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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/17549 Currently Dropout is only enabled in training, we enable the option of having dropout in Eval. This is to follow [1]. This functionality would be used for uncertainty estimation in exploration project. [1] Gal, Yarin, and Zoubin Ghahramani. "Dropout as a bayesian approximation: Representing model uncertainty in deep learning." international conference on machine learning. 2016. Reviewed By: Wakeupbuddy Differential Revision: D14216216 fbshipit-source-id: 87c8c9cc522a82df467b685805f0775c86923d8b |
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| .. | ||
| __init__.py | ||
| adaptive_weight.py | ||
| add_bias.py | ||
| arc_cosine_feature_map.py | ||
| batch_distill_lr_loss.py | ||
| batch_lr_loss.py | ||
| batch_mse_loss.py | ||
| batch_normalization.py | ||
| batch_sigmoid_cross_entropy_loss.py | ||
| batch_softmax_loss.py | ||
| blob_weighted_sum.py | ||
| bucket_weighted.py | ||
| build_index.py | ||
| concat.py | ||
| constant_weight.py | ||
| conv.py | ||
| dropout.py | ||
| fc_without_bias.py | ||
| fc.py | ||
| feature_sparse_to_dense.py | ||
| functional.py | ||
| gather_record.py | ||
| homotopy_weight.py | ||
| label_smooth.py | ||
| last_n_window_collector.py | ||
| layer_normalization.py | ||
| layers.py | ||
| margin_rank_loss.py | ||
| merge_id_lists.py | ||
| pairwise_similarity.py | ||
| position_weighted.py | ||
| random_fourier_features.py | ||
| reservoir_sampling.py | ||
| sampling_train.py | ||
| sampling_trainable_mixin.py | ||
| select_record_by_context.py | ||
| semi_random_features.py | ||
| sparse_feature_hash.py | ||
| sparse_lookup.py | ||
| split.py | ||
| tags.py | ||
| uniform_sampling.py | ||