Alyssa Wang d9e15bccb0 Perform weight re-init for embedding table in sparse_lookup.py (#22348) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/22348 This is the last step of LRU hash eviction weight re-init. This diff checks if there's evicted values in sparse_lookup, if so call op created in D15709866 to re-init the values for indicies in evicted_values. Also created gradient op for the operator. The gradient op just passes the output gradient as input gradient. Reviewed By: itomatik Differential Revision: D16044736 fbshipit-source-id: 9afb85209b0de1038c5153bcb7dfc5f52e0b2abb		2019-07-03 10:33:40 -07:00
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__init__.py
adaptive_weight.py
add_bias.py
arc_cosine_feature_map.py
batch_huber_loss.py	Add new regression loss function type to FBLearner (#21080)	2019-06-17 17:43:00 -07:00
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	Add hashing to bucket-weighted pooling (#20673)	2019-06-20 15:12:36 -07:00
build_index.py
concat.py
constant_weight.py
conv.py
dropout.py
fc.py
fc_without_bias.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	Pass LRU hash output evicted_values to SparseLookup (#21389)	2019-07-02 11:27:37 -07:00
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	Add div hashing	2019-06-12 11:27:37 -07:00
sparse_lookup.py	Perform weight re-init for embedding table in sparse_lookup.py (#22348)	2019-07-03 10:33:40 -07:00
split.py
tags.py
uniform_sampling.py