micromamba create -n gpuTutorialEnv -c conda-forge -c nvidia -c pytorch -y pytorch-cuda=11.8 pytorch jupyterlab diffusers transformers accelerate safetensors omegaconf ipywidgets
specify "/dss/dsstbyfs01/pn56su/pn56su-dss-0020/opt/micromamba/envs/terrabyte_gpu" as a custom Jupyterlab micormaba Environment on the OpenOnDemand Portal
If nvidia-smi is not found a GPU is most likely not available if Torch is not CUDA enabled, try (re)installing it in the cuda enabled version (not cpu)
!nvidia-smi
Thu Nov 16 17:45:25 2023 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 520.61.05 Driver Version: 520.61.05 CUDA Version: 11.8 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 NVIDIA A100-SXM... On | 00000000:4B:00.0 Off | 0 | | N/A 43C P0 66W / 500W | 0MiB / 81920MiB | 0% Default | | | | Disabled | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+
import torch
print("Torch version:",torch.__version__)
print("Is CUDA enabled?",torch.cuda.is_available())
#If Cuda is not enabled recheck and reinstall pytorch in GPU Version
Torch version: 2.1.0.post300 Is CUDA enabled? True
URL: "https://huggingface.co/docs/diffusers/quicktour"
from diffusers import AutoPipelineForText2Image, StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline
import torch
pipeline_text2image = AutoPipelineForText2Image.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
).to("cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipeline_text2image(prompt=prompt).images[0]
image
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prompt = "25 scientists sitting at the german airospace center listening to a talk about machine learning, photorealistic, detailed, 8k"
image = pipeline_text2image(prompt=prompt).images[0]
image
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from diffusers import AutoPipelineForInpainting
from diffusers.utils import load_image
from diffusers import DiffusionPipeline
import torch
base = DiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
).to("cuda")
refiner = DiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-refiner-1.0",
text_encoder_2=base.text_encoder_2,
vae=base.vae,
torch_dtype=torch.float16,
use_safetensors=True,
variant="fp16",
).to("cuda")
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prompt = "A Satellite orbiting the Earth, photorealistic 8k"
image = base(
prompt=prompt,
num_inference_steps=40,
denoising_end=0.8,
output_type="latent",
).images
image = refiner(
prompt=prompt,
num_inference_steps=40,
denoising_start=0.8,
image=image,
).images[0]
image
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