Ahmed Aly f8778aef78 Implement a Caffe2 standalone LSTM operator (#17726) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/17726 Pull Request resolved: https://github.com/pytorch/pytorch/pull/17725 Pull Request resolved: https://github.com/pytorch/pytorch/pull/17461 Implementing a standalone LSTM Operator in Caffe2 adopted from this Aten implementation: diffusion/FBS/browse/master/fbcode/caffe2/aten/src/ATen/native/RNN.cpp. The most tricky thing in this exercise was that caffe2::Tensor has no copy constructor that made it necessary to implement a custom templated copy constructor for the different Tensor containers used in the code. Also there was no way to use off-the-shelf C2 operators in my code easily so I had to copy some code that is doing basic matmul, cat, split, transpose and linear as utility functions. Two things missing: - Profiling this implementation against the current ONNXified LSTM op - Make this operator available to use in PyTorch Reviewed By: dzhulgakov Differential Revision: D14351575 fbshipit-source-id: 3b99b53212cf593c7a49e45580b5a07b90809e64		2019-03-07 01:08:49 -08:00
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__init__.py	Add __init__.py so files get picked up on install (#14898)	2018-12-07 13:40:23 -08:00
blob_deallocation_test.py	Fix crash in blob deallocation	2017-10-10 19:03:01 -07:00
do_op_test.py	DoOp reuse workspace and test	2017-10-12 13:37:34 -07:00
executor_test_util.py	Fix occasional test timeouts	2018-01-19 20:08:58 -08:00
executor_test.py	Unify gpu_support variable in python tests (#16748)	2019-02-07 00:29:51 -08:00
inference_lstm_op_test.py	Implement a Caffe2 standalone LSTM operator (#17726)	2019-03-07 01:08:49 -08:00