from fastai.gen_doc.nbdoc import *
from fastai.text import * 


show_doc(language_model_learner)

jekyll_note("Using QRNN (change the flag in the config of the AWD LSTM) requires to have cuda installed (same version as pytorch is using).")

path = untar_data(URLs.IMDB_SAMPLE)
data = TextLMDataBunch.from_csv(path, 'texts.csv')
learn = language_model_learner(data, AWD_LSTM, drop_mult=0.5)

show_doc(text_classifier_learner)

path = untar_data(URLs.IMDB_SAMPLE)
data = TextClasDataBunch.from_csv(path, 'texts.csv')
learn = text_classifier_learner(data, AWD_LSTM, drop_mult=0.5)

show_doc(RNNLearner)

show_doc(RNNLearner.get_preds)

show_doc(TextClassificationInterpretation,title_level=3)

import matplotlib.cm as cm

txt_ci = TextClassificationInterpretation.from_learner(learn)
test_text = "Zombiegeddon was perhaps the GREATEST movie i have ever seen!"
txt_ci.show_intrinsic_attention(test_text,cmap=cm.Purples)

txt_ci.intrinsic_attention(test_text)[1]

txt_ci.show_top_losses(5)

show_doc(RNNLearner.load_encoder)

show_doc(RNNLearner.save_encoder)

show_doc(RNNLearner.load_pretrained)

show_doc(convert_weights)

show_doc(LanguageLearner, title_level=3)

show_doc(LanguageLearner.predict)

show_doc(LanguageLearner.beam_search)

show_doc(get_language_model)

show_doc(get_text_classifier)

show_doc(MultiBatchEncoder.forward)

show_doc(LanguageLearner.show_results)

show_doc(MultiBatchEncoder.concat)

show_doc(MultiBatchEncoder)

show_doc(decode_spec_tokens)

show_doc(MultiBatchEncoder.reset)