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Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Maxime Boucher f16c2fe3da Create a reserve operation for tensors to avoid reallocating memory on Extend() and Resize() operations 
Summary: I want to collect tensors over multiple batches and so this operation could become helpful to allocate enough memory from the beginning

Reviewed By: dzhulgakov

Differential Revision: D4216198

fbshipit-source-id: e6b67cc7d80d71455487878da9b6b7a225035085
2016-11-29 15:18:39 -08:00
caffe/proto more build updates: 2016-08-02 23:28:23 -07:00
caffe2 Create a reserve operation for tensors to avoid reallocating memory on Extend() and Resize() operations 2016-11-29 15:18:39 -08:00
docs chunky sync 2016-05-13 14:43:48 -07:00
third_party nervana build files 2016-10-07 18:37:26 -07:00
.Doxyfile Adding optional Eigen code. Added a switch USE_SYSTEM_EIGEN in Env. Misc changes. 2015-10-18 16:55:24 -07:00
.gitignore Adding optional Eigen code. Added a switch USE_SYSTEM_EIGEN in Env. Misc changes. 2015-10-18 16:55:24 -07:00
.gitmodules nervana build files 2016-10-07 18:37:26 -07:00
build.py nervana build files 2016-10-07 18:37:26 -07:00
build_android.py fbsync 2016-10-07 15:47:52 -07:00
build_android_prepare.py fbsync 2016-10-07 15:47:52 -07:00
LICENSE fbsync. TODO: check if build files need update. 2016-11-15 00:00:46 -08:00
Makefile more build updates: 2016-08-02 23:28:23 -07:00
README.md removed deprecated readme info 2016-11-18 17:03:20 -08:00

README.md

Caffe2

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.

License and Citation

Caffe2 is released under the BSD 2-Clause license.