kmaehashi/chainer repository overview

⁠Chainer: A deep learning framework

Website⁠ | Docs⁠ | Install Guide⁠ | Tutorial⁠ | Examples (Official⁠, External⁠)

Forum (en⁠, ja⁠) | Slack invitation (en⁠, ja⁠) | Twitter (en⁠, ja⁠)

Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy⁠ for high performance training and inference. For more details of Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter.

⁠Stable version

The stable version of current Chainer is separated in here: v4⁠.

⁠Installation

To install Chainer, use pip.

$ pip install chainer

To enable CUDA support, set up CUDA⁠ and install CuPy⁠.

$ pip install cupy

See the installation guide for more details.⁠.

⁠Docker image

We are providing the official Docker image. This image supports nvidia-docker⁠. Login to the environment with the following command, and run the Python interpreter to use Chainer with CUDA and cuDNN support.

$ nvidia-docker run -it chainer/chainer /bin/bash

⁠Contribution

Any contributions to Chainer are welcome! If you want to file an issue or send a pull request, please follow the contribution guide⁠.

⁠License

MIT License (see LICENSE file).

⁠More information

• Release notes⁠
• Research projects using Chainer⁠

⁠Reference

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