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Tensors and Dynamic neural networks in Python with strong GPU acceleration
pytorch.org
Summary:
Uncached build: https://travis-ci.org/lukeyeager/caffe2/builds/239677224
Cached build: https://travis-ci.org/lukeyeager/caffe2/builds/239686725
* Parallel builds everywhere
* All builds use CCache for quick build times (help from https://github.com/pytorch/pytorch/pull/614, https://github.com/ccache/ccache/pull/145)
* Run ctests when available (continuation of https://github.com/caffe2/caffe2/pull/550)
* Upgraded from cuDNN v5 to v6
* Fixed MKL build (by updating pkg version)
* Fixed android builds (
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| .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.
Events
Caffe2 Bay Area Meetup at NVIDIA, May 31 6-8:30, Santa Clara, CA: https://www.meetup.com/Caffe2-Bay-Area/events/239836290/
User Groups
Caffe2 Community Facebook Group: join to ask questions, talk to other users, and keep informed of important Caffe2 updates.
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.