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requirements.txt
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requirements.txt
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# Requirements automatically generated by pigar.
# https://github.com/damnever/pigar
# models/pretrained/berkley_coref_system.py: 7
# run.py: 21,22
allennlp == 0.8.3
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
asposebarcode == 1.0.0
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
asposestorage == 1.0.2
# models/apex/exec.py: 17
# models/apex_tf/architectures/coarse_grain_model.py: 12
# models/apex_tf/architectures/coarse_grain_model_v2.py: 13
# models/apex_tf/architectures/reduced_context_agg_ext_model.py: 9
# models/apex_tf/architectures/reduced_context_agg_model.py: 7
# models/apex_tf/bert_features.py: 7
# models/apex_tf/context_reducer.py: 4
# models/apex_tf/ensemble.py: 6
# models/apex_tf/gpt2_features.py: 7
# models/apex_tf/mean_pool_model.py: 6
# models/apex_tf/plus_features.py: 7
# models/apex_tf/tokenizer.py: 5
# models/base/stanford_base.py: 1
# models/data_pipeline.py: 5
# models/dataset.py: 3
# models/model.py: 6
# models/preprocessing/pretrained_features.py: 2
# models/preprocessing/text_sanitizer.py: 4
# run.py: 16
attrdict == 2.0.1
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
automium-web == 0.1.1
# models/apex_tf/ensemble.py: 8
# models/apex_tf/mean_pool_model.py: 4
# models/base/bayes_opt.py: 1,3,4,5,6,7
bayesian_optimization == 1.0.1
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
hematopy == 0.0.1.dev6
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
indras-net == 2.0.6
# models/data_pipeline.py: 7
# models/dataset.py: 5
# run.py: 1
# visualization/__init__.py: 1
ipython == 7.3.0
# models/apex_tf/fit_fold.py: 8,15
# models/preprocessing/coref_extractor.py: 4
joblib == 0.13.2
# models/base/utils.py: 6
networkx == 2.2
# run.py: 23
neuralcoref == 4.0
# models/base/utils.py: 5
# run.py: 26
nltk == 3.4
# models/apex/exec.py: 10
# models/apex/gpr_features.py: 5
# models/apex/graph_v2.py: 1
# models/apex_tf/architectures/coarse_grain_model.py: 2
# models/apex_tf/architectures/coarse_grain_model_v2.py: 2
# models/apex_tf/architectures/context_agg_model.py: 2
# models/apex_tf/architectures/reduced_context_agg_ext_model.py: 2
# models/apex_tf/architectures/reduced_context_agg_model.py: 2
# models/apex_tf/base_dataloader.py: 2
# models/apex_tf/bert_features.py: 4
# models/apex_tf/context_reducer.py: 2
# models/apex_tf/ensemble.py: 2
# models/apex_tf/gpt2_features.py: 4
# models/apex_tf/mean_pool_model.py: 15
# models/base/stanford_base.py: 2
# models/data_pipeline.py: 4
# models/dataset.py: 2
# models/model.py: 17
# models/preprocessing/coref_annotator.py: 2
# models/preprocessing/coref_extractor.py: 2
# models/preprocessing/label_sanitizer.py: 2
# models/preprocessing/mentions_annotator.py: 3
# models/preprocessing/pretrained_proref.py: 2
# models/preprocessing/text_sanitizer.py: 3
# models/pretrained/stanford.py: 1
# run.py: 10
# score.py: 2
# visualization/__init__.py: 5
numpy == 1.16.2
# models/apex/exec.py: 11
# models/apex_tf/architectures/coarse_grain_model.py: 3
# models/apex_tf/architectures/coarse_grain_model_v2.py: 3
# models/apex_tf/architectures/context_agg_model.py: 3
# models/apex_tf/architectures/reduced_context_agg_ext_model.py: 3
# models/apex_tf/architectures/reduced_context_agg_model.py: 3
# models/apex_tf/base_dataloader.py: 1
# models/apex_tf/bert_features.py: 5
# models/apex_tf/context_reducer.py: 1
# models/apex_tf/ensemble.py: 3
# models/apex_tf/fit_fold.py: 10
# models/apex_tf/gpt2_features.py: 5
# models/apex_tf/mean_pool_model.py: 14
# models/apex_tf/plus_features.py: 6
# models/apex_tf/tokenizer.py: 4
# models/data_pipeline.py: 3
# models/dataset.py: 1
# models/model.py: 16
# models/multi_pass_sieve.py: 1
# models/preprocessing/coref_annotator.py: 1
# models/preprocessing/coref_extractor.py: 1
# models/preprocessing/label_sanitizer.py: 1
# models/preprocessing/mentions_annotator.py: 2
# models/preprocessing/pretrained_features.py: 3
# models/preprocessing/pretrained_proref.py: 1
# models/preprocessing/text_sanitizer.py: 2
# models/pronoun_resolution.py: 1
# run.py: 9
# score.py: 1
# visualization/__init__.py: 4
pandas == 0.24.2
# models/pretrained/lee_et_al.py: 2
pyhocon == 0.3.51
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
pynotion == 0.0.1
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
pyskyscanner == 1.0.1
# models/apex/exec.py: 29
# models/apex/graph.py: 6
# models/apex/graph_v2.py: 8
# models/apex/ops.py: 7
# models/apex/ops_v2.py: 7
# models/apex_tf/bert_features.py: 20,21
# models/apex_tf/gpt2_features.py: 24
pytorch_pretrained_bert == 0.6.1
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
roomai == 0.1.16
# models/apex/exec.py: 24
# models/apex_tf/architectures/coarse_grain_model.py: 11,13
# models/apex_tf/architectures/coarse_grain_model_v2.py: 12,14
# models/apex_tf/architectures/context_agg_model.py: 5
# models/apex_tf/architectures/reduced_context_agg_ext_model.py: 8
# models/apex_tf/architectures/reduced_context_agg_model.py: 8
# models/apex_tf/bert_features.py: 6
# models/apex_tf/context_reducer.py: 3
# models/apex_tf/elmo_features.py: 3
# models/apex_tf/ensemble.py: 7
# models/apex_tf/fit_fold.py: 21
# models/apex_tf/gpt2_features.py: 6
# models/apex_tf/mean_pool_model.py: 7
# models/apex_tf/plus_features.py: 3,4,8
# models/apex_tf/tokenizer.py: 2
# models/data_pipeline.py: 6
# models/dataset.py: 4
# models/model.py: 7
# models/preprocessing/label_sanitizer.py: 3
# models/preprocessing/pretrained_features.py: 1
# models/preprocessing/text_sanitizer.py: 6
# models/pronoun_resolution.py: 4
# score.py: 4
scikit_learn == 0.20.3
# models/apex/exec.py: 23,35
scipy == 1.2.1
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
solar-radiation-model == 0.0.20
# run.py: 11
spacy == 2.0.18
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
swiftcodegen == 0.3
# models/apex_tf/architectures/coarse_grain_model.py: 1
# models/apex_tf/architectures/coarse_grain_model_v2.py: 1
# models/apex_tf/architectures/context_agg_model.py: 1
# models/apex_tf/architectures/reduced_context_agg_ext_model.py: 1
# models/apex_tf/architectures/reduced_context_agg_model.py: 1
# models/apex_tf/common_layers.py: 1
# models/apex_tf/elmo_features.py: 1
# models/apex_tf/fit_fold.py: 7
# models/apex_tf/mean_pool_model.py: 1
# models/model.py: 1
# models/pretrained/lee_et_al.py: 3
tensorflow_gpu == 1.13.1
# models/apex_tf/elmo_features.py: 2
tensorflow_hub == 0.3.0
# models/apex/exec.py: 22
# models/apex/graph.py: 1,2,3,4
# models/apex/graph_v2.py: 3,4,5,6
# models/apex/ops.py: 3,4,5,6
# models/apex/ops_v2.py: 3,4,5,6
# models/apex_tf/bert_features.py: 17,18
# models/apex_tf/fit_fold.py: 24
# models/apex_tf/gpt2_features.py: 17,18,23
# run.py: 13
torch == 1.0.1.post2
# models/apex/exec.py: 16
# models/apex/gpr_features.py: 6
# models/apex_tf/architectures/coarse_grain_model.py: 4
# models/apex_tf/architectures/coarse_grain_model_v2.py: 4
# models/apex_tf/architectures/context_agg_model.py: 4
# models/apex_tf/architectures/reduced_context_agg_ext_model.py: 4
# models/apex_tf/architectures/reduced_context_agg_model.py: 6
# models/apex_tf/base_dataloader.py: 3
# models/apex_tf/bert_features.py: 8
# models/apex_tf/gpt2_features.py: 8
# models/apex_tf/mean_pool_model.py: 5
# models/apex_tf/plus_features.py: 5
# models/apex_tf/tokenizer.py: 3
# models/model.py: 5
# models/preprocessing/coref_annotator.py: 4
# models/preprocessing/coref_extractor.py: 5
# models/preprocessing/mentions_annotator.py: 4
# models/preprocessing/text_sanitizer.py: 5
# models/pretrained/berkley_coref_system.py: 5
# models/pronoun_resolution.py: 3
# run.py: 15
tqdm == 4.31.1
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
transferflow == 0.1.8
# models/apex_tf/fit_fold.py: 6
# run.py: 18,19,25,28,29,30,31,32,33,34,36,37
# score.py: 6
visvmtagger == 1.0a0