Colorado, United States ... 47 8.171262
48 30820 Eagle County, Colorado, United States ... 48 8.282984
49 30821 Eagle County, Colorado, United States ... 49 8.246166
50 30822 Eagle County, Colorado, United States ... 50 8.154293
51 30823 Eagle County, Colorado, United States ... 51 9.300027
52 30824 Eagle County, Colorado, United States ... 52 9.161006
53 30825 Eagle County, Colorado, United States ... 53 9.634283
54 30826 Eagle County, Colorado, United States ... 54 9.632183
55 30827 Eagle County, Colorado, United States ... 55 9.632958
[15 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1t6pbtgz wandb: Agent Starting Run: stuwxn27 with config: batch_size: 3 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: stuwxn27
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.118256822228432
The number of items in train is:
12
The loss for epoch 0
1.2598547351857026
The running loss is:
18.95265108346939
The number of items in train is:
12
The loss for epoch 1
1.579387590289116
The running loss is:
12.225189611315727
The number of items in train is:
12
The loss for epoch 2
1.0187658009429772
The running loss is:
11.719947949051857
The number of items in train is:
12
The loss for epoch 3
0.9766623290876547
The running loss is:
11.743443045765162
The number of items in train is:
12
The loss for epoch 4
0.9786202538137635
The running loss is:
11.300051920115948
The number of items in train is:
12
The loss for epoch 5
0.9416709933429956
The running loss is:
10.814161136746407
The number of items in train is:
12
The loss for epoch 6
0.9011800947288672
The running loss is:
10.698570221662521
The number of items in train is:
12
The loss for epoch 7
0.8915475184718767
The running loss is:
10.697828751057386
The number of items in train is:
12
The loss for epoch 8
0.8914857292547822
The running loss is:
10.184408448636532
The number of items in train is:
12
The loss for epoch 9
0.8487007040530443
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.240055
47 30819 Eagle County, Colorado, United States ... 47 1.800865
48 30820 Eagle County, Colorado, United States ... 48 1.639500
49 30821 Eagle County, Colorado, United States ... 49 1.430543
50 30822 Eagle County, Colorado, United States ... 50 1.315372
51 30823 Eagle County, Colorado, United States ... 51 1.186460
52 30824 Eagle County, Colorado, United States ... 52 3.861452
53 30825 Eagle County, Colorado, United States ... 53 3.363582
54 30826 Eagle County, Colorado, United States ... 54 3.074578
55 30827 Eagle County, Colorado, United States ... 55 2.776423
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: stuwxn27 wandb: Agent Starting Run: n3y19nh5 with config: batch_size: 3 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: n3y19nh5
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.848535776138306
The number of items in train is:
12
The loss for epoch 0
1.2373779813448589
The running loss is:
17.392040729522705
The number of items in train is:
12
The loss for epoch 1
1.4493367274602253
The running loss is:
11.61117922514677
The number of items in train is:
12
The loss for epoch 2
0.9675982687622309
The running loss is:
11.772338047623634
The number of items in train is:
12
The loss for epoch 3
0.9810281706353029
The running loss is:
11.49287236109376
The number of items in train is:
12
The loss for epoch 4
0.95773936342448
The running loss is:
10.781698107719421
The number of items in train is:
12
The loss for epoch 5
0.8984748423099518
The running loss is:
10.424548596143723
The number of items in train is:
12
The loss for epoch 6
0.8687123830119768
The running loss is:
10.12140953913331
The number of items in train is:
12
The loss for epoch 7
0.8434507949277759
The running loss is:
9.658258616924286
The number of items in train is:
12
The loss for epoch 8
0.8048548847436905
The running loss is:
9.880091970786452
The number of items in train is:
12
The loss for epoch 9
0.8233409975655377
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.166862
47 30819 Eagle County, Colorado, United States ... 47 2.140870
48 30820 Eagle County, Colorado, United States ... 48 3.050914
49 30821 Eagle County, Colorado, United States ... 49 2.472847
50 30822 Eagle County, Colorado, United States ... 50 2.448125
51 30823 Eagle County, Colorado, United States ... 51 2.150080
52 30824 Eagle County, Colorado, United States ... 52 5.302005
53 30825 Eagle County, Colorado, United States ... 53 5.484312
54 30826 Eagle County, Colorado, United States ... 54 6.253271
55 30827 Eagle County, Colorado, United States ... 55 7.036977
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: n3y19nh5 wandb: Agent Starting Run: h1q7w0qd with config: batch_size: 3 forecast_history: 6 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: h1q7w0qd
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.079257428646088
The number of items in train is:
12
The loss for epoch 0
1.2566047857205074
The running loss is:
15.718450710177422
The number of items in train is:
12
The loss for epoch 1
1.309870892514785
The running loss is:
12.495803490281105
The number of items in train is:
12
The loss for epoch 2
1.0413169575234253
The running loss is:
12.496650338172913
The number of items in train is:
12
The loss for epoch 3
1.041387528181076
The running loss is:
12.224688678979874
The number of items in train is:
12
The loss for epoch 4
1.0187240565816562
The running loss is:
11.561807550489902
The number of items in train is:
12
The loss for epoch 5
0.9634839625408252
The running loss is:
11.38438879698515
The number of items in train is:
12
The loss for epoch 6
0.9486990664154291
The running loss is:
11.246962681412697
The number of items in train is:
12
The loss for epoch 7
0.9372468901177248
The running loss is:
10.89895249903202
The number of items in train is:
12
The loss for epoch 8
0.9082460415860018
The running loss is:
10.400408629328012
The number of items in train is:
12
The loss for epoch 9
0.8667007191106677
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.580725
47 30819 Eagle County, Colorado, United States ... 47 1.974475
48 30820 Eagle County, Colorado, United States ... 48 -0.211604
49 30821 Eagle County, Colorado, United States ... 49 0.609134
50 30822 Eagle County, Colorado, United States ... 50 1.167469
51 30823 Eagle County, Colorado, United States ... 51 1.519079
52 30824 Eagle County, Colorado, United States ... 52 4.284061
53 30825 Eagle County, Colorado, United States ... 53 3.987715
54 30826 Eagle County, Colorado, United States ... 54 3.588098
55 30827 Eagle County, Colorado, United States ... 55 2.746731
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: h1q7w0qd wandb: Agent Starting Run: oxt2syp4 with config: batch_size: 3 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: oxt2syp4
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.496992111206055
The number of items in train is:
12
The loss for epoch 0
1.0414160092671711
The running loss is:
23.51863168179989
The number of items in train is:
12
The loss for epoch 1
1.959885973483324
The running loss is:
16.172030597925186
The number of items in train is:
12
The loss for epoch 2
1.3476692164937656
The running loss is:
13.880412250757217
The number of items in train is:
12
The loss for epoch 3
1.1567010208964348
The running loss is:
12.677022129297256
The number of items in train is:
12
The loss for epoch 4
1.0564185107747714
The running loss is:
12.19552794098854
The number of items in train is:
12
The loss for epoch 5
1.0162939950823784
The running loss is:
11.290437750518322
The number of items in train is:
12
The loss for epoch 6
0.9408698125431935
The running loss is:
10.617049016058445
The number of items in train is:
12
The loss for epoch 7
0.884754084671537
The running loss is:
10.623746745288372
The number of items in train is:
12
The loss for epoch 8
0.885312228774031
The running loss is:
9.808349553495646
The number of items in train is:
12
The loss for epoch 9
0.8173624627913038
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.538319
47 30819 Eagle County, Colorado, United States ... 47 3.409076
48 30820 Eagle County, Colorado, United States ... 48 4.306860
49 30821 Eagle County, Colorado, United States ... 49 3.943794
50 30822 Eagle County, Colorado, United States ... 50 4.117706
51 30823 Eagle County, Colorado, United States ... 51 3.392669
52 30824 Eagle County, Colorado, United States ... 52 6.199790
53 30825 Eagle County, Colorado, United States ... 53 5.883504
54 30826 Eagle County, Colorado, United States ... 54 6.553258
55 30827 Eagle County, Colorado, United States ... 55 7.520857
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: oxt2syp4 wandb: Agent Starting Run: ie9c1ks0 with config: batch_size: 3 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ie9c1ks0
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.599737614393234
The number of items in train is:
12
The loss for epoch 0
1.0499781345327694
The running loss is:
22.203148394823074
The number of items in train is:
12
The loss for epoch 1
1.8502623662352562
The running loss is:
14.325762331485748
The number of items in train is:
12
The loss for epoch 2
1.1938135276238124
The running loss is:
13.595742899924517
The number of items in train is:
12
The loss for epoch 3
1.1329785749937098
The running loss is:
11.89985717087984
The number of items in train is:
12
The loss for epoch 4
0.9916547642399868
The running loss is:
11.515253067016602
The number of items in train is:
12
The loss for epoch 5
0.9596044222513834
The running loss is:
11.157676301896572
The number of items in train is:
12
The loss for epoch 6
0.929806358491381
The running loss is:
10.4517732411623
The number of items in train is:
12
The loss for epoch 7
0.8709811034301916
The running loss is:
10.010308530181646
The number of items in train is:
12
The loss for epoch 8
0.8341923775151372
The running loss is:
10.091852685436606
The number of items in train is:
12
The loss for epoch 9
0.8409877237863839
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.594056
47 30819 Eagle County, Colorado, United States ... 47 1.672091
48 30820 Eagle County, Colorado, United States ... 48 4.155540
49 30821 Eagle County, Colorado, United States ... 49 3.079499
50 30822 Eagle County, Colorado, United States ... 50 2.709257
51 30823 Eagle County, Colorado, United States ... 51 1.828926
52 30824 Eagle County, Colorado, United States ... 52 4.691890
53 30825 Eagle County, Colorado, United States ... 53 3.811723
54 30826 Eagle County, Colorado, United States ... 54 5.404132
55 30827 Eagle County, Colorado, United States ... 55 8.138603
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ie9c1ks0 wandb: Agent Starting Run: 2fpwq82a with config: batch_size: 3 forecast_history: 6 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 2fpwq82a
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.415539905428886
The number of items in train is:
12
The loss for epoch 0
1.1179616587857406
The running loss is:
20.85493763536215
The number of items in train is:
12
The loss for epoch 1
1.7379114696135123
The running loss is:
14.253133296966553
The number of items in train is:
12
The loss for epoch 2
1.1877611080805461
The running loss is:
13.560869604349136
The number of items in train is:
12
The loss for epoch 3
1.1300724670290947
The running loss is:
12.388650253415108
The number of items in train is:
12
The loss for epoch 4
1.0323875211179256
The running loss is:
12.170100808143616
The number of items in train is:
12
The loss for epoch 5
1.0141750673453014
The running loss is:
11.739183232188225
The number of items in train is:
12
The loss for epoch 6
0.9782652693490187
The running loss is:
11.55619814991951
The number of items in train is:
12
The loss for epoch 7
0.9630165124932925
The running loss is:
10.790475085377693
The number of items in train is:
12
The loss for epoch 8
0.8992062571148077
The running loss is:
10.633037384599447
The number of items in train is:
12
The loss for epoch 9
0.8860864487166206
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.839489
47 30819 Eagle County, Colorado, United States ... 47 1.569898
48 30820 Eagle County, Colorado, United States ... 48 1.385082
49 30821 Eagle County, Colorado, United States ... 49 0.573623
50 30822 Eagle County, Colorado, United States ... 50 1.309624
51 30823 Eagle County, Colorado, United States ... 51 1.179892
52 30824 Eagle County, Colorado, United States ... 52 4.661685
53 30825 Eagle County, Colorado, United States ... 53 2.778619
54 30826 Eagle County, Colorado, United States ... 54 2.841144
55 30827 Eagle County, Colorado, United States ... 55 4.202115
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2fpwq82a wandb: Agent Starting Run: l8nn6c9n with config: batch_size: 3 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: l8nn6c9n
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.551168888807297
The number of items in train is:
12
The loss for epoch 0
1.3792640740672748
The running loss is:
16.275571942329407
The number of items in train is:
12
The loss for epoch 1
1.3562976618607838
The running loss is:
24.606696739792824
The number of items in train is:
12
The loss for epoch 2
2.050558061649402
The running loss is:
12.262774214148521
The number of items in train is:
12
The loss for epoch 3
1.0218978511790435
The running loss is:
12.773478485643864
The number of items in train is:
12
The loss for epoch 4
1.064456540470322
The running loss is:
11.611447669565678
The number of items in train is:
12
The loss for epoch 5
0.9676206391304731
The running loss is:
11.665397956967354
The number of items in train is:
12
The loss for epoch 6
0.9721164964139462
The running loss is:
10.316370545886457
The number of items in train is:
12
The loss for epoch 7
0.8596975454905381
The running loss is:
11.990142315626144
The number of items in train is:
12
The loss for epoch 8
0.9991785263021787
The running loss is:
10.906970590353012
The number of items in train is:
12
The loss for epoch 9
0.908914215862751
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.308692
47 30819 Eagle County, Colorado, United States ... 47 3.952347
48 30820 Eagle County, Colorado, United States ... 48 7.571158
49 30821 Eagle County, Colorado, United States ... 49 3.904990
50 30822 Eagle County, Colorado, United States ... 50 3.892237
51 30823 Eagle County, Colorado, United States ... 51 3.134773
52 30824 Eagle County, Colorado, United States ... 52 8.374115
53 30825 Eagle County, Colorado, United States ... 53 7.191282
54 30826 Eagle County, Colorado, United States ... 54 8.137844
55 30827 Eagle County, Colorado, United States ... 55 9.537454
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l8nn6c9n wandb: Agent Starting Run: km3ikef2 with config: batch_size: 3 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: km3ikef2
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.698626637458801
The number of items in train is:
12
The loss for epoch 0
1.2248855531215668
The running loss is:
20.655080318450928
The number of items in train is:
12
The loss for epoch 1
1.721256693204244
The running loss is:
18.092076182365417
The number of items in train is:
12
The loss for epoch 2
1.507673015197118
The running loss is:
12.09486810863018
The number of items in train is:
12
The loss for epoch 3
1.0079056757191818
The running loss is:
11.600006587803364
The number of items in train is:
12
The loss for epoch 4
0.9666672156502804
The running loss is:
10.95479815453291
The number of items in train is:
12
The loss for epoch 5
0.9128998462110758
The running loss is:
11.188478022813797
The number of items in train is:
12
The loss for epoch 6
0.9323731685678164
The running loss is:
10.409742364659905
The number of items in train is:
12
The loss for epoch 7
0.8674785303883255
The running loss is:
10.057693980634212
The number of items in train is:
12
The loss for epoch 8
0.8381411650528511
The running loss is:
12.17088376916945
The number of items in train is:
12
The loss for epoch 9
1.014240314097454
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 2.268881
47 30819 ... 1.202799
48 30820 ... 10.090469
49 30821 ... 8.409049
50 30822 ... 6.849900
51 30823 ... 2.807540
52 30824 ... 5.809826
53 30825 ... 2.110427
54 30826 ... 5.633467
55 30827 ... 13.213568
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: km3ikef2 wandb: Agent Starting Run: c5lun9dz with config: batch_size: 3 forecast_history: 6 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: c5lun9dz
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.00420992076397
The number of items in train is:
12
The loss for epoch 0
1.1670174933969975
The running loss is:
19.73149611055851
The number of items in train is:
12
The loss for epoch 1
1.6442913425465424
The running loss is:
15.858351707458496
The number of items in train is:
12
The loss for epoch 2
1.3215293089548747
The running loss is:
13.022899746894836
The number of items in train is:
12
The loss for epoch 3
1.0852416455745697
The running loss is:
12.677206307649612
The number of items in train is:
12
The loss for epoch 4
1.056433858970801
The running loss is:
12.486706361174583
The number of items in train is:
12
The loss for epoch 5
1.0405588634312153
The running loss is:
12.287828579545021
The number of items in train is:
12
The loss for epoch 6
1.023985714962085
The running loss is:
11.929625041782856
The number of items in train is:
12
The loss for epoch 7
0.9941354201485714
The running loss is:
12.279497995972633
The number of items in train is:
12
The loss for epoch 8
1.023291499664386
The running loss is:
11.818829461932182
The number of items in train is:
12
The loss for epoch 9
0.9849024551610152
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.814013
47 30819 ... 6.518628
48 30820 ... 9.284746
49 30821 ... 6.500539
50 30822 ... 7.052881
51 30823 ... 5.470279
52 30824 ... 9.392167
53 30825 ... 9.151134
54 30826 ... 9.920794
55 30827 ... 11.009304
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c5lun9dz wandb: Agent Starting Run: b3b14bgb with config: batch_size: 3 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: b3b14bgb
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
81.98305875062943
The number of items in train is:
12
The loss for epoch 0
6.831921562552452
The running loss is:
23.46656311303377
The number of items in train is:
12
The loss for epoch 1
1.9555469260861476
The running loss is:
18.955001026391983
The number of items in train is:
12
The loss for epoch 2
1.5795834188659985
The running loss is:
13.628064028918743
The number of items in train is:
12
The loss for epoch 3
1.1356720024098952
The running loss is:
13.840984091162682
The number of items in train is:
12
The loss for epoch 4
1.1534153409302235
The running loss is:
12.88997782766819
The number of items in train is:
12
The loss for epoch 5
1.0741648189723492
The running loss is:
12.13399039208889
The number of items in train is:
12
The loss for epoch 6
1.0111658660074074
The running loss is:
12.013321369886398
The number of items in train is:
12
The loss for epoch 7
1.0011101141571999
The running loss is:
11.848396576941013
The number of items in train is:
12
The loss for epoch 8
0.9873663814117511
The running loss is:
12.80077788233757
The number of items in train is:
12
The loss for epoch 9
1.0667314901947975
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.724473
47 30819 ... 8.855355
48 30820 ... 13.927794
49 30821 ... 10.620327
50 30822 ... 7.505313
51 30823 ... 5.085643
52 30824 ... 7.951116
53 30825 ... 8.628775
54 30826 ... 10.043982
55 30827 ... 17.028318
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: b3b14bgb wandb: Agent Starting Run: s1h956bq with config: batch_size: 3 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: s1h956bq
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
59.376845210790634
The number of items in train is:
12
The loss for epoch 0
4.9480704342325526
The running loss is:
20.686773542314768
The number of items in train is:
12
The loss for epoch 1
1.7238977951928973
The running loss is:
13.994047820568085
The number of items in train is:
12
The loss for epoch 2
1.1661706517140071
The running loss is:
11.97829656675458
The number of items in train is:
12
The loss for epoch 3
0.9981913805628816
The running loss is:
11.18816128000617
The number of items in train is:
12
The loss for epoch 4
0.9323467733338475
The running loss is:
14.145705461502075
The number of items in train is:
12
The loss for epoch 5
1.1788087884585063
The running loss is:
11.821292378008366
The number of items in train is:
12
The loss for epoch 6
0.9851076981673638
The running loss is:
12.026786141097546
The number of items in train is:
12
The loss for epoch 7
1.0022321784247954
The running loss is:
11.274334587156773
The number of items in train is:
12
The loss for epoch 8
0.9395278822630644
The running loss is:
10.756500020623207
The number of items in train is:
12
The loss for epoch 9
0.8963750017186006
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 3.249136
47 30819 ... 7.751321
48 30820 ... 12.270601
49 30821 ... 5.888708
50 30822 ... 4.762325
51 30823 ... 5.235315
52 30824 ... 7.638667
53 30825 ... 10.344776
54 30826 ... 10.507303
55 30827 ... 10.673805
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: s1h956bq wandb: Agent Starting Run: vo80oil3 with config: batch_size: 3 forecast_history: 6 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: vo80oil3
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 6
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 6
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 6
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 6
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
45.60368609428406
The number of items in train is:
12
The loss for epoch 0
3.8003071745236716
The running loss is:
18.71952261030674
The number of items in train is:
12
The loss for epoch 1
1.5599602175255616
The running loss is:
14.976400405168533
The number of items in train is:
12
The loss for epoch 2
1.2480333670973778
The running loss is:
12.58779701590538
The number of items in train is:
12
The loss for epoch 3
1.0489830846587818
The running loss is:
13.024215057492256
The number of items in train is:
12
The loss for epoch 4
1.0853512547910213
The running loss is:
12.297743678092957
The number of items in train is:
12
The loss for epoch 5
1.024811973174413
The running loss is:
12.213317602872849
The number of items in train is:
12
The loss for epoch 6
1.0177764669060707
The running loss is:
12.347241327166557
The number of items in train is:
12
The loss for epoch 7
1.0289367772638798
The running loss is:
12.762004941701889
The number of items in train is:
12
The loss for epoch 8
1.0635004118084908
The running loss is:
12.372626543045044
The number of items in train is:
12
The loss for epoch 9
1.0310522119204204
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 6, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.393170
47 30819 ... 11.193472
48 30820 ... 11.361673
49 30821 ... 11.471720
50 30822 ... 11.755054
51 30823 ... 11.518402
52 30824 ... 11.129681
53 30825 ... 11.483230
54 30826 ... 12.134523
55 30827 ... 13.660666
[16 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vo80oil3 wandb: Agent Starting Run: ubv4ystc with config: batch_size: 3 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: ubv4ystc
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.101865265518427
The number of items in train is:
12
The loss for epoch 0
1.1751554387932022
The running loss is:
26.686464205384254
The number of items in train is:
12
The loss for epoch 1
2.2238720171153545
The running loss is:
13.082868907600641
The number of items in train is:
12
The loss for epoch 2
1.0902390756333868
The running loss is:
12.054546843282878
The number of items in train is:
12
The loss for epoch 3
1.0045455702735733
The running loss is:
11.357063516043127
The number of items in train is:
12
The loss for epoch 4
0.9464219596702605
The running loss is:
10.975450985133648
The number of items in train is:
12
The loss for epoch 5
0.914620915427804
The running loss is:
10.746945226565003
The number of items in train is:
12
The loss for epoch 6
0.895578768880417
The running loss is:
10.431892652064562
The number of items in train is:
12
The loss for epoch 7
0.8693243876720468
The running loss is:
10.116163417696953
The number of items in train is:
12
The loss for epoch 8
0.8430136181414127
The running loss is:
9.563586957752705
The number of items in train is:
12
The loss for epoch 9
0.7969655798127254
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.468307
47 30819 ... 6.544013
48 30820 ... 5.728243
49 30821 ... 5.464718
50 30822 ... 5.680757
51 30823 ... 6.046756
52 30824 ... 6.474231
53 30825 ... 9.770175
54 30826 ... 10.915289
55 30827 ... 11.168087
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ubv4ystc wandb: Agent Starting Run: gz2rrs14 with config: batch_size: 3 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: gz2rrs14
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.668365709483624
The number of items in train is:
12
The loss for epoch 0
1.139030475790302
The running loss is:
22.000758349895477
The number of items in train is:
12
The loss for epoch 1
1.8333965291579564
The running loss is:
12.867923766374588
The number of items in train is:
12
The loss for epoch 2
1.0723269805312157
The running loss is:
12.467137441039085
The number of items in train is:
12
The loss for epoch 3
1.0389281200865905
The running loss is:
12.045014038681984
The number of items in train is:
12
The loss for epoch 4
1.0037511698901653
The running loss is:
11.449671164155006
The number of items in train is:
12
The loss for epoch 5
0.9541392636795839
The running loss is:
11.364717662334442
The number of items in train is:
12
The loss for epoch 6
0.9470598051945368
The running loss is:
11.024014353752136
The number of items in train is:
12
The loss for epoch 7
0.918667862812678
The running loss is:
10.835795931518078
The number of items in train is:
12
The loss for epoch 8
0.9029829942931732
The running loss is:
10.63074404746294
The number of items in train is:
12
The loss for epoch 9
0.8858953372885784
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.082046
47 30819 ... 5.716176
48 30820 ... 4.953457
49 30821 ... 5.225757
50 30822 ... 5.296615
51 30823 ... 5.834962
52 30824 ... 6.323007
53 30825 ... 9.013754
54 30826 ... 9.816219
55 30827 ... 10.285398
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gz2rrs14 wandb: Agent Starting Run: c7r3et8o with config: batch_size: 3 forecast_history: 7 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: c7r3et8o
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.087084546685219
The number of items in train is:
11
The loss for epoch 0
1.2806440496986562
The running loss is:
15.108550131320953
The number of items in train is:
11
The loss for epoch 1
1.373504557392814
The running loss is:
11.57915723323822
The number of items in train is:
11
The loss for epoch 2
1.0526506575671108
The running loss is:
11.622581869363785
The number of items in train is:
11
The loss for epoch 3
1.0565983517603441
The running loss is:
11.423680514097214
The number of items in train is:
11
The loss for epoch 4
1.038516410372474
The running loss is:
11.086277157068253
The number of items in train is:
11
The loss for epoch 5
1.0078433779152958
The running loss is:
10.852890878915787
The number of items in train is:
11
The loss for epoch 6
0.9866264435377988
The running loss is:
10.427777409553528
The number of items in train is:
11
The loss for epoch 7
0.9479797645048662
The running loss is:
10.2155372351408
The number of items in train is:
11
The loss for epoch 8
0.9286852031946182
The running loss is:
9.269150421023369
The number of items in train is:
11
The loss for epoch 9
0.8426500382748517
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.902751
47 30819 ... 6.116383
48 30820 ... 5.196961
49 30821 ... 6.538588
50 30822 ... 6.004770
51 30823 ... 7.052540
52 30824 ... 7.391847
53 30825 ... 11.100878
54 30826 ... 12.244072
55 30827 ... 14.028635
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c7r3et8o wandb: Agent Starting Run: 2btvbagt with config: batch_size: 3 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 2btvbagt
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.820672918111086
The number of items in train is:
12
The loss for epoch 0
1.1517227431759238
The running loss is:
26.606332644820213
The number of items in train is:
12
The loss for epoch 1
2.2171943870683513
The running loss is:
19.74119022488594
The number of items in train is:
12
The loss for epoch 2
1.6450991854071617
The running loss is:
13.292974773794413
The number of items in train is:
12
The loss for epoch 3
1.107747897816201
The running loss is:
12.035850204527378
The number of items in train is:
12
The loss for epoch 4
1.0029875170439482
The running loss is:
10.859765394590795
The number of items in train is:
12
The loss for epoch 5
0.904980449549233
The running loss is:
10.321846425533295
The number of items in train is:
12
The loss for epoch 6
0.8601538687944412
The running loss is:
10.080843094736338
The number of items in train is:
12
The loss for epoch 7
0.8400702578946948
The running loss is:
9.47326545137912
The number of items in train is:
12
The loss for epoch 8
0.7894387876149267
The running loss is:
9.196296703070402
The number of items in train is:
12
The loss for epoch 9
0.7663580585892001
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.013854
47 30819 Eagle County, Colorado, United States ... 47 4.551272
48 30820 Eagle County, Colorado, United States ... 48 3.015524
49 30821 Eagle County, Colorado, United States ... 49 1.243749
50 30822 Eagle County, Colorado, United States ... 50 1.685084
51 30823 Eagle County, Colorado, United States ... 51 2.245061
52 30824 Eagle County, Colorado, United States ... 52 3.145492
53 30825 Eagle County, Colorado, United States ... 53 5.108663
54 30826 Eagle County, Colorado, United States ... 54 6.053539
55 30827 Eagle County, Colorado, United States ... 55 5.009378
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 2btvbagt wandb: Agent Starting Run: vf9yil9d with config: batch_size: 3 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: vf9yil9d
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.319420583546162
The number of items in train is:
12
The loss for epoch 0
1.1099517152955134
The running loss is:
23.99860054254532
The number of items in train is:
12
The loss for epoch 1
1.9998833785454433
The running loss is:
16.226833522319794
The number of items in train is:
12
The loss for epoch 2
1.3522361268599827
The running loss is:
13.81850466877222
The number of items in train is:
12
The loss for epoch 3
1.1515420557310183
The running loss is:
12.647154584527016
The number of items in train is:
12
The loss for epoch 4
1.0539295487105846
The running loss is:
11.547047853469849
The number of items in train is:
12
The loss for epoch 5
0.962253987789154
The running loss is:
10.53432285785675
The number of items in train is:
12
The loss for epoch 6
0.8778602381547292
The running loss is:
10.211327746510506
The number of items in train is:
12
The loss for epoch 7
0.8509439788758755
The running loss is:
10.368523627519608
The number of items in train is:
12
The loss for epoch 8
0.864043635626634
The running loss is:
9.499119475483894
The number of items in train is:
12
The loss for epoch 9
0.7915932896236578
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.554091
47 30819 Eagle County, Colorado, United States ... 47 4.430425
48 30820 Eagle County, Colorado, United States ... 48 3.866688
49 30821 Eagle County, Colorado, United States ... 49 4.931254
50 30822 Eagle County, Colorado, United States ... 50 4.549019
51 30823 Eagle County, Colorado, United States ... 51 5.059370
52 30824 Eagle County, Colorado, United States ... 52 5.614854
53 30825 Eagle County, Colorado, United States ... 53 6.800270
54 30826 Eagle County, Colorado, United States ... 54 6.520226
55 30827 Eagle County, Colorado, United States ... 55 6.729157
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vf9yil9d wandb: Agent Starting Run: 95ntbs64 with config: batch_size: 3 forecast_history: 7 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 95ntbs64
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
12.921886771917343
The number of items in train is:
11
The loss for epoch 0
1.174716979265213
The running loss is:
19.92188435792923
The number of items in train is:
11
The loss for epoch 1
1.8110803961753845
The running loss is:
13.59029796719551
The number of items in train is:
11
The loss for epoch 2
1.23548163338141
The running loss is:
13.310383319854736
The number of items in train is:
11
The loss for epoch 3
1.2100348472595215
The running loss is:
11.705954015254974
The number of items in train is:
11
The loss for epoch 4
1.0641776377504522
The running loss is:
11.907550156116486
The number of items in train is:
11
The loss for epoch 5
1.0825045596469531
The running loss is:
11.72386035323143
The number of items in train is:
11
The loss for epoch 6
1.0658054866574027
The running loss is:
11.24789434671402
The number of items in train is:
11
The loss for epoch 7
1.0225358497012744
The running loss is:
10.430751740932465
The number of items in train is:
11
The loss for epoch 8
0.9482501582665877
The running loss is:
9.527582883834839
The number of items in train is:
11
The loss for epoch 9
0.8661438985304399
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.573842
47 30819 Eagle County, Colorado, United States ... 47 5.654085
48 30820 Eagle County, Colorado, United States ... 48 5.214627
49 30821 Eagle County, Colorado, United States ... 49 6.999577
50 30822 Eagle County, Colorado, United States ... 50 6.205671
51 30823 Eagle County, Colorado, United States ... 51 7.371466
52 30824 Eagle County, Colorado, United States ... 52 8.793597
53 30825 Eagle County, Colorado, United States ... 53 9.819304
54 30826 Eagle County, Colorado, United States ... 54 9.304229
55 30827 Eagle County, Colorado, United States ... 55 9.831146
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 95ntbs64 wandb: Agent Starting Run: 1x40zbqa with config: batch_size: 3 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 1x40zbqa
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
22.54161025211215
The number of items in train is:
12
The loss for epoch 0
1.8784675210093458
The running loss is:
17.038389161229134
The number of items in train is:
12
The loss for epoch 1
1.4198657634357612
The running loss is:
31.379464015364647
The number of items in train is:
12
The loss for epoch 2
2.6149553346137204
The running loss is:
13.966453918255866
The number of items in train is:
12
The loss for epoch 3
1.1638711598546554
The running loss is:
15.581669982522726
The number of items in train is:
12
The loss for epoch 4
1.2984724985435605
The running loss is:
11.612488612532616
The number of items in train is:
12
The loss for epoch 5
0.967707384377718
The running loss is:
11.270859359763563
The number of items in train is:
12
The loss for epoch 6
0.9392382799802969
The running loss is:
9.403395362198353
The number of items in train is:
12
The loss for epoch 7
0.7836162801831961
The running loss is:
8.220736034214497
The number of items in train is:
12
The loss for epoch 8
0.6850613361845413
The running loss is:
9.775267072021961
The number of items in train is:
12
The loss for epoch 9
0.8146055893351635
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.412656
47 30819 Eagle County, Colorado, United States ... 47 5.343231
48 30820 Eagle County, Colorado, United States ... 48 4.858974
49 30821 Eagle County, Colorado, United States ... 49 4.976553
50 30822 Eagle County, Colorado, United States ... 50 4.848750
51 30823 Eagle County, Colorado, United States ... 51 4.915821
52 30824 Eagle County, Colorado, United States ... 52 5.174218
53 30825 Eagle County, Colorado, United States ... 53 7.864298
54 30826 Eagle County, Colorado, United States ... 54 7.851389
55 30827 Eagle County, Colorado, United States ... 55 7.985761
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1x40zbqa wandb: Agent Starting Run: 0xhh0dml with config: batch_size: 3 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 0xhh0dml
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
18.429566003382206
The number of items in train is:
12
The loss for epoch 0
1.535797166948517
The running loss is:
18.622036963701248
The number of items in train is:
12
The loss for epoch 1
1.5518364136417706
The running loss is:
28.973867908120155
The number of items in train is:
12
The loss for epoch 2
2.414488992343346
The running loss is:
16.044194497168064
The number of items in train is:
12
The loss for epoch 3
1.3370162080973387
The running loss is:
16.122961774468422
The number of items in train is:
12
The loss for epoch 4
1.3435801478723686
The running loss is:
12.899257555603981
The number of items in train is:
12
The loss for epoch 5
1.074938129633665
The running loss is:
12.557156592607498
The number of items in train is:
12
The loss for epoch 6
1.0464297160506248
The running loss is:
12.619301199913025
The number of items in train is:
12
The loss for epoch 7
1.0516084333260853
The running loss is:
12.38354542851448
The number of items in train is:
12
The loss for epoch 8
1.0319621190428734
The running loss is:
11.681083425879478
The number of items in train is:
12
The loss for epoch 9
0.9734236188232899
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.246218
47 30819 ... 14.066824
48 30820 ... 12.973879
49 30821 ... 10.188002
50 30822 ... 10.609279
51 30823 ... 10.523514
52 30824 ... 11.179653
53 30825 ... 12.925735
54 30826 ... 13.551861
55 30827 ... 13.512096
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0xhh0dml wandb: Agent Starting Run: ye5e1j66 with config: batch_size: 3 forecast_history: 7 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ye5e1j66
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.376830667257309
The number of items in train is:
11
The loss for epoch 0
1.306984606114301
The running loss is:
16.50704401731491
The number of items in train is:
11
The loss for epoch 1
1.5006403652104465
The running loss is:
18.80806991457939
The number of items in train is:
11
The loss for epoch 2
1.7098245376890355
The running loss is:
12.212967872619629
The number of items in train is:
11
The loss for epoch 3
1.1102698066017844
The running loss is:
12.07007920742035
The number of items in train is:
11
The loss for epoch 4
1.0972799279473044
The running loss is:
11.875926405191422
The number of items in train is:
11
The loss for epoch 5
1.07962967319922
The running loss is:
11.825728297233582
The number of items in train is:
11
The loss for epoch 6
1.0750662088394165
The running loss is:
11.659875005483627
The number of items in train is:
11
The loss for epoch 7
1.0599886368621478
The running loss is:
11.533598870038986
The number of items in train is:
11
The loss for epoch 8
1.0485089881853624
The running loss is:
10.735102593898773
The number of items in train is:
11
The loss for epoch 9
0.9759184176271612
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.420413
47 30819 ... 8.245983
48 30820 ... 7.171728
49 30821 ... 7.246099
50 30822 ... 6.445683
51 30823 ... 7.200696
52 30824 ... 8.086080
53 30825 ... 11.314844
54 30826 ... 12.178420
55 30827 ... 12.283268
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ye5e1j66 wandb: Agent Starting Run: 62zrpq21 with config: batch_size: 3 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 62zrpq21
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
103.22703457251191
The number of items in train is:
12
The loss for epoch 0
8.60225288104266
The running loss is:
29.94053180515766
The number of items in train is:
12
The loss for epoch 1
2.495044317096472
The running loss is:
16.690219312906265
The number of items in train is:
12
The loss for epoch 2
1.3908516094088554
The running loss is:
13.111681044101715
The number of items in train is:
12
The loss for epoch 3
1.0926400870084763
The running loss is:
15.997931838035583
The number of items in train is:
12
The loss for epoch 4
1.3331609865029652
The running loss is:
11.851074589183554
The number of items in train is:
12
The loss for epoch 5
0.9875895490986295
The running loss is:
10.893377058207989
The number of items in train is:
12
The loss for epoch 6
0.9077814215173324
The running loss is:
11.342389456927776
The number of items in train is:
12
The loss for epoch 7
0.945199121410648
The running loss is:
10.936100173741579
The number of items in train is:
12
The loss for epoch 8
0.9113416811451316
The running loss is:
10.374511506408453
The number of items in train is:
12
The loss for epoch 9
0.8645426255340377
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.288023
47 30819 Eagle County, Colorado, United States ... 47 2.294388
48 30820 Eagle County, Colorado, United States ... 48 2.283244
49 30821 Eagle County, Colorado, United States ... 49 2.281832
50 30822 Eagle County, Colorado, United States ... 50 2.283400
51 30823 Eagle County, Colorado, United States ... 51 2.285488
52 30824 Eagle County, Colorado, United States ... 52 2.234835
53 30825 Eagle County, Colorado, United States ... 53 3.238281
54 30826 Eagle County, Colorado, United States ... 54 3.240119
55 30827 Eagle County, Colorado, United States ... 55 3.236318
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 62zrpq21 wandb: Agent Starting Run: 4hwszs1n with config: batch_size: 3 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 4hwszs1n
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
81.03642698377371
The number of items in train is:
12
The loss for epoch 0
6.753035581981142
The running loss is:
20.14825175702572
The number of items in train is:
12
The loss for epoch 1
1.6790209797521432
The running loss is:
21.776003628969193
The number of items in train is:
12
The loss for epoch 2
1.814666969080766
The running loss is:
12.587840363383293
The number of items in train is:
12
The loss for epoch 3
1.0489866969486077
The running loss is:
13.271085634827614
The number of items in train is:
12
The loss for epoch 4
1.105923802902301
The running loss is:
15.132914364337921
The number of items in train is:
12
The loss for epoch 5
1.26107619702816
The running loss is:
12.673068717122078
The number of items in train is:
12
The loss for epoch 6
1.056089059760173
The running loss is:
13.078043937683105
The number of items in train is:
12
The loss for epoch 7
1.0898369948069255
The running loss is:
12.038839250802994
The number of items in train is:
12
The loss for epoch 8
1.0032366042335827
The running loss is:
13.619364827871323
The number of items in train is:
12
The loss for epoch 9
1.1349470689892769
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.130917
47 30819 Eagle County, Colorado, United States ... 47 6.415527
48 30820 Eagle County, Colorado, United States ... 48 7.077496
49 30821 Eagle County, Colorado, United States ... 49 6.234654
50 30822 Eagle County, Colorado, United States ... 50 6.276112
51 30823 Eagle County, Colorado, United States ... 51 6.861938
52 30824 Eagle County, Colorado, United States ... 52 7.286839
53 30825 Eagle County, Colorado, United States ... 53 9.426314
54 30826 Eagle County, Colorado, United States ... 54 9.667464
55 30827 Eagle County, Colorado, United States ... 55 9.229389
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 4hwszs1n wandb: Agent Starting Run: cy9snt8t with config: batch_size: 3 forecast_history: 7 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: cy9snt8t
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 7
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 7
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 7
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 7
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
54.83278104662895
The number of items in train is:
11
The loss for epoch 0
4.984798276966268
The running loss is:
15.510921031236649
The number of items in train is:
11
The loss for epoch 1
1.4100837301124225
The running loss is:
15.879859685897827
The number of items in train is:
11
The loss for epoch 2
1.4436236078088933
The running loss is:
12.013406425714493
The number of items in train is:
11
The loss for epoch 3
1.0921278568831356
The running loss is:
13.37919408082962
The number of items in train is:
11
The loss for epoch 4
1.216290370984511
The running loss is:
11.679980754852295
The number of items in train is:
11
The loss for epoch 5
1.0618164322592996
The running loss is:
11.539081782102585
The number of items in train is:
11
The loss for epoch 6
1.0490074347365985
The running loss is:
11.794884741306305
The number of items in train is:
11
The loss for epoch 7
1.072262249209664
The running loss is:
11.983941286802292
The number of items in train is:
11
The loss for epoch 8
1.0894492078911175
The running loss is:
11.315197944641113
The number of items in train is:
11
The loss for epoch 9
1.0286543586037376
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 7, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 13.684507
47 30819 ... 13.638751
48 30820 ... 13.938817
49 30821 ... 15.181535
50 30822 ... 15.354393
51 30823 ... 14.973742
52 30824 ... 14.617647
53 30825 ... 19.675823
54 30826 ... 19.256590
55 30827 ... 20.088932
[17 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cy9snt8t wandb: Agent Starting Run: gllvj7he with config: batch_size: 3 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: gllvj7he
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.211308494210243
The number of items in train is:
12
The loss for epoch 0
1.4342757078508537
The running loss is:
16.233859598636627
The number of items in train is:
12
The loss for epoch 1
1.352821633219719
The running loss is:
12.66020293906331
The number of items in train is:
12
The loss for epoch 2
1.0550169115886092
The running loss is:
11.963709861040115
The number of items in train is:
12
The loss for epoch 3
0.996975821753343
The running loss is:
11.758347198367119
The number of items in train is:
12
The loss for epoch 4
0.9798622665305933
The running loss is:
11.206863448023796
The number of items in train is:
12
The loss for epoch 5
0.9339052873353163
The running loss is:
11.012989409267902
The number of items in train is:
12
The loss for epoch 6
0.9177491174389919
The running loss is:
10.944889828562737
The number of items in train is:
12
The loss for epoch 7
0.912074152380228
The running loss is:
11.287752538919449
The number of items in train is:
12
The loss for epoch 8
0.9406460449099541
The running loss is:
10.014553174376488
The number of items in train is:
12
The loss for epoch 9
0.8345460978647073
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.422697
47 30819 ... 7.106028
48 30820 ... 9.759746
49 30821 ... 8.222320
50 30822 ... 4.610928
51 30823 ... 6.268315
52 30824 ... 6.628915
53 30825 ... 6.769064
54 30826 ... 9.233932
55 30827 ... 12.926121
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: gllvj7he wandb: Agent Starting Run: 11cp523e with config: batch_size: 3 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 11cp523e
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.0985167324543
The number of items in train is:
11
The loss for epoch 0
1.3725924302231183
The running loss is:
16.43994829058647
The number of items in train is:
11
The loss for epoch 1
1.4945407536896793
The running loss is:
12.457493215799332
The number of items in train is:
11
The loss for epoch 2
1.1324993832544847
The running loss is:
12.50855478644371
The number of items in train is:
11
The loss for epoch 3
1.1371413442221554
The running loss is:
12.073927566409111
The number of items in train is:
11
The loss for epoch 4
1.0976297787644647
The running loss is:
11.802223101258278
The number of items in train is:
11
The loss for epoch 5
1.0729293728416616
The running loss is:
11.131017163395882
The number of items in train is:
11
The loss for epoch 6
1.0119106512178073
The running loss is:
10.766869887709618
The number of items in train is:
11
The loss for epoch 7
0.978806353428147
The running loss is:
10.445338189601898
The number of items in train is:
11
The loss for epoch 8
0.949576199054718
The running loss is:
10.062777064740658
The number of items in train is:
11
The loss for epoch 9
0.9147979149764235
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.078831
47 30819 ... 11.039064
48 30820 ... 16.357121
49 30821 ... 13.192023
50 30822 ... 6.326085
51 30823 ... 9.873568
52 30824 ... 10.910859
53 30825 ... 11.316805
54 30826 ... 15.975700
55 30827 ... 22.182123
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 11cp523e wandb: Agent Starting Run: 5qrg143a with config: batch_size: 3 forecast_history: 8 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 5qrg143a
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.156650215387344
The number of items in train is:
11
The loss for epoch 0
1.2869682013988495
The running loss is:
16.89894598722458
The number of items in train is:
11
The loss for epoch 1
1.5362678170204163
The running loss is:
11.663092344999313
The number of items in train is:
11
The loss for epoch 2
1.060281122272665
The running loss is:
11.744797706604004
The number of items in train is:
11
The loss for epoch 3
1.067708882418546
The running loss is:
11.475342273712158
The number of items in train is:
11
The loss for epoch 4
1.0432129339738325
The running loss is:
11.35976918041706
The number of items in train is:
11
The loss for epoch 5
1.0327062891288237
The running loss is:
11.192541688680649
The number of items in train is:
11
The loss for epoch 6
1.017503789880059
The running loss is:
11.171793431043625
The number of items in train is:
11
The loss for epoch 7
1.0156175846403295
The running loss is:
10.933511719107628
The number of items in train is:
11
The loss for epoch 8
0.9939556108279661
The running loss is:
10.853802099823952
The number of items in train is:
11
The loss for epoch 9
0.9867092818021774
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 7.104875
47 30819 Eagle County, Colorado, United States ... 47 7.535665
48 30820 Eagle County, Colorado, United States ... 48 7.494577
49 30821 Eagle County, Colorado, United States ... 49 6.863788
50 30822 Eagle County, Colorado, United States ... 50 6.753548
51 30823 Eagle County, Colorado, United States ... 51 6.998057
52 30824 Eagle County, Colorado, United States ... 52 7.178608
53 30825 Eagle County, Colorado, United States ... 53 7.816975
54 30826 Eagle County, Colorado, United States ... 54 8.525613
55 30827 Eagle County, Colorado, United States ... 55 8.816086
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 5qrg143a wandb: Agent Starting Run: xml2wk55 with config: batch_size: 3 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: xml2wk55
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.242870450019836
The number of items in train is:
12
The loss for epoch 0
1.103572537501653
The running loss is:
26.00589569658041
The number of items in train is:
12
The loss for epoch 1
2.167157974715034
The running loss is:
16.079134315252304
The number of items in train is:
12
The loss for epoch 2
1.3399278596043587
The running loss is:
14.295495130121708
The number of items in train is:
12
The loss for epoch 3
1.1912912608434756
The running loss is:
12.250516004860401
The number of items in train is:
12
The loss for epoch 4
1.0208763337383668
The running loss is:
12.25134564191103
The number of items in train is:
12
The loss for epoch 5
1.0209454701592524
The running loss is:
11.315909065306187
The number of items in train is:
12
The loss for epoch 6
0.9429924221088489
The running loss is:
12.214250043034554
The number of items in train is:
12
The loss for epoch 7
1.0178541702528794
The running loss is:
11.34765262156725
The number of items in train is:
12
The loss for epoch 8
0.9456377184639374
The running loss is:
11.16403116285801
The number of items in train is:
12
The loss for epoch 9
0.9303359302381674
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.780159
47 30819 ... 7.524302
48 30820 ... 8.775655
49 30821 ... 7.754395
50 30822 ... 4.720078
51 30823 ... 6.290050
52 30824 ... 6.727722
53 30825 ... 5.912613
54 30826 ... 8.422699
55 30827 ... 11.214253
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xml2wk55 wandb: Agent Starting Run: 57qin94v with config: batch_size: 3 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 57qin94v
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.26663488149643
The number of items in train is:
11
The loss for epoch 0
1.2969668074087664
The running loss is:
20.902589723467827
The number of items in train is:
11
The loss for epoch 1
1.900235429406166
The running loss is:
13.939648985862732
The number of items in train is:
11
The loss for epoch 2
1.267240816896612
The running loss is:
13.26231038570404
The number of items in train is:
11
The loss for epoch 3
1.205664580518549
The running loss is:
12.16365271806717
The number of items in train is:
11
The loss for epoch 4
1.105786610733379
The running loss is:
11.990179777145386
The number of items in train is:
11
The loss for epoch 5
1.0900163433768533
The running loss is:
10.77952553331852
The number of items in train is:
11
The loss for epoch 6
0.97995686666532
The running loss is:
9.914591431617737
The number of items in train is:
11
The loss for epoch 7
0.9013264937834307
The running loss is:
9.7501370459795
The number of items in train is:
11
The loss for epoch 8
0.8863760950890455
The running loss is:
10.100802019238472
The number of items in train is:
11
The loss for epoch 9
0.9182547290216793
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 6.128566
47 30819 ... 8.571231
48 30820 ... 13.003282
49 30821 ... 10.600195
50 30822 ... 3.180500
51 30823 ... 5.083227
52 30824 ... 6.587037
53 30825 ... 6.724599
54 30826 ... 10.925661
55 30827 ... 15.574051
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 57qin94v wandb: Agent Starting Run: c9vklx84 with config: batch_size: 3 forecast_history: 8 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: c9vklx84
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.399442881345749
The number of items in train is:
11
The loss for epoch 0
1.2181311710314318
The running loss is:
21.727802246809006
The number of items in train is:
11
The loss for epoch 1
1.9752547497099096
The running loss is:
14.162266343832016
The number of items in train is:
11
The loss for epoch 2
1.2874787585301832
The running loss is:
13.402291283011436
The number of items in train is:
11
The loss for epoch 3
1.2183901166374034
The running loss is:
11.804574847221375
The number of items in train is:
11
The loss for epoch 4
1.0731431679292158
The running loss is:
11.677122816443443
The number of items in train is:
11
The loss for epoch 5
1.0615566196766766
The running loss is:
11.409079656004906
The number of items in train is:
11
The loss for epoch 6
1.0371890596368096
The running loss is:
11.398159816861153
The number of items in train is:
11
The loss for epoch 7
1.0361963469873776
The running loss is:
11.29641242325306
The number of items in train is:
11
The loss for epoch 8
1.0269465839320964
The running loss is:
11.140063360333443
The number of items in train is:
11
The loss for epoch 9
1.0127330327575856
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.260872
47 30819 Eagle County, Colorado, United States ... 47 8.526230
48 30820 Eagle County, Colorado, United States ... 48 8.849753
49 30821 Eagle County, Colorado, United States ... 49 8.448010
50 30822 Eagle County, Colorado, United States ... 50 8.209758
51 30823 Eagle County, Colorado, United States ... 51 8.382380
52 30824 Eagle County, Colorado, United States ... 52 8.583577
53 30825 Eagle County, Colorado, United States ... 53 8.607120
54 30826 Eagle County, Colorado, United States ... 54 9.303979
55 30827 Eagle County, Colorado, United States ... 55 9.497848
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: c9vklx84 wandb: Agent Starting Run: i5gtlelt with config: batch_size: 3 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: i5gtlelt
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.092710718512535
The number of items in train is:
12
The loss for epoch 0
1.257725893209378
The running loss is:
20.450885623693466
The number of items in train is:
12
The loss for epoch 1
1.704240468641122
The running loss is:
21.794561214745045
The number of items in train is:
12
The loss for epoch 2
1.816213434562087
The running loss is:
12.902893766760826
The number of items in train is:
12
The loss for epoch 3
1.075241147230069
The running loss is:
12.682588957250118
The number of items in train is:
12
The loss for epoch 4
1.0568824131041765
The running loss is:
11.801365286111832
The number of items in train is:
12
The loss for epoch 5
0.9834471071759859
The running loss is:
12.599437983706594
The number of items in train is:
12
The loss for epoch 6
1.0499531653088827
The running loss is:
12.43399265408516
The number of items in train is:
12
The loss for epoch 7
1.0361660545070965
The running loss is:
12.696432754397392
The number of items in train is:
12
The loss for epoch 8
1.0580360628664494
The running loss is:
12.389419689774513
The number of items in train is:
12
The loss for epoch 9
1.0324516408145428
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 7.582536
47 30819 ... 9.944989
48 30820 ... 11.621634
49 30821 ... 10.119394
50 30822 ... 6.626044
51 30823 ... 9.020576
52 30824 ... 9.057504
53 30825 ... 7.155132
54 30826 ... 9.989118
55 30827 ... 12.453584
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: i5gtlelt wandb: Agent Starting Run: o7duvp7g with config: batch_size: 3 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: o7duvp7g
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.42051613330841
The number of items in train is:
11
The loss for epoch 0
1.3109560121189465
The running loss is:
21.608804553747177
The number of items in train is:
11
The loss for epoch 1
1.9644367776133798
The running loss is:
19.04217305779457
The number of items in train is:
11
The loss for epoch 2
1.7311066416176883
The running loss is:
12.788259238004684
The number of items in train is:
11
The loss for epoch 3
1.1625690216367894
The running loss is:
12.244571149349213
The number of items in train is:
11
The loss for epoch 4
1.1131428317590193
The running loss is:
11.830523952841759
The number of items in train is:
11
The loss for epoch 5
1.075502177531069
The running loss is:
10.642112955451012
The number of items in train is:
11
The loss for epoch 6
0.9674648141319101
The running loss is:
10.170588843524456
The number of items in train is:
11
The loss for epoch 7
0.9245989857749506
The running loss is:
11.671000733971596
The number of items in train is:
11
The loss for epoch 8
1.0610000667246906
The running loss is:
10.027777716517448
The number of items in train is:
11
The loss for epoch 9
0.9116161560470407
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 5.864102
47 30819 ... 8.607596
48 30820 ... 17.503693
49 30821 ... 15.386040
50 30822 ... 8.010992
51 30823 ... 12.374982
52 30824 ... 12.264388
53 30825 ... 6.375187
54 30826 ... 10.301676
55 30827 ... 19.392179
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: o7duvp7g wandb: Agent Starting Run: 52mcezh5 with config: batch_size: 3 forecast_history: 8 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 52mcezh5
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.35429021716118
The number of items in train is:
11
The loss for epoch 0
1.4867536561055616
The running loss is:
16.922948479652405
The number of items in train is:
11
The loss for epoch 1
1.5384498617865823
The running loss is:
17.590839356184006
The number of items in train is:
11
The loss for epoch 2
1.599167214198546
The running loss is:
13.326302886009216
The number of items in train is:
11
The loss for epoch 3
1.2114820805462925
The running loss is:
12.184310719370842
The number of items in train is:
11
The loss for epoch 4
1.1076646108518948
The running loss is:
11.508990198373795
The number of items in train is:
11
The loss for epoch 5
1.0462718362157994
The running loss is:
11.508930832147598
The number of items in train is:
11
The loss for epoch 6
1.0462664392861454
The running loss is:
11.157640248537064
The number of items in train is:
11
The loss for epoch 7
1.0143309316851876
The running loss is:
11.021537959575653
The number of items in train is:
11
The loss for epoch 8
1.0019579963250593
The running loss is:
11.048202827572823
The number of items in train is:
11
The loss for epoch 9
1.004382075233893
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.469040
47 30819 Eagle County, Colorado, United States ... 47 6.957081
48 30820 Eagle County, Colorado, United States ... 48 9.914102
49 30821 Eagle County, Colorado, United States ... 49 7.646966
50 30822 Eagle County, Colorado, United States ... 50 6.059446
51 30823 Eagle County, Colorado, United States ... 51 6.762846
52 30824 Eagle County, Colorado, United States ... 52 6.450365
53 30825 Eagle County, Colorado, United States ... 53 5.381968
54 30826 Eagle County, Colorado, United States ... 54 6.979038
55 30827 Eagle County, Colorado, United States ... 55 7.752284
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 52mcezh5 wandb: Agent Starting Run: a971extu with config: batch_size: 3 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: a971extu
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
62.512909442186356
The number of items in train is:
12
The loss for epoch 0
5.209409120182197
The running loss is:
17.651342948898673
The number of items in train is:
12
The loss for epoch 1
1.4709452457415562
The running loss is:
16.37899762019515
The number of items in train is:
12
The loss for epoch 2
1.3649164683495958
The running loss is:
15.15978118032217
The number of items in train is:
12
The loss for epoch 3
1.2633150983601809
The running loss is:
12.805925235152245
The number of items in train is:
12
The loss for epoch 4
1.067160436262687
The running loss is:
13.833072826266289
The number of items in train is:
12
The loss for epoch 5
1.152756068855524
The running loss is:
12.69072575867176
The number of items in train is:
12
The loss for epoch 6
1.0575604798893135
The running loss is:
11.099541798233986
The number of items in train is:
12
The loss for epoch 7
0.9249618165194988
The running loss is:
14.725254192948341
The number of items in train is:
12
The loss for epoch 8
1.2271045160790284
The running loss is:
13.127574309706688
The number of items in train is:
12
The loss for epoch 9
1.0939645258088906
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.151128
47 30819 ... 10.103148
48 30820 ... 8.635044
49 30821 ... 8.976196
50 30822 ... 11.631431
51 30823 ... 10.928533
52 30824 ... 10.460353
53 30825 ... 9.690262
54 30826 ... 9.819814
55 30827 ... 9.771276
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: a971extu wandb: Agent Starting Run: r5j5ub0k with config: batch_size: 3 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: r5j5ub0k
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
56.22648885846138
The number of items in train is:
11
The loss for epoch 0
5.111498987132853
The running loss is:
16.17362278699875
The number of items in train is:
11
The loss for epoch 1
1.4703293442726135
The running loss is:
12.739032804965973
The number of items in train is:
11
The loss for epoch 2
1.158093891360543
The running loss is:
12.801687873899937
The number of items in train is:
11
The loss for epoch 3
1.163789806718176
The running loss is:
11.013139143586159
The number of items in train is:
11
The loss for epoch 4
1.0011944675987416
The running loss is:
11.208409741520882
The number of items in train is:
11
The loss for epoch 5
1.018946340138262
The running loss is:
11.521547451615334
The number of items in train is:
11
The loss for epoch 6
1.0474134046923032
The running loss is:
12.145481154322624
The number of items in train is:
11
The loss for epoch 7
1.1041346503929659
The running loss is:
11.915283277630806
The number of items in train is:
11
The loss for epoch 8
1.0832075706937097
The running loss is:
10.81276260316372
The number of items in train is:
11
The loss for epoch 9
0.982978418469429
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 8.238698
47 30819 ... 15.917160
48 30820 ... 18.836643
49 30821 ... 15.165972
50 30822 ... 7.579820
51 30823 ... 11.474918
52 30824 ... 10.543474
53 30825 ... 3.774284
54 30826 ... 13.712145
55 30827 ... 21.918915
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r5j5ub0k wandb: Agent Starting Run: auiqco3o with config: batch_size: 3 forecast_history: 8 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: auiqco3o
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 8
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 8
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 8
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 8
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
68.5550007224083
The number of items in train is:
11
The loss for epoch 0
6.232272792946208
The running loss is:
17.13252791762352
The number of items in train is:
11
The loss for epoch 1
1.5575025379657745
The running loss is:
21.412274941802025
The number of items in train is:
11
The loss for epoch 2
1.9465704492547296
The running loss is:
18.478636503219604
The number of items in train is:
11
The loss for epoch 3
1.6798760457472368
The running loss is:
13.234049081802368
The number of items in train is:
11
The loss for epoch 4
1.2030953710729426
The running loss is:
12.859165400266647
The number of items in train is:
11
The loss for epoch 5
1.169015036387877
The running loss is:
12.60863396525383
The number of items in train is:
11
The loss for epoch 6
1.1462394513867118
The running loss is:
11.726247698068619
The number of items in train is:
11
The loss for epoch 7
1.0660225180062382
The running loss is:
11.967080354690552
The number of items in train is:
11
The loss for epoch 8
1.0879163958809592
The running loss is:
11.622294649481773
The number of items in train is:
11
The loss for epoch 9
1.0565722408619793
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 8, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 11.041265
47 30819 ... 11.052490
48 30820 ... 11.052483
49 30821 ... 11.052554
50 30822 ... 11.196361
51 30823 ... 11.056916
52 30824 ... 11.044400
53 30825 ... 11.057491
54 30826 ... 11.101706
55 30827 ... 11.101956
[18 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: auiqco3o wandb: Agent Starting Run: somsettb with config: batch_size: 3 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: somsettb
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.22938135266304
The number of items in train is:
11
The loss for epoch 0
1.2935801229693673
The running loss is:
19.941050857305527
The number of items in train is:
11
The loss for epoch 1
1.8128228052095934
The running loss is:
11.153500378131866
The number of items in train is:
11
The loss for epoch 2
1.0139545798301697
The running loss is:
11.50929357111454
The number of items in train is:
11
The loss for epoch 3
1.0462994155558674
The running loss is:
10.824358247220516
The number of items in train is:
11
The loss for epoch 4
0.9840325679291378
The running loss is:
10.066967114806175
The number of items in train is:
11
The loss for epoch 5
0.9151788286187432
The running loss is:
10.130360662937164
The number of items in train is:
11
The loss for epoch 6
0.9209418784488331
The running loss is:
9.796619072556496
The number of items in train is:
11
The loss for epoch 7
0.8906017338687723
The running loss is:
9.525743946433067
The number of items in train is:
11
The loss for epoch 8
0.8659767224030062
The running loss is:
9.004187449812889
The number of items in train is:
11
The loss for epoch 9
0.8185624954375353
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 1.641901
47 30819 Eagle County, Colorado, United States ... 47 0.659750
48 30820 Eagle County, Colorado, United States ... 48 0.145355
49 30821 Eagle County, Colorado, United States ... 49 -1.664633
50 30822 Eagle County, Colorado, United States ... 50 -3.271421
51 30823 Eagle County, Colorado, United States ... 51 -3.226503
52 30824 Eagle County, Colorado, United States ... 52 -4.404780
53 30825 Eagle County, Colorado, United States ... 53 -4.431837
54 30826 Eagle County, Colorado, United States ... 54 -3.693761
55 30827 Eagle County, Colorado, United States ... 55 -5.035707
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: somsettb wandb: Agent Starting Run: ahdp4ztj with config: batch_size: 3 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: ahdp4ztj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.904565572738647
The number of items in train is:
11
The loss for epoch 0
1.2640514157035134
The running loss is:
14.439204514026642
The number of items in train is:
11
The loss for epoch 1
1.3126549558206038
The running loss is:
11.414902299642563
The number of items in train is:
11
The loss for epoch 2
1.0377183908765966
The running loss is:
11.388078331947327
The number of items in train is:
11
The loss for epoch 3
1.035279848358848
The running loss is:
10.855302773416042
The number of items in train is:
11
The loss for epoch 4
0.9868457066741857
The running loss is:
10.968083716928959
The number of items in train is:
11
The loss for epoch 5
0.9970985197208144
The running loss is:
10.221406817436218
The number of items in train is:
11
The loss for epoch 6
0.9292188015851107
The running loss is:
10.399505764245987
The number of items in train is:
11
The loss for epoch 7
0.9454096149314534
The running loss is:
9.819108434021473
The number of items in train is:
11
The loss for epoch 8
0.8926462212746794
The running loss is:
10.10106372833252
The number of items in train is:
11
The loss for epoch 9
0.9182785207575018
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.993636
47 30819 Eagle County, Colorado, United States ... 47 0.337607
48 30820 Eagle County, Colorado, United States ... 48 -0.410252
49 30821 Eagle County, Colorado, United States ... 49 -2.278395
50 30822 Eagle County, Colorado, United States ... 50 -3.970787
51 30823 Eagle County, Colorado, United States ... 51 -4.415275
52 30824 Eagle County, Colorado, United States ... 52 -5.037481
53 30825 Eagle County, Colorado, United States ... 53 -4.421631
54 30826 Eagle County, Colorado, United States ... 54 -4.119612
55 30827 Eagle County, Colorado, United States ... 55 -5.898763
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ahdp4ztj wandb: Agent Starting Run: x81o8l78 with config: batch_size: 3 forecast_history: 9 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: x81o8l78
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.101940542459488
The number of items in train is:
11
The loss for epoch 0
1.3729036856781354
The running loss is:
23.97471283376217
The number of items in train is:
11
The loss for epoch 1
2.1795193485238333
The running loss is:
11.563013285398483
The number of items in train is:
11
The loss for epoch 2
1.0511830259453168
The running loss is:
11.633486792445183
The number of items in train is:
11
The loss for epoch 3
1.0575897084041075
The running loss is:
11.537669107317924
The number of items in train is:
11
The loss for epoch 4
1.0488790097561749
The running loss is:
10.989692643284798
The number of items in train is:
11
The loss for epoch 5
0.9990629675713453
The running loss is:
10.99491299688816
The number of items in train is:
11
The loss for epoch 6
0.9995375451716509
The running loss is:
10.651772901415825
The number of items in train is:
11
The loss for epoch 7
0.9683429910378023
The running loss is:
10.3761787712574
The number of items in train is:
11
The loss for epoch 8
0.9432889792052183
The running loss is:
10.486194789409637
The number of items in train is:
11
The loss for epoch 9
0.9532904354008761
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.549189
47 30819 Eagle County, Colorado, United States ... 47 5.238999
48 30820 Eagle County, Colorado, United States ... 48 5.157782
49 30821 Eagle County, Colorado, United States ... 49 4.296832
50 30822 Eagle County, Colorado, United States ... 50 3.588796
51 30823 Eagle County, Colorado, United States ... 51 3.961380
52 30824 Eagle County, Colorado, United States ... 52 3.981963
53 30825 Eagle County, Colorado, United States ... 53 4.519014
54 30826 Eagle County, Colorado, United States ... 54 5.010921
55 30827 Eagle County, Colorado, United States ... 55 4.995728
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: x81o8l78 wandb: Agent Starting Run: a8gs6fcn with config: batch_size: 3 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: a8gs6fcn
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.293268650770187
The number of items in train is:
11
The loss for epoch 0
1.2993880591609261
The running loss is:
25.236984327435493
The number of items in train is:
11
The loss for epoch 1
2.2942713024941357
The running loss is:
15.248826995491982
The number of items in train is:
11
The loss for epoch 2
1.3862569995901801
The running loss is:
13.369037687778473
The number of items in train is:
11
The loss for epoch 3
1.2153670625253157
The running loss is:
11.280201107263565
The number of items in train is:
11
The loss for epoch 4
1.0254728279330514
The running loss is:
10.680228557437658
The number of items in train is:
11
The loss for epoch 5
0.970929868857969
The running loss is:
10.887261852622032
The number of items in train is:
11
The loss for epoch 6
0.9897510775110938
The running loss is:
10.184634555131197
The number of items in train is:
11
The loss for epoch 7
0.9258758686482906
The running loss is:
10.048418715596199
The number of items in train is:
11
The loss for epoch 8
0.9134926105087454
The running loss is:
9.457138307392597
The number of items in train is:
11
The loss for epoch 9
0.8597398461265997
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.523421
47 30819 Eagle County, Colorado, United States ... 47 5.732596
48 30820 Eagle County, Colorado, United States ... 48 5.351936
49 30821 Eagle County, Colorado, United States ... 49 4.316126
50 30822 Eagle County, Colorado, United States ... 50 3.560244
51 30823 Eagle County, Colorado, United States ... 51 4.253401
52 30824 Eagle County, Colorado, United States ... 52 3.771999
53 30825 Eagle County, Colorado, United States ... 53 3.702273
54 30826 Eagle County, Colorado, United States ... 54 4.884375
55 30827 Eagle County, Colorado, United States ... 55 4.741635
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: a8gs6fcn wandb: Agent Starting Run: vu8mseek with config: batch_size: 3 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: vu8mseek
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.480009138584137
The number of items in train is:
11
The loss for epoch 0
1.2254553762349216
The running loss is:
18.653071716427803
The number of items in train is:
11
The loss for epoch 1
1.6957337924025275
The running loss is:
12.810831904411316
The number of items in train is:
11
The loss for epoch 2
1.1646210822192105
The running loss is:
12.394441686570644
The number of items in train is:
11
The loss for epoch 3
1.1267674260518767
The running loss is:
11.051628254354
The number of items in train is:
11
The loss for epoch 4
1.0046934776685454
The running loss is:
11.096481785178185
The number of items in train is:
11
The loss for epoch 5
1.008771071379835
The running loss is:
10.40086854994297
The number of items in train is:
11
The loss for epoch 6
0.9455335045402701
The running loss is:
10.105966605246067
The number of items in train is:
11
The loss for epoch 7
0.9187242368405516
The running loss is:
9.457882694900036
The number of items in train is:
11
The loss for epoch 8
0.8598075177181851
The running loss is:
9.17867822945118
The number of items in train is:
11
The loss for epoch 9
0.8344252935864709
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 0.126443
47 30819 Eagle County, Colorado, United States ... 47 1.472562
48 30820 Eagle County, Colorado, United States ... 48 0.837418
49 30821 Eagle County, Colorado, United States ... 49 -0.418314
50 30822 Eagle County, Colorado, United States ... 50 -1.061832
51 30823 Eagle County, Colorado, United States ... 51 -0.909486
52 30824 Eagle County, Colorado, United States ... 52 -1.210210
53 30825 Eagle County, Colorado, United States ... 53 -1.402265
54 30826 Eagle County, Colorado, United States ... 54 -1.178178
55 30827 Eagle County, Colorado, United States ... 55 -2.296195
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: vu8mseek wandb: Agent Starting Run: ypnfalp7 with config: batch_size: 3 forecast_history: 9 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: ypnfalp7
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.256483346223831
The number of items in train is:
11
The loss for epoch 0
1.3869530314748937
The running loss is:
20.161068454384804
The number of items in train is:
11
The loss for epoch 1
1.8328244049440732
The running loss is:
21.77994852513075
The number of items in train is:
11
The loss for epoch 2
1.9799953204664318
The running loss is:
14.009808540344238
The number of items in train is:
11
The loss for epoch 3
1.2736189582131126
The running loss is:
11.812053754925728
The number of items in train is:
11
The loss for epoch 4
1.0738230686296115
The running loss is:
11.489768326282501
The number of items in train is:
11
The loss for epoch 5
1.0445243932984092
The running loss is:
11.18503075838089
The number of items in train is:
11
The loss for epoch 6
1.0168209780346265
The running loss is:
10.996993936598301
The number of items in train is:
11
The loss for epoch 7
0.9997267215089365
The running loss is:
10.645965211093426
The number of items in train is:
11
The loss for epoch 8
0.9678150191903114
The running loss is:
10.70228710025549
The number of items in train is:
11
The loss for epoch 9
0.9729351909323172
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.941140
47 30819 Eagle County, Colorado, United States ... 47 5.203240
48 30820 Eagle County, Colorado, United States ... 48 5.400292
49 30821 Eagle County, Colorado, United States ... 49 5.070734
50 30822 Eagle County, Colorado, United States ... 50 4.472741
51 30823 Eagle County, Colorado, United States ... 51 4.626699
52 30824 Eagle County, Colorado, United States ... 52 4.676058
53 30825 Eagle County, Colorado, United States ... 53 4.822545
54 30826 Eagle County, Colorado, United States ... 54 4.917575
55 30827 Eagle County, Colorado, United States ... 55 5.222575
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: ypnfalp7 wandb: Agent Starting Run: fhuyeb8k with config: batch_size: 3 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: fhuyeb8k
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.009724855422974
The number of items in train is:
11
The loss for epoch 0
1.819065895947543
The running loss is:
17.003920286893845
The number of items in train is:
11
The loss for epoch 1
1.5458109351721676
The running loss is:
24.95011392235756
The number of items in train is:
11
The loss for epoch 2
2.268192174759778
The running loss is:
14.320160880684853
The number of items in train is:
11
The loss for epoch 3
1.3018328073349865
The running loss is:
13.634816728532314
The number of items in train is:
11
The loss for epoch 4
1.2395287935029378
The running loss is:
11.614453293383121
The number of items in train is:
11
The loss for epoch 5
1.0558593903075566
The running loss is:
10.36690553277731
The number of items in train is:
11
The loss for epoch 6
0.94244595752521
The running loss is:
11.941105760633945
The number of items in train is:
11
The loss for epoch 7
1.0855550691485405
The running loss is:
11.603152967989445
The number of items in train is:
11
The loss for epoch 8
1.0548320879990405
The running loss is:
10.878066308796406
The number of items in train is:
11
The loss for epoch 9
0.9889151189814914
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.755946
47 30819 Eagle County, Colorado, United States ... 47 3.948533
48 30820 Eagle County, Colorado, United States ... 48 4.109846
49 30821 Eagle County, Colorado, United States ... 49 3.798323
50 30822 Eagle County, Colorado, United States ... 50 3.180298
51 30823 Eagle County, Colorado, United States ... 51 3.435037
52 30824 Eagle County, Colorado, United States ... 52 3.290437
53 30825 Eagle County, Colorado, United States ... 53 3.229304
54 30826 Eagle County, Colorado, United States ... 54 3.526299
55 30827 Eagle County, Colorado, United States ... 55 3.496862
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fhuyeb8k wandb: Agent Starting Run: o12nxwrs with config: batch_size: 3 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: o12nxwrs
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.3218465000391
The number of items in train is:
11
The loss for epoch 0
1.483804227276282
The running loss is:
15.315989192575216
The number of items in train is:
11
The loss for epoch 1
1.3923626538704743
The running loss is:
14.728986725211143
The number of items in train is:
11
The loss for epoch 2
1.338998793201013
The running loss is:
11.862384408712387
The number of items in train is:
11
The loss for epoch 3
1.078398582610217
The running loss is:
11.441317409276962
The number of items in train is:
11
The loss for epoch 4
1.0401197644797238
The running loss is:
11.3860694617033
The number of items in train is:
11
The loss for epoch 5
1.035097223791209
The running loss is:
10.910162702202797
The number of items in train is:
11
The loss for epoch 6
0.991832972927527
The running loss is:
10.58010609447956
The number of items in train is:
11
The loss for epoch 7
0.9618278267708692
The running loss is:
10.980321384966373
The number of items in train is:
11
The loss for epoch 8
0.9982110349969431
The running loss is:
10.795635655522346
The number of items in train is:
11
The loss for epoch 9
0.9814214232293043
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.697867
47 30819 Eagle County, Colorado, United States ... 47 6.948792
48 30820 Eagle County, Colorado, United States ... 48 7.443105
49 30821 Eagle County, Colorado, United States ... 49 7.463962
50 30822 Eagle County, Colorado, United States ... 50 6.714512
51 30823 Eagle County, Colorado, United States ... 51 6.026889
52 30824 Eagle County, Colorado, United States ... 52 6.382638
53 30825 Eagle County, Colorado, United States ... 53 7.221634
54 30826 Eagle County, Colorado, United States ... 54 7.065754
55 30827 Eagle County, Colorado, United States ... 55 7.099236
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: o12nxwrs wandb: Agent Starting Run: xvue9u7r with config: batch_size: 3 forecast_history: 9 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: xvue9u7r
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
23.463824197649956
The number of items in train is:
11
The loss for epoch 0
2.133074927059087
The running loss is:
15.782015278935432
The number of items in train is:
11
The loss for epoch 1
1.434728661721403
The running loss is:
18.047666788101196
The number of items in train is:
11
The loss for epoch 2
1.6406969807364724
The running loss is:
15.659799247980118
The number of items in train is:
11
The loss for epoch 3
1.423618113452738
The running loss is:
12.579364575445652
The number of items in train is:
11
The loss for epoch 4
1.1435785977677866
The running loss is:
11.840390399098396
The number of items in train is:
11
The loss for epoch 5
1.0763991271907634
The running loss is:
11.462177857756615
The number of items in train is:
11
The loss for epoch 6
1.042016168886965
The running loss is:
11.036812007427216
The number of items in train is:
11
The loss for epoch 7
1.0033465461297468
The running loss is:
11.114317834377289
The number of items in train is:
11
The loss for epoch 8
1.0103925303979353
The running loss is:
10.485807582736015
The number of items in train is:
11
The loss for epoch 9
0.9532552347941832
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.167429
47 30819 Eagle County, Colorado, United States ... 47 5.274903
48 30820 Eagle County, Colorado, United States ... 48 5.347121
49 30821 Eagle County, Colorado, United States ... 49 5.224376
50 30822 Eagle County, Colorado, United States ... 50 4.545171
51 30823 Eagle County, Colorado, United States ... 51 4.629979
52 30824 Eagle County, Colorado, United States ... 52 4.639435
53 30825 Eagle County, Colorado, United States ... 53 4.866332
54 30826 Eagle County, Colorado, United States ... 54 4.865740
55 30827 Eagle County, Colorado, United States ... 55 5.358328
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xvue9u7r wandb: Agent Starting Run: 3k2gj89q with config: batch_size: 3 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 3k2gj89q
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
90.29608756303787
The number of items in train is:
11
The loss for epoch 0
8.208735233003443
The running loss is:
16.856530398130417
The number of items in train is:
11
The loss for epoch 1
1.5324118543754925
The running loss is:
21.56619629263878
The number of items in train is:
11
The loss for epoch 2
1.960563299330798
The running loss is:
15.163192972540855
The number of items in train is:
11
The loss for epoch 3
1.378472088412805
The running loss is:
16.831146404147148
The number of items in train is:
11
The loss for epoch 4
1.5301042185588316
The running loss is:
13.869851365685463
The number of items in train is:
11
The loss for epoch 5
1.2608955786986784
The running loss is:
14.04520610626787
The number of items in train is:
11
The loss for epoch 6
1.2768369187516244
The running loss is:
12.467475153505802
The number of items in train is:
11
The loss for epoch 7
1.133406832136891
The running loss is:
11.837162591516972
The number of items in train is:
11
The loss for epoch 8
1.0761056901379065
The running loss is:
11.645600214600563
The number of items in train is:
11
The loss for epoch 9
1.0586909286000512
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 12.232118
47 30819 ... 11.285740
48 30820 ... 11.412394
49 30821 ... 11.406689
50 30822 ... 11.396914
51 30823 ... 11.609783
52 30824 ... 11.633080
53 30825 ... 11.424625
54 30826 ... 11.864182
55 30827 ... 11.468259
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 3k2gj89q wandb: Agent Starting Run: 1tgk2elj with config: batch_size: 3 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: 1tgk2elj
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
59.00660365819931
The number of items in train is:
11
The loss for epoch 0
5.364236696199938
The running loss is:
14.09033265709877
The number of items in train is:
11
The loss for epoch 1
1.2809393324635245
The running loss is:
13.665505439043045
The number of items in train is:
11
The loss for epoch 2
1.2423186762766405
The running loss is:
15.05822366476059
The number of items in train is:
11
The loss for epoch 3
1.3689294240691445
The running loss is:
13.959211483597755
The number of items in train is:
11
The loss for epoch 4
1.2690192257816142
The running loss is:
12.256061419844627
The number of items in train is:
11
The loss for epoch 5
1.114187401804057
The running loss is:
12.423433378338814
The number of items in train is:
11
The loss for epoch 6
1.1294030343944377
The running loss is:
12.089040637016296
The number of items in train is:
11
The loss for epoch 7
1.0990036942742087
The running loss is:
12.20865024626255
The number of items in train is:
11
The loss for epoch 8
1.1098772951147773
The running loss is:
12.115084633231163
The number of items in train is:
11
The loss for epoch 9
1.101371330293742
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.465091
47 30819 Eagle County, Colorado, United States ... 47 9.144346
48 30820 Eagle County, Colorado, United States ... 48 9.144058
49 30821 Eagle County, Colorado, United States ... 49 8.759192
50 30822 Eagle County, Colorado, United States ... 50 8.681924
51 30823 Eagle County, Colorado, United States ... 51 8.518374
52 30824 Eagle County, Colorado, United States ... 52 8.642056
53 30825 Eagle County, Colorado, United States ... 53 8.642455
54 30826 Eagle County, Colorado, United States ... 54 8.403084
55 30827 Eagle County, Colorado, United States ... 55 9.770735
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 1tgk2elj wandb: Agent Starting Run: u0l4gkbl with config: batch_size: 3 forecast_history: 9 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: u0l4gkbl
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 9
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 9
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 9
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 9
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
88.96907395124435
The number of items in train is:
11
The loss for epoch 0
8.088097631931305
The running loss is:
28.60553839802742
The number of items in train is:
11
The loss for epoch 1
2.6005034907297655
The running loss is:
36.84468446671963
The number of items in train is:
11
The loss for epoch 2
3.3495167697017845
The running loss is:
12.81296344101429
The number of items in train is:
11
The loss for epoch 3
1.1648148582740263
The running loss is:
12.78886991739273
The number of items in train is:
11
The loss for epoch 4
1.1626245379447937
The running loss is:
12.014240890741348
The number of items in train is:
11
The loss for epoch 5
1.0922037173401227
The running loss is:
11.263784617185593
The number of items in train is:
11
The loss for epoch 6
1.0239804197441449
The running loss is:
11.543391533195972
The number of items in train is:
11
The loss for epoch 7
1.049399230290543
The running loss is:
11.280034869909286
The number of items in train is:
11
The loss for epoch 8
1.0254577154462987
The running loss is:
11.284744039177895
The number of items in train is:
11
The loss for epoch 9
1.025885821743445
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 9, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 8.673812
47 30819 Eagle County, Colorado, United States ... 47 7.985293
48 30820 Eagle County, Colorado, United States ... 48 8.133834
49 30821 Eagle County, Colorado, United States ... 49 7.933124
50 30822 Eagle County, Colorado, United States ... 50 7.829472
51 30823 Eagle County, Colorado, United States ... 51 7.938765
52 30824 Eagle County, Colorado, United States ... 52 7.902779
53 30825 Eagle County, Colorado, United States ... 53 8.302330
54 30826 Eagle County, Colorado, United States ... 54 8.484731
55 30827 Eagle County, Colorado, United States ... 55 8.491733
[19 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: u0l4gkbl wandb: Agent Starting Run: l929ks1j with config: batch_size: 3 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: l929ks1j
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.92371991276741
The number of items in train is:
11
The loss for epoch 0
1.3567018102515827
The running loss is:
16.43264576792717
The number of items in train is:
11
The loss for epoch 1
1.493876887993379
The running loss is:
11.552073381841183
The number of items in train is:
11
The loss for epoch 2
1.0501884892582893
The running loss is:
11.72037386894226
The number of items in train is:
11
The loss for epoch 3
1.0654885335402056
The running loss is:
11.173139587044716
The number of items in train is:
11
The loss for epoch 4
1.0157399624586105
The running loss is:
10.70702352002263
The number of items in train is:
11
The loss for epoch 5
0.9733657745475118
The running loss is:
10.8629803173244
The number of items in train is:
11
The loss for epoch 6
0.9875436652113091
The running loss is:
10.56940308585763
The number of items in train is:
11
The loss for epoch 7
0.9608548259870573
The running loss is:
10.278399351984262
The number of items in train is:
11
The loss for epoch 8
0.9343999410894784
The running loss is:
9.92225181683898
The number of items in train is:
11
The loss for epoch 9
0.9020228924399073
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.548505
47 30819 Eagle County, Colorado, United States ... 47 6.799479
48 30820 Eagle County, Colorado, United States ... 48 7.248922
49 30821 Eagle County, Colorado, United States ... 49 6.497251
50 30822 Eagle County, Colorado, United States ... 50 5.649336
51 30823 Eagle County, Colorado, United States ... 51 4.337851
52 30824 Eagle County, Colorado, United States ... 52 3.793358
53 30825 Eagle County, Colorado, United States ... 53 4.435680
54 30826 Eagle County, Colorado, United States ... 54 5.779097
55 30827 Eagle County, Colorado, United States ... 55 6.433308
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l929ks1j wandb: Agent Starting Run: uz1ls2ow with config: batch_size: 3 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: uz1ls2ow
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.075268387794495
The number of items in train is:
11
The loss for epoch 0
1.370478944344954
The running loss is:
18.250104278326035
The number of items in train is:
11
The loss for epoch 1
1.6591003889387304
The running loss is:
11.863716915249825
The number of items in train is:
11
The loss for epoch 2
1.078519719568166
The running loss is:
11.809837684035301
The number of items in train is:
11
The loss for epoch 3
1.0736216076395728
The running loss is:
11.555817887187004
The number of items in train is:
11
The loss for epoch 4
1.0505288988351822
The running loss is:
11.156246989965439
The number of items in train is:
11
The loss for epoch 5
1.01420427181504
The running loss is:
11.147064179182053
The number of items in train is:
11
The loss for epoch 6
1.013369470834732
The running loss is:
10.738830104470253
The number of items in train is:
11
The loss for epoch 7
0.9762572822245684
The running loss is:
10.667878225445747
The number of items in train is:
11
The loss for epoch 8
0.9698071114041589
The running loss is:
10.60825464129448
The number of items in train is:
11
The loss for epoch 9
0.9643867855722253
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 4.673477
47 30819 Eagle County, Colorado, United States ... 47 5.280448
48 30820 Eagle County, Colorado, United States ... 48 6.011500
49 30821 Eagle County, Colorado, United States ... 49 4.960355
50 30822 Eagle County, Colorado, United States ... 50 3.920301
51 30823 Eagle County, Colorado, United States ... 51 2.750020
52 30824 Eagle County, Colorado, United States ... 52 2.592566
53 30825 Eagle County, Colorado, United States ... 53 2.902614
54 30826 Eagle County, Colorado, United States ... 54 3.555806
55 30827 Eagle County, Colorado, United States ... 55 4.717776
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: uz1ls2ow wandb: Agent Starting Run: 54fe3ak1 with config: batch_size: 3 forecast_history: 10 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 54fe3ak1
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
13.83226963877678
The number of items in train is:
10
The loss for epoch 0
1.383226963877678
The running loss is:
15.266054153442383
The number of items in train is:
10
The loss for epoch 1
1.5266054153442383
The running loss is:
11.117882281541824
The number of items in train is:
10
The loss for epoch 2
1.1117882281541824
The running loss is:
11.215152770280838
The number of items in train is:
10
The loss for epoch 3
1.1215152770280838
The running loss is:
10.989554300904274
The number of items in train is:
10
The loss for epoch 4
1.0989554300904274
The running loss is:
10.816273152828217
The number of items in train is:
10
The loss for epoch 5
1.0816273152828217
The running loss is:
10.548416331410408
The number of items in train is:
10
The loss for epoch 6
1.0548416331410408
The running loss is:
10.31107048690319
The number of items in train is:
10
The loss for epoch 7
1.031107048690319
The running loss is:
10.179565638303757
The number of items in train is:
10
The loss for epoch 8
1.0179565638303756
The running loss is:
9.991168916225433
The number of items in train is:
10
The loss for epoch 9
0.9991168916225434
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.514035
47 30819 Eagle County, Colorado, United States ... 47 7.254191
48 30820 Eagle County, Colorado, United States ... 48 6.290533
49 30821 Eagle County, Colorado, United States ... 49 6.119982
50 30822 Eagle County, Colorado, United States ... 50 6.080837
51 30823 Eagle County, Colorado, United States ... 51 4.723925
52 30824 Eagle County, Colorado, United States ... 52 3.630096
53 30825 Eagle County, Colorado, United States ... 53 4.117791
54 30826 Eagle County, Colorado, United States ... 54 5.901507
55 30827 Eagle County, Colorado, United States ... 55 5.877332
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 54fe3ak1 wandb: Agent Starting Run: xlo78q8b with config: batch_size: 3 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: xlo78q8b
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.106579810380936
The number of items in train is:
11
The loss for epoch 0
1.3733254373073578
The running loss is:
22.456708751618862
The number of items in train is:
11
The loss for epoch 1
2.0415189774198965
The running loss is:
14.402357146143913
The number of items in train is:
11
The loss for epoch 2
1.309305195103992
The running loss is:
13.298728570342064
The number of items in train is:
11
The loss for epoch 3
1.2089753245765513
The running loss is:
11.133810125291348
The number of items in train is:
11
The loss for epoch 4
1.012164556844668
The running loss is:
11.0093739554286
The number of items in train is:
11
The loss for epoch 5
1.0008521777662365
The running loss is:
10.6600153259933
The number of items in train is:
11
The loss for epoch 6
0.9690923023630272
The running loss is:
10.412130199372768
The number of items in train is:
11
The loss for epoch 7
0.9465572908520699
The running loss is:
10.362909991294146
The number of items in train is:
11
The loss for epoch 8
0.942082726481286
The running loss is:
10.477576583623886
The number of items in train is:
11
The loss for epoch 9
0.952506962147626
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 7.556224
47 30819 Eagle County, Colorado, United States ... 47 8.307045
48 30820 Eagle County, Colorado, United States ... 48 8.447693
49 30821 Eagle County, Colorado, United States ... 49 8.431895
50 30822 Eagle County, Colorado, United States ... 50 8.247824
51 30823 Eagle County, Colorado, United States ... 51 7.643862
52 30824 Eagle County, Colorado, United States ... 52 7.295239
53 30825 Eagle County, Colorado, United States ... 53 7.528549
54 30826 Eagle County, Colorado, United States ... 54 8.345770
55 30827 Eagle County, Colorado, United States ... 55 8.461617
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: xlo78q8b wandb: Agent Starting Run: l9ce7gon with config: batch_size: 3 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: l9ce7gon
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.394998997449875
The number of items in train is:
11
The loss for epoch 0
1.399545363404534
The running loss is:
23.997811377048492
The number of items in train is:
11
The loss for epoch 1
2.1816192160953176
The running loss is:
14.285172209143639
The number of items in train is:
11
The loss for epoch 2
1.2986520190130582
The running loss is:
12.942523777484894
The number of items in train is:
11
The loss for epoch 3
1.1765930706804448
The running loss is:
11.262697920203209
The number of items in train is:
11
The loss for epoch 4
1.0238816291093826
The running loss is:
11.160549372434616
The number of items in train is:
11
The loss for epoch 5
1.014595397494056
The running loss is:
11.12978708744049
The number of items in train is:
11
The loss for epoch 6
1.0117988261309536
The running loss is:
10.566879317164421
The number of items in train is:
11
The loss for epoch 7
0.9606253924694929
The running loss is:
10.78386503458023
The number of items in train is:
11
The loss for epoch 8
0.980351366780021
The running loss is:
10.294064745306969
The number of items in train is:
11
The loss for epoch 9
0.935824067755179
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.395967
47 30819 Eagle County, Colorado, United States ... 47 5.880879
48 30820 Eagle County, Colorado, United States ... 48 6.679946
49 30821 Eagle County, Colorado, United States ... 49 5.419914
50 30822 Eagle County, Colorado, United States ... 50 4.428827
51 30823 Eagle County, Colorado, United States ... 51 3.509271
52 30824 Eagle County, Colorado, United States ... 52 4.432165
53 30825 Eagle County, Colorado, United States ... 53 4.058541
54 30826 Eagle County, Colorado, United States ... 54 4.401000
55 30827 Eagle County, Colorado, United States ... 55 5.193408
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: l9ce7gon wandb: Agent Starting Run: r358t16w with config: batch_size: 3 forecast_history: 10 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: r358t16w
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.527101278305054
The number of items in train is:
10
The loss for epoch 0
1.4527101278305055
The running loss is:
22.141034603118896
The number of items in train is:
10
The loss for epoch 1
2.2141034603118896
The running loss is:
12.012695848941803
The number of items in train is:
10
The loss for epoch 2
1.2012695848941803
The running loss is:
12.097595125436783
The number of items in train is:
10
The loss for epoch 3
1.2097595125436782
The running loss is:
11.048981189727783
The number of items in train is:
10
The loss for epoch 4
1.1048981189727782
The running loss is:
11.015377283096313
The number of items in train is:
10
The loss for epoch 5
1.1015377283096313
The running loss is:
10.59331339597702
The number of items in train is:
10
The loss for epoch 6
1.059331339597702
The running loss is:
10.057495325803757
The number of items in train is:
10
The loss for epoch 7
1.0057495325803756
The running loss is:
9.739617317914963
The number of items in train is:
10
The loss for epoch 8
0.9739617317914963
The running loss is:
9.51185992360115
The number of items in train is:
10
The loss for epoch 9
0.951185992360115
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 3.109675
47 30819 Eagle County, Colorado, United States ... 47 7.202462
48 30820 Eagle County, Colorado, United States ... 48 6.471476
49 30821 Eagle County, Colorado, United States ... 49 6.885487
50 30822 Eagle County, Colorado, United States ... 50 8.134160
51 30823 Eagle County, Colorado, United States ... 51 5.623744
52 30824 Eagle County, Colorado, United States ... 52 2.716154
53 30825 Eagle County, Colorado, United States ... 53 2.542940
54 30826 Eagle County, Colorado, United States ... 54 5.271421
55 30827 Eagle County, Colorado, United States ... 55 3.604456
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: r358t16w wandb: Agent Starting Run: 0n7rpkqi with config: batch_size: 3 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: 0n7rpkqi
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
20.287513837218285
The number of items in train is:
11
The loss for epoch 0
1.8443194397471168
The running loss is:
17.763389602303505
The number of items in train is:
11
The loss for epoch 1
1.6148536002094096
The running loss is:
18.308134004473686
The number of items in train is:
11
The loss for epoch 2
1.664375818588517
The running loss is:
13.646052297204733
The number of items in train is:
11
The loss for epoch 3
1.240550208836794
The running loss is:
11.77882007136941
The number of items in train is:
11
The loss for epoch 4
1.0708018246699462
The running loss is:
11.554875448346138
The number of items in train is:
11
The loss for epoch 5
1.0504432225769216
The running loss is:
10.891038347035646
The number of items in train is:
11
The loss for epoch 6
0.9900943951850588
The running loss is:
10.527192924171686
The number of items in train is:
11
The loss for epoch 7
0.9570175385610624
The running loss is:
10.677618101239204
The number of items in train is:
11
The loss for epoch 8
0.9706925546581094
The running loss is:
9.92277317494154
The number of items in train is:
11
The loss for epoch 9
0.9020702886310491
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.662254
47 30819 Eagle County, Colorado, United States ... 47 8.584000
48 30820 Eagle County, Colorado, United States ... 48 8.154727
49 30821 Eagle County, Colorado, United States ... 49 7.953487
50 30822 Eagle County, Colorado, United States ... 50 9.607455
51 30823 Eagle County, Colorado, United States ... 51 7.888170
52 30824 Eagle County, Colorado, United States ... 52 4.632975
53 30825 Eagle County, Colorado, United States ... 53 4.524205
54 30826 Eagle County, Colorado, United States ... 54 7.611029
55 30827 Eagle County, Colorado, United States ... 55 6.325020
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 0n7rpkqi wandb: Agent Starting Run: sm1667zy with config: batch_size: 3 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: sm1667zy
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
21.04368895292282
The number of items in train is:
11
The loss for epoch 0
1.9130626320838928
The running loss is:
17.420522198081017
The number of items in train is:
11
The loss for epoch 1
1.5836838361891834
The running loss is:
18.03695920109749
The number of items in train is:
11
The loss for epoch 2
1.6397235637361354
The running loss is:
12.567854255437851
The number of items in train is:
11
The loss for epoch 3
1.1425322050398046
The running loss is:
11.904003366827965
The number of items in train is:
11
The loss for epoch 4
1.0821821242570877
The running loss is:
11.364094316959381
The number of items in train is:
11
The loss for epoch 5
1.0330994833599438
The running loss is:
11.217663764953613
The number of items in train is:
11
The loss for epoch 6
1.019787614995783
The running loss is:
10.618583157658577
The number of items in train is:
11
The loss for epoch 7
0.9653257416053251
The running loss is:
10.280679374933243
The number of items in train is:
11
The loss for epoch 8
0.9346072159030221
The running loss is:
10.05563603155315
The number of items in train is:
11
The loss for epoch 9
0.9141487301411954
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 5.821763
47 30819 Eagle County, Colorado, United States ... 47 7.734202
48 30820 Eagle County, Colorado, United States ... 48 7.385605
49 30821 Eagle County, Colorado, United States ... 49 6.645911
50 30822 Eagle County, Colorado, United States ... 50 5.434975
51 30823 Eagle County, Colorado, United States ... 51 4.449950
52 30824 Eagle County, Colorado, United States ... 52 4.956104
53 30825 Eagle County, Colorado, United States ... 53 4.387439
54 30826 Eagle County, Colorado, United States ... 54 4.889442
55 30827 Eagle County, Colorado, United States ... 55 4.947524
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: sm1667zy wandb: Agent Starting Run: fxx2bd2s with config: batch_size: 3 forecast_history: 10 lr: 0.004 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: fxx2bd2s
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.389306485652924
The number of items in train is:
10
The loss for epoch 0
1.7389306485652924
The running loss is:
17.50364814698696
The number of items in train is:
10
The loss for epoch 1
1.750364814698696
The running loss is:
12.744259268045425
The number of items in train is:
10
The loss for epoch 2
1.2744259268045426
The running loss is:
11.429000854492188
The number of items in train is:
10
The loss for epoch 3
1.1429000854492188
The running loss is:
11.428666561841965
The number of items in train is:
10
The loss for epoch 4
1.1428666561841965
The running loss is:
11.07622879743576
The number of items in train is:
10
The loss for epoch 5
1.107622879743576
The running loss is:
10.732758343219757
The number of items in train is:
10
The loss for epoch 6
1.0732758343219757
The running loss is:
10.29849573969841
The number of items in train is:
10
The loss for epoch 7
1.029849573969841
The running loss is:
9.432255893945694
The number of items in train is:
10
The loss for epoch 8
0.9432255893945694
The running loss is:
10.343920201063156
The number of items in train is:
10
The loss for epoch 9
1.0343920201063157
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 3.357261
47 30819 ... 10.925328
48 30820 ... 7.806000
49 30821 ... 7.145774
50 30822 ... 8.982411
51 30823 ... 6.517039
52 30824 ... 1.144588
53 30825 ... 2.173529
54 30826 ... 7.736863
55 30827 ... 6.227529
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fxx2bd2s wandb: Agent Starting Run: w6g5blue with config: batch_size: 3 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: w6g5blue
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
90.27539926767349
The number of items in train is:
11
The loss for epoch 0
8.206854478879409
The running loss is:
17.084474243223667
The number of items in train is:
11
The loss for epoch 1
1.5531340221112424
The running loss is:
31.057914689183235
The number of items in train is:
11
The loss for epoch 2
2.8234467899257485
The running loss is:
12.706370091997087
The number of items in train is:
11
The loss for epoch 3
1.155124553817917
The running loss is:
13.30304903909564
The number of items in train is:
11
The loss for epoch 4
1.2093680944632401
The running loss is:
11.941582351922989
The number of items in train is:
11
The loss for epoch 5
1.0855983956293627
The running loss is:
11.729828983545303
The number of items in train is:
11
The loss for epoch 6
1.0663480894132094
The running loss is:
11.54419081658125
The number of items in train is:
11
The loss for epoch 7
1.0494718924164772
The running loss is:
11.445036083459854
The number of items in train is:
11
The loss for epoch 8
1.0404578257690777
The running loss is:
12.198932491242886
The number of items in train is:
11
The loss for epoch 9
1.1089938628402622
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.059834
47 30819 Eagle County, Colorado, United States ... 47 9.635443
48 30820 Eagle County, Colorado, United States ... 48 8.613738
49 30821 Eagle County, Colorado, United States ... 49 8.764878
50 30822 Eagle County, Colorado, United States ... 50 9.000231
51 30823 Eagle County, Colorado, United States ... 51 8.862867
52 30824 Eagle County, Colorado, United States ... 52 8.921799
53 30825 Eagle County, Colorado, United States ... 53 8.708253
54 30826 Eagle County, Colorado, United States ... 54 8.750038
55 30827 Eagle County, Colorado, United States ... 55 8.904809
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: w6g5blue wandb: Agent Starting Run: k5yt9z6i with config: batch_size: 3 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: k5yt9z6i
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
79.64415696263313
The number of items in train is:
11
The loss for epoch 0
7.240377905693921
The running loss is:
15.614883661270142
The number of items in train is:
11
The loss for epoch 1
1.4195348782972856
The running loss is:
31.27257139980793
The number of items in train is:
11
The loss for epoch 2
2.8429610363461753
The running loss is:
12.299777299165726
The number of items in train is:
11
The loss for epoch 3
1.1181615726514296
The running loss is:
12.365853264927864
The number of items in train is:
11
The loss for epoch 4
1.1241684786298058
The running loss is:
11.874301999807358
The number of items in train is:
11
The loss for epoch 5
1.0794819999824872
The running loss is:
11.15727785974741
The number of items in train is:
11
The loss for epoch 6
1.0142979872497646
The running loss is:
12.789401710033417
The number of items in train is:
11
The loss for epoch 7
1.1626728827303106
The running loss is:
12.836177736520767
The number of items in train is:
11
The loss for epoch 8
1.1669252487746151
The running loss is:
12.494936317205429
The number of items in train is:
11
The loss for epoch 9
1.13590330156413
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
36 30808 Eagle County, Colorado, United States ... 36 0.000000
37 30809 Eagle County, Colorado, United States ... 37 0.000000
38 30810 Eagle County, Colorado, United States ... 38 0.000000
39 30811 Eagle County, Colorado, United States ... 39 0.000000
40 30812 Eagle County, Colorado, United States ... 40 0.000000
41 30813 Eagle County, Colorado, United States ... 41 0.000000
42 30814 Eagle County, Colorado, United States ... 42 0.000000
43 30815 Eagle County, Colorado, United States ... 43 0.000000
44 30816 Eagle County, Colorado, United States ... 44 0.000000
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 9.161367
47 30819 Eagle County, Colorado, United States ... 47 7.209705
48 30820 Eagle County, Colorado, United States ... 48 7.124010
49 30821 Eagle County, Colorado, United States ... 49 6.953374
50 30822 Eagle County, Colorado, United States ... 50 6.195547
51 30823 Eagle County, Colorado, United States ... 51 6.672840
52 30824 Eagle County, Colorado, United States ... 52 8.153156
53 30825 Eagle County, Colorado, United States ... 53 8.977440
54 30826 Eagle County, Colorado, United States ... 54 7.785304
55 30827 Eagle County, Colorado, United States ... 55 7.588449
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: k5yt9z6i wandb: Agent Starting Run: 9x1zyi9m with config: batch_size: 3 forecast_history: 10 lr: 0.01 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 9x1zyi9m
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 3
dataset_params:
desc: null
value:
batch_size: 3
class: default
forecast_history: 10
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 10
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 10
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.01
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 10
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 3
criterion: MSE
epochs: 10
optim_params:
lr: 0.01
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
64.2933794260025
The number of items in train is:
10
The loss for epoch 0
6.429337942600251
The running loss is:
12.211681365966797
The number of items in train is:
10
The loss for epoch 1
1.2211681365966798
The running loss is:
21.949569940567017
The number of items in train is:
10
The loss for epoch 2
2.1949569940567017
The running loss is:
11.897155582904816
The number of items in train is:
10
The loss for epoch 3
1.1897155582904815
The running loss is:
11.937202170491219
The number of items in train is:
10
The loss for epoch 4
1.193720217049122
The running loss is:
11.373739659786224
The number of items in train is:
10
The loss for epoch 5
1.1373739659786224
The running loss is:
11.289853632450104
The number of items in train is:
10
The loss for epoch 6
1.1289853632450104
The running loss is:
12.61861452460289
The number of items in train is:
10
The loss for epoch 7
1.261861452460289
The running loss is:
11.258632987737656
The number of items in train is:
10
The loss for epoch 8
1.1258632987737656
The running loss is:
11.705809533596039
The number of items in train is:
10
The loss for epoch 9
1.1705809533596039
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 10, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
36 30808 ... 0.000000
37 30809 ... 0.000000
38 30810 ... 0.000000
39 30811 ... 0.000000
40 30812 ... 0.000000
41 30813 ... 0.000000
42 30814 ... 0.000000
43 30815 ... 0.000000
44 30816 ... 0.000000
45 30817 ... 0.000000
46 30818 ... 10.613785
47 30819 ... 10.972606
48 30820 ... 9.573963
49 30821 ... 10.296286
50 30822 ... 11.664459
51 30823 ... 11.187622
52 30824 ... 10.221498
53 30825 ... 9.448482
54 30826 ... 11.003543
55 30827 ... 10.186419
[20 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 9x1zyi9m wandb: Agent Starting Run: cnj2rij2 with config: batch_size: 4 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: cnj2rij2
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.563437849283218
The number of items in train is:
11
The loss for epoch 0
1.4148579862984745
The running loss is:
11.875256389379501
The number of items in train is:
11
The loss for epoch 1
1.0795687626708637
The running loss is:
11.802671521902084
The number of items in train is:
11
The loss for epoch 2
1.072970138354735
The running loss is:
10.889880567789078
The number of items in train is:
11
The loss for epoch 3
0.9899891425262798
The running loss is:
10.882348626852036
The number of items in train is:
11
The loss for epoch 4
0.9893044206229124
The running loss is:
10.595496848225594
The number of items in train is:
11
The loss for epoch 5
0.9632269862023267
The running loss is:
11.13110238313675
The number of items in train is:
11
The loss for epoch 6
1.0119183984669773
The running loss is:
11.167180925607681
The number of items in train is:
11
The loss for epoch 7
1.0151982659643346
The running loss is:
11.299386888742447
The number of items in train is:
11
The loss for epoch 8
1.027216989885677
The running loss is:
11.52681016921997
The number of items in train is:
11
The loss for epoch 9
1.047891833565452
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.068464
47 30819 Eagle County, Colorado, United States ... 47 7.053399
48 30820 Eagle County, Colorado, United States ... 48 7.034788
49 30821 Eagle County, Colorado, United States ... 49 6.769552
50 30822 Eagle County, Colorado, United States ... 50 6.443708
51 30823 Eagle County, Colorado, United States ... 51 6.102969
52 30824 Eagle County, Colorado, United States ... 52 5.758569
53 30825 Eagle County, Colorado, United States ... 53 7.237902
54 30826 Eagle County, Colorado, United States ... 54 7.340793
55 30827 Eagle County, Colorado, United States ... 55 7.105416
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: cnj2rij2 wandb: Agent Starting Run: j0ahel1n with config: batch_size: 4 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: j0ahel1n
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
17.160024404525757
The number of items in train is:
10
The loss for epoch 0
1.7160024404525758
The running loss is:
14.127461165189743
The number of items in train is:
10
The loss for epoch 1
1.4127461165189743
The running loss is:
14.144697785377502
The number of items in train is:
10
The loss for epoch 2
1.4144697785377502
The running loss is:
13.568500280380249
The number of items in train is:
10
The loss for epoch 3
1.356850028038025
The running loss is:
13.604806244373322
The number of items in train is:
10
The loss for epoch 4
1.3604806244373322
The running loss is:
13.699465811252594
The number of items in train is:
10
The loss for epoch 5
1.3699465811252594
The running loss is:
13.266174376010895
The number of items in train is:
10
The loss for epoch 6
1.3266174376010895
The running loss is:
13.102667212486267
The number of items in train is:
10
The loss for epoch 7
1.3102667212486268
The running loss is:
13.137517273426056
The number of items in train is:
10
The loss for epoch 8
1.3137517273426056
The running loss is:
13.256415218114853
The number of items in train is:
10
The loss for epoch 9
1.3256415218114852
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 17.149412
47 30819 ... 21.162560
48 30820 ... 21.526651
49 30821 ... 20.793573
50 30822 ... 19.730604
51 30823 ... 18.568447
52 30824 ... 17.376465
53 30825 ... 22.073378
54 30826 ... 22.643063
55 30827 ... 21.971800
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: j0ahel1n wandb: Agent Starting Run: fp31d2fi with config: batch_size: 4 forecast_history: 1 lr: 0.001 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: fp31d2fi
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.001
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.001
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.85852700471878
The number of items in train is:
10
The loss for epoch 0
1.685852700471878
The running loss is:
14.15521228313446
The number of items in train is:
10
The loss for epoch 1
1.415521228313446
The running loss is:
14.270996749401093
The number of items in train is:
10
The loss for epoch 2
1.4270996749401093
The running loss is:
13.61488264799118
The number of items in train is:
10
The loss for epoch 3
1.361488264799118
The running loss is:
13.466632664203644
The number of items in train is:
10
The loss for epoch 4
1.3466632664203644
The running loss is:
13.480274975299835
The number of items in train is:
10
The loss for epoch 5
1.3480274975299835
The running loss is:
13.14782440662384
The number of items in train is:
10
The loss for epoch 6
1.314782440662384
The running loss is:
13.135575473308563
The number of items in train is:
10
The loss for epoch 7
1.3135575473308563
The running loss is:
13.177307307720184
The number of items in train is:
10
The loss for epoch 8
1.3177307307720185
The running loss is:
13.156183660030365
The number of items in train is:
10
The loss for epoch 9
1.3156183660030365
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 1.945907
47 30819 Eagle County, Colorado, United States ... 47 1.576598
48 30820 Eagle County, Colorado, United States ... 48 1.056971
49 30821 Eagle County, Colorado, United States ... 49 0.520163
50 30822 Eagle County, Colorado, United States ... 50 -0.018607
51 30823 Eagle County, Colorado, United States ... 51 -0.557603
52 30824 Eagle County, Colorado, United States ... 52 -1.096623
53 30825 Eagle County, Colorado, United States ... 53 1.706281
54 30826 Eagle County, Colorado, United States ... 54 1.549211
55 30827 Eagle County, Colorado, United States ... 55 1.053840
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: fp31d2fi wandb: Agent Starting Run: rs828r4n with config: batch_size: 4 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: rs828r4n
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
14.697568587958813
The number of items in train is:
11
The loss for epoch 0
1.3361425989053466
The running loss is:
21.38100452721119
The number of items in train is:
11
The loss for epoch 1
1.9437276842919262
The running loss is:
12.067806363105774
The number of items in train is:
11
The loss for epoch 2
1.0970733057368884
The running loss is:
11.344721049070358
The number of items in train is:
11
The loss for epoch 3
1.0313382771882145
The running loss is:
11.251488268375397
The number of items in train is:
11
The loss for epoch 4
1.0228625698523088
The running loss is:
10.448600202798843
The number of items in train is:
11
The loss for epoch 5
0.9498727457089857
The running loss is:
10.87918820977211
The number of items in train is:
11
The loss for epoch 6
0.9890171099792827
The running loss is:
10.925427049398422
The number of items in train is:
11
The loss for epoch 7
0.993220640854402
The running loss is:
11.275335520505905
The number of items in train is:
11
The loss for epoch 8
1.0250305018641732
The running loss is:
11.531207740306854
The number of items in train is:
11
The loss for epoch 9
1.0482916127551685
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 6.516066
47 30819 Eagle County, Colorado, United States ... 47 7.549709
48 30820 Eagle County, Colorado, United States ... 48 7.593652
49 30821 Eagle County, Colorado, United States ... 49 7.419073
50 30822 Eagle County, Colorado, United States ... 50 7.196244
51 30823 Eagle County, Colorado, United States ... 51 6.962763
52 30824 Eagle County, Colorado, United States ... 52 6.726929
53 30825 Eagle County, Colorado, United States ... 53 7.780549
54 30826 Eagle County, Colorado, United States ... 54 7.828902
55 30827 Eagle County, Colorado, United States ... 55 7.655297
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: rs828r4n wandb: Agent Starting Run: tvqwisfk with config: batch_size: 4 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: tvqwisfk
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 2
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 2
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 2
number_time_series: 3
output_seq_len: 2
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 2
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
16.14820921421051
The number of items in train is:
10
The loss for epoch 0
1.614820921421051
The running loss is:
20.01530832052231
The number of items in train is:
10
The loss for epoch 1
2.001530832052231
The running loss is:
13.697478771209717
The number of items in train is:
10
The loss for epoch 2
1.3697478771209717
The running loss is:
13.846294492483139
The number of items in train is:
10
The loss for epoch 3
1.384629449248314
The running loss is:
13.398303747177124
The number of items in train is:
10
The loss for epoch 4
1.3398303747177125
The running loss is:
13.124554067850113
The number of items in train is:
10
The loss for epoch 5
1.3124554067850114
The running loss is:
12.877797603607178
The number of items in train is:
10
The loss for epoch 6
1.2877797603607177
The running loss is:
12.75420868396759
The number of items in train is:
10
The loss for epoch 7
1.275420868396759
The running loss is:
12.53428190946579
The number of items in train is:
10
The loss for epoch 8
1.253428190946579
The running loss is:
12.539280235767365
The number of items in train is:
10
The loss for epoch 9
1.2539280235767365
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 ... preds
45 30817 ... 0.000000
46 30818 ... 16.437286
47 30819 ... 19.616352
48 30820 ... 19.625738
49 30821 ... 18.815519
50 30822 ... 17.793373
51 30823 ... 16.716425
52 30824 ... 15.625306
53 30825 ... 20.219040
54 30826 ... 20.594223
55 30827 ... 19.878592
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: tvqwisfk wandb: Agent Starting Run: 8ncbbnk0 with config: batch_size: 4 forecast_history: 1 lr: 0.002 optimizer: Adam out_seq_length: 3 wandb: Agent Started Run: 8ncbbnk0
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 3
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 3
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.002
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 3
number_time_series: 3
output_seq_len: 3
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 3
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.002
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
15.368807047605515
The number of items in train is:
10
The loss for epoch 0
1.5368807047605515
The running loss is:
20.804774045944214
The number of items in train is:
10
The loss for epoch 1
2.080477404594421
The running loss is:
13.8933824300766
The number of items in train is:
10
The loss for epoch 2
1.38933824300766
The running loss is:
13.693770349025726
The number of items in train is:
10
The loss for epoch 3
1.3693770349025727
The running loss is:
13.354897767305374
The number of items in train is:
10
The loss for epoch 4
1.3354897767305374
The running loss is:
13.140376150608063
The number of items in train is:
10
The loss for epoch 5
1.3140376150608062
The running loss is:
12.762926369905472
The number of items in train is:
10
The loss for epoch 6
1.2762926369905472
The running loss is:
12.811955034732819
The number of items in train is:
10
The loss for epoch 7
1.2811955034732818
The running loss is:
12.677973330020905
The number of items in train is:
10
The loss for epoch 8
1.2677973330020904
The running loss is:
12.525837749242783
The number of items in train is:
10
The loss for epoch 9
1.2525837749242783
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 2.510345
47 30819 Eagle County, Colorado, United States ... 47 2.237988
48 30820 Eagle County, Colorado, United States ... 48 1.784898
49 30821 Eagle County, Colorado, United States ... 49 1.313485
50 30822 Eagle County, Colorado, United States ... 50 0.840213
51 30823 Eagle County, Colorado, United States ... 51 0.366755
52 30824 Eagle County, Colorado, United States ... 52 -0.106724
53 30825 Eagle County, Colorado, United States ... 53 2.398144
54 30826 Eagle County, Colorado, United States ... 54 2.226613
55 30827 Eagle County, Colorado, United States ... 55 1.783744
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: 8ncbbnk0 wandb: Agent Starting Run: p9hz0mzs with config: batch_size: 4 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 1 wandb: Agent Started Run: p9hz0mzs
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
Using Wandb config:
wandb_version: 1
GCS:
desc: null
value: false
_wandb:
desc: null
value:
cli_version: 0.8.35
framework: torch
is_jupyter_run: true
is_kaggle_kernel: false
python_version: 3.6.9
batch_size:
desc: null
value: 4
dataset_params:
desc: null
value:
batch_size: 4
class: default
forecast_history: 1
forecast_length: 1
interpolate: false
relevant_cols:
- new_cases
- month
- weekday
scaler: StandardScaler
target_col:
- new_cases
test_path: Colorado_Eagle County.csv
train_end: 44
training_path: Colorado_Eagle County.csv
valid_end: 57
valid_start: 45
validation_path: Colorado_Eagle County.csv
forecast_history:
desc: null
value: 1
forward_params:
desc: null
value: {}
inference_params:
desc: null
value:
dataset_params:
file_path: Colorado_Eagle County.csv
forecast_history: 1
forecast_length: 1
interpolate_param: false
relevant_cols:
- new_cases
- month
- weekday
scaling: StandardScaler
target_col:
- new_cases
datetime_start: '2020-04-21'
decoder_params:
decoder_function: simple_decode
unsqueeze_dim: 1
hours_to_forecast: 10
test_csv_path: Colorado_Eagle County.csv
lr:
desc: null
value: 0.004
metrics:
desc: null
value:
- MSE
model_name:
desc: null
value: MultiAttnHeadSimple
model_params:
desc: null
value:
forecast_length: 1
number_time_series: 3
output_seq_len: 1
seq_len: 1
model_type:
desc: null
value: PyTorch
optimizer:
desc: null
value: Adam
out_seq_length:
desc: null
value: 1
sweep:
desc: null
value: true
training_params:
desc: null
value:
batch_size: 4
criterion: MSE
epochs: 10
optim_params:
lr: 0.004
optimizer: Adam
wandb:
desc: null
value: false
Torch is using cpu
The running loss is:
11.638315871357918
The number of items in train is:
11
The loss for epoch 0
1.0580287155779926
The running loss is:
27.962097346782684
The number of items in train is:
11
The loss for epoch 1
2.542008849707517
The running loss is:
18.45736888051033
The number of items in train is:
11
The loss for epoch 2
1.677942625500939
The running loss is:
12.270208045840263
The number of items in train is:
11
The loss for epoch 3
1.1154734587127513
The running loss is:
12.896877467632294
The number of items in train is:
11
The loss for epoch 4
1.1724434061483904
The running loss is:
10.983336746692657
The number of items in train is:
11
The loss for epoch 5
0.9984851587902416
The running loss is:
11.255826324224472
The number of items in train is:
11
The loss for epoch 6
1.0232569385658612
The running loss is:
11.209508925676346
The number of items in train is:
11
The loss for epoch 7
1.0190462659705768
The running loss is:
11.425876408815384
The number of items in train is:
11
The loss for epoch 8
1.0387160371650348
The running loss is:
11.56713530421257
The number of items in train is:
11
The loss for epoch 9
1.0515577549284154
interpolate should be below
Now loading and scaling Colorado_Eagle County.csv
CSV Path below
Colorado_Eagle County.csv
torch.Size([1, 1, 3])
Add debugging crap below
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'] = 0 /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df['preds'][history_length:] = end_tensor.numpy().tolist() /usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._set_with(key, value) /content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)
torch.Size([10]) test_data scale Un-transforming data
/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
df['preds'][history_length:] = end_tensor_list
/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
test_acc = evaluate_model(trained_model, model_type, params["dataset_params"]["target_col"], params["metrics"], params["inference_params"], {})
Current historical dataframe
Unnamed: 0 name ... original_index preds
45 30817 Eagle County, Colorado, United States ... 45 0.000000
46 30818 Eagle County, Colorado, United States ... 46 7.352677
47 30819 Eagle County, Colorado, United States ... 47 8.552509
48 30820 Eagle County, Colorado, United States ... 48 8.681703
49 30821 Eagle County, Colorado, United States ... 49 8.588442
50 30822 Eagle County, Colorado, United States ... 50 8.448961
51 30823 Eagle County, Colorado, United States ... 51 8.299876
52 30824 Eagle County, Colorado, United States ... 52 8.148796
53 30825 Eagle County, Colorado, United States ... 53 8.838028
54 30826 Eagle County, Colorado, United States ... 54 8.861131
55 30827 Eagle County, Colorado, United States ... 55 8.745827
[11 rows x 32 columns]
/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning: Blended transforms not yet supported. Zoom behavior may not work as expected. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning: The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3. /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning: Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates! /usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning: I found a path object that I don't think is part of a bar chart. Ignoring.
wandb: Agent Finished Run: p9hz0mzs wandb: Agent Starting Run: uz3tntwz with config: batch_size: 4 forecast_history: 1 lr: 0.004 optimizer: Adam out_seq_length: 2 wandb: Agent Started Run: uz3tntwz Buffered data was truncated after reaching the output size limit.
reduced_config = {
"name": "Default sweep",
"method": "grid",
"parameters": {
"batch_size": {
"values": [2, 3]
},
"lr":{
"values":[0.002, 0.001]
},
"forecast_history":{
"values":[5]
},
"out_seq_length":{
"values":[3]
}
}
}
for region_df in df_list:
region_df, len_region, file_path = format_corona_data(region_df, "county")
sweep_id = wandb.sweep(reduced_config, project="covid-forecast")
paths = []
if len(os.listdir("model_save"))>1:
weight_files = filter(lambda x: x.endswith(".pth"), os.listdir("model_save"))
for weight_file in weight_files:
paths.append(os.path.join("model_save", weight_file))
correct_file = max(paths, key = os.path.getctime)
print(correct_file)
wandb.agent(sweep_id, lambda:train_function("PyTorch", make_config_file(file_path, len_region, correct_file)))
else:
wandb.agent(sweep_id, lambda:train_function("PyTorch", make_config_file(file_path, len_region))
print("sucessfully completed sweep for: " + file_path)