Swati Rallapalli c47ccfd01d Enable variable size embedding (#25782) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/25782 Enable variable size embedding for dot processor. We split the embedding matrix into multiple towers, based on the embedding size and perform dot product in a loop over each of the towers and finally concatenate all the dot product outputs. Test Plan: buck test //caffe2/caffe2/fb/dper/layer_models/tests/split_1: https://our.intern.facebook.com/intern/testinfra/testrun/3659174703037560 Specific unit tests -- buck test //caffe2/caffe2/fb/dper/layer_models/tests/split_1:sparse_nn_test -- test_per_feature_emb_dim https://our.intern.facebook.com/intern/testinfra/testrun/3377699726358808 Reviewed By: chenshouyuan Differential Revision: D16690811 fbshipit-source-id: 8f5bce5aa5b272f5f795d4ac32bba814cc55210b		2019-09-09 22:08:32 -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	Support focal loss in MTML	2019-08-25 01:42:25 -07:00
batch_mse_loss.py
batch_normalization.py
batch_sigmoid_cross_entropy_loss.py
batch_softmax_loss.py
blob_weighted_sum.py
bpr_loss.py	Add BPR loss to TTSN (#24439)	2019-08-15 23:20:15 -07:00
bucket_weighted.py	Make hashing default for bucket-weighted pooling (#24266)	2019-08-13 13:56:32 -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	Return list of AccessedFeatures from get_accessed_features (#23983)	2019-08-14 10:50:27 -07:00
functional.py
gather_record.py
homotopy_weight.py
label_smooth.py
last_n_window_collector.py
layer_normalization.py
layers.py	Return list of AccessedFeatures from get_accessed_features (#23983)	2019-08-14 10:50:27 -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_dropout_with_replacement.py	hook up dropout sparse with replacement operator	2019-07-23 14:34:25 -07:00
sparse_feature_hash.py	Refactor and expose metadata of tum_history layer for online prediction	2019-08-15 00:27:11 -07:00
sparse_lookup.py	Add the sparse feature information during logging in sparse lookup layer (#24863)	2019-08-27 23:25:26 -07:00
split.py	Enable variable size embedding (#25782)	2019-09-09 22:08:32 -07:00
tags.py
uniform_sampling.py