commit | 81d5461973aade28a09f3cd293f8262f59a88db3 | [log] [tgz] |
---|---|---|
author | Yangqing Jia <jiayq@fb.com> | Sun Mar 05 22:36:55 2017 -0800 |
committer | Facebook Github Bot <facebook-github-bot@users.noreply.github.com> | Sun Mar 05 22:46:22 2017 -0800 |
tree | c7e3f767e63ff06142b6ef2944e43442089a3632 | |
parent | 4030fbf5350e931745e406a1bde6f4959c3ce000 [diff] |
cuda check -> enforce Summary: In the past we have moved most of the CHECKs to CAFFE_ENFORCE (exceptions). However, we kept the name "*_CHECK" for cuda calls, and that caused some confusion especially in the destructor calls: while our destructors are not written to handle exceptions, these CUDA_CHECKs could actually throw some exceptions. As a result, this diff (1) Renames all cuda related "*_CHECK" to "*_ENFORCE" (2) Explicitly marked the destructor of core Caffe2 classes as noexcept (3) Added proper, really-CHECK cuda check macros, and used those in the corresponding destructors. This should not change any of existing functionality. Reviewed By: dzhulgakov Differential Revision: D4656368 fbshipit-source-id: 32e3056e66c0400156c5ca0187b6151cf3d52404
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/caffe2/caffe2.git cd caffe2
brew install 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 python-protobuf 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
We use CMake's Android and iOS ports to build native binaries that you can then integrate into your Android or XCode projects. See scripts/build_android.sh and scripts/build_ios.sh for more details.
For Android, one can also use gradle to build Caffe2 directly with Android Studio. An example project can be found here. Note that you may need to configure Android Studio so that it has the right SDK and NDK versions to build the code.
For Raspbian, run scripts/build_raspbian.sh on the Raspberry Pi.
To install Caffe2 on NVidia's Tegra X1 platform, simply install the latest system with the NVidia JetPack installer, and then run scripts/build_tegra_x1.sh on the Tegra device.
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)
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