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Tensors and Dynamic neural networks in Python with strong GPU acceleration

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Caffe2

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.

License and Citation

Caffe2 is released under the BSD 2-Clause license.

Building Caffe2

Build Status

git clone https://github.com/bwasti/caffe2.git
cd caffe2

OS X

brew install openblas glog gtest automake protobuf leveled lmdb
mkdir build && cd build
cmake .. -DBLAS=OpenBLAS -DUSE_OPENCV=off
make

Ubuntu

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

Python support

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

Build status (known working)

Ubuntu 14.04 (GCC)

  • Default CPU build
  • Default GPU build

OS X (Clang)

  • Default CPU build
  • Default GPU build

Options (both Clang and GCC)

  • Nervana GPU
  • ZMQ
  • RocksDB
  • MPI
  • OpenMP
  • No LMDB
  • No LevelDB
  • No OpenCV

BLAS

  • OpenBLAS
  • ATLAS
  • MKL

Other

  • CMake 2.8 support
  • List of dependencies for Ubuntu 14.04
  • List of dependencies for OS X

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Tensors and Dynamic neural networks in Python with strong GPU acceleration

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  • Python 46.0%
  • C++ 43.9%
  • Cuda 4.0%
  • C 2.3%
  • Objective-C++ 1.4%
  • CMake 0.8%
  • Other 1.6%