Chainer is tested on Ubuntu 14.04 and CentOS 7. We recommend them to use Chainer, though it may run on other systems as well.

Minimum requirements:

• Python 2.7.6+, 3.4.3+, 3.5.0+
• NumPy 1.9
• Six 1.9
• h5py 2.5.0

Requirements for some features:

• CUDA support
  • CUDA 6.5, 7.0, 7.5
  • filelock
  • g++
• cuDNN support
  • cuDNN v2, v3
• Caffe model support
  • Python 2.7.6+ (Py3 is not supported)
  • Protocol Buffers (pip install protobuf)
• Testing utilities
  • Mock
  • Nose

Chainer requires libhdf5 via h5py. Anaconda distribution includes this package. If you are using another Python distribution, use either of the following commands to install libhdf5 depending on your Linux environment:

apt-get install libhdf5-dev
yum install hdf5-devel

If you use old setuptools, upgrade it:

pip install -U setuptools

Then, install Chainer via PyPI:

pip install chainer

You can also install Chainer from the source code:

python setup.py install

If you want to enable CUDA, first you have to install CUDA and set the environment variable PATH and LD_LIBRARY_PATH for CUDA executables and libraries. For example, if you are using Ubuntu and CUDA is installed by the official distribution, then CUDA is installed at /usr/local/cuda. In this case, you have to add the following lines to .bashrc or .zshrc (choose which you are using):

export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

Chainer had chainer-cuda-deps module to enable CUDA in previous version. Recent version (>=1.3) does not require this module. So you do not have to install chainer-cuda-deps.

If you want to enable cuDNN, add a directory containing cudnn.h to CPATH, and add a directory containing libcudnn.so to LIBRARY_PATH and LD_LIBRARY_PATH:

export CPATH=/path/to/cudnn/include:$CPATH
export LIBRARY_PATH=/path/to/cudnn/lib:$LIBRARY_PATH
export LD_LIBRARY_PATH=/path/to/cudnn/lib:$LD_LIBRARY_PATH

Do not forget to restart your terminal session (or source it) to enable these changes. And then, reinstall Chainer.

Tokui, S., Oono, K., Hido, S. and Clayton, J., Chainer: a Next-Generation Open Source Framework for Deep Learning, Proceedings of Workshop on Machine Learning Systems(LearningSys) in The Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS), (2015) URL, BibTex

• Official site: http://chainer.org/
• Official document: http://docs.chainer.org/
• github: https://github.com/pfnet/chainer
• Forum: https://groups.google.com/forum/#!forum/chainer
• Forum (Japanese): https://groups.google.com/forum/#!forum/chainer-jp
• Twitter: https://twitter.com/ChainerOfficial
• Twitter (Japanese): https://twitter.com/chainerjp

MIT License (see LICENSE file).