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Tensors and Dynamic neural networks in Python with strong GPU acceleration
pytorch.org
Summary: According to GitHub issue #1168, YellowFin's accuracy between Caffe2 and Numpy models from tests are not good enough in some environments. Results were very close on my machine. GitHub's Travis failed on some tests which I later disabled. Therefore the difference doesn't come from logical differences but from loss of precision on some machines. It is safe to disable equivalency test if equivalency was already once tested. Reviewed By: akyrola Differential Revision: D5777049 fbshipit-source-id: c249a205d94b52c3928c37481f15227d500aafd0 |
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| .travis | ||
| caffe/proto | ||
| caffe2 | ||
| cmake | ||
| conda | ||
| docker | ||
| docs | ||
| scripts | ||
| third_party | ||
| .Doxyfile | ||
| .Doxyfile-c | ||
| .Doxyfile-python | ||
| .gitignore | ||
| .gitmodules | ||
| .travis.yml | ||
| appveyor.yml | ||
| CMakeLists.txt | ||
| LICENSE | ||
| Makefile | ||
| PATENTS | ||
| README.md | ||
| release-notes.md | ||
Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind.
News and Events
Caffe2 research award competition request for proposals
Questions and Feedback
Please use Github issues (https://github.com/caffe2/caffe2/issues) to ask questions, report bugs, and request new features.
Please participate in our survey (https://www.surveymonkey.com/r/caffe2). We will send you information about new releases and special developer events/webinars.
License and Citation
Caffe2 is released under the BSD 2-Clause license.