| commit | 05233cd5b86e320c5ac47f0ce0324fa6d25e06c9 | [log] [tgz] |
|---|---|---|
| author | Simon Layton <slayton58@users.noreply.github.com> | Mon Dec 19 14:49:46 2016 -0800 |
| committer | Facebook Github Bot <facebook-github-bot@users.noreply.github.com> | Mon Dec 19 14:59:49 2016 -0800 |
| tree | 1291cf26636ad3aa2dcccd1357e81fbe77d3b798 | |
| parent | fe38a0c2b18c68b03f2b94b609f83eda18b64420 [diff] |
Make bias optional in cuDNN conv op Summary: Yangqing This seems to work for me, not sure if it's implemented in the right way for you to accept :) Allows user to specify "no_bias" as an option for convolution layers (only cuDNN at this point), so that the bias associated with that operator is not allocated or computed. This is useful in particular for conv + BatchNorm combinations (such as ResNets), as the bias term can be handled by both conv and Batch Norm, wasting memory and computation. Closes https://github.com/caffe2/caffe2/pull/50 Reviewed By: Yangqing Differential Revision: D4341288 Pulled By: bwasti fbshipit-source-id: e6138d0024c83ed876dff2f83ffbebe7de502fd8
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.