commit | bb928f3cc074cbeeddf92ecf05eb7889cfe65f48 | [log] [tgz] |
---|---|---|
author | Aapo Kyrola <akyrola@fb.com> | Tue Jan 10 12:58:49 2017 -0800 |
committer | Facebook Github Bot <facebook-github-bot@users.noreply.github.com> | Tue Jan 10 12:59:23 2017 -0800 |
tree | 1c3b5234eb40a5a6e8939097e54aeb48f0f0e3eb | |
parent | 4f1db36cffd15b2fd8110425a7a3cd0a4f863581 [diff] |
Latest fixes to Xray Flow workflows for Caffe2 Summary: (Ignore the convolution-op related changes, they will be later patched separately) This diff ignores work from latest few weeks: - some refactoring of the flow ops - no_bias setting - MAP computation (instead of accuracy) for OC - adaptive learning rate for Xray concepts - various small bug fixes Reviewed By: viswanathgs Differential Revision: D4329500 fbshipit-source-id: 000d4fd22ec408af5290480c788eb86546bff52e
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.
Caffe2 is released under the BSD 2-Clause license.
git clone --recursive https://github.com/bwasti/caffe2.git cd caffe2
brew install gtest automake protobuf mkdir build && cd build cmake .. make
sudo apt-get install libprotobuf-dev protobuf-compiler libatlas-base-dev libgoogle-glog-dev libgtest-dev liblmdb-dev libleveldb-dev libsnappy-dev python-dev python-pip libiomp-dev libopencv-dev libpthread-stubs0-dev cmake sudo pip install numpy wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_8.0.44-1_amd64.deb sudo dpkg -i cuda-repo-ubuntu1404_8.0.44-1_amd64.deb sudo apt-get update sudo apt-get install cuda sudo apt-get install git CUDNN_URL="http://developer.download.nvidia.com/compute/redist/cudnn/v5.1/cudnn-8.0-linux-x64-v5.1.tgz" && curl -fsSL ${CUDNN_URL} -O && sudo tar -xzf cudnn-8.0-linux-x64-v5.1.tgz -C /usr/local && rm cudnn-8.0-linux-x64-v5.1.tgz && sudo ldconfig mkdir build && cd build cmake .. make
To run the tutorials you'll need ipython-notebooks and matplotlib, which can be installed on OS X with:
brew install matplotlib --with-python3 pip install ipython notebook
Ubuntu 14.04 (GCC)
OS X (Clang)
Options (both Clang and GCC)
BLAS
Other