commit | 390867d2d08e233976bc53645d897268d42200b5 | [log] [tgz] |
---|---|---|
author | Wael Abdelghani <wael@fb.com> | Fri Dec 09 01:12:32 2016 -0800 |
committer | Bram Wasti <bwasti@dev11999.prn1.facebook.com> | Thu Dec 15 12:01:29 2016 -0800 |
tree | 51203c6f85068cc9d75a45c74dd887545280d4c2 | |
parent | 0bc104a3d03098b4a232ce6d36b57ec450e96d80 [diff] |
Fix RecurrentNetworkGradient with batch size > 1 Summary: Fix RecurrentNetworkGradient with batch size > 1. The main issue was that we always set the Gradient output to 1, 1, recurrent_size which mismatch the input (1, batch_size, recurrent_size). Further gradient ops do Squeeze and split assuming that output gradient blob is the same size as the input so they fail. The fix is simply Resizing the output as the input (1, batch_size, recurrent_size), I had to move the resize to the RunOnDevice since batch_size is computed from Input(0) which is not available till the we actually run the op. Differential Revision: D4301487 fbshipit-source-id: e5c7426d6e770d985ce72a3737381a2b4af333ba
Caffe2 is a deep learning framework made with expression, speed, and modularity in mind. It is an experimental refactoring of Caffe, and allows a more flexible way to organize computation.
Read the installation instructions for installation details.
Caffe2 is released under the BSD 2-Clause license.