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Tensors and Dynamic neural networks in Python with strong GPU acceleration
5a856ce03e
Summary: salexspb recognized that my diff of fixing num_layers>1 cudnn lstm made it run much slower. Turns out this was caused by adding the dropout states to the gradient op (which it was missing ,that was a bug). But since we use dropout=1.0, we don't need to initialize the dropout states, and turns out this improves the perf of CuDNN LSTM very significantly, at least when hidden_dim is small (2.5x increase with hidden_dim=40). With large hidden_dim, the improvement is more modest. Reviewed By: salexspb Differential Revision: D4920543 fbshipit-source-id: 860c9d4c61793252f658dc5e3390bab571476be5 |
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| caffe2 | ||
| cmake | ||
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| third_party | ||
| .Doxyfile | ||
| .Doxyfile-c | ||
| .Doxyfile-python | ||
| .gitignore | ||
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| .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.
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.
Building Caffe2
Detailed Build Status
| Target | Status |
|---|---|
| Linux | |
| Android | |
| iOS | |
| Linux + MKL |