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README.md
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# Chainer: A deep learning framework
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[**Website**](https://chainer.org/)
| [**Docs**](https://docs.chainer.org/en/stable/)
| [**Install Guide**](https://docs.chainer.org/en/stable/install.html)
| **Tutorials** ([ja](https://tutorials.chainer.org/ja/))
| **Examples** ([Official](examples), [External](https://github.com/chainer-community/awesome-chainer))
| [**Concepts**](https://docs.chainer.org/en/stable/guides/)
| [**ChainerX**](#chainerx)
**Forum** ([en](https://groups.google.com/forum/#!forum/chainer), [ja](https://groups.google.com/forum/#!forum/chainer-jp))
| **Slack invitation** ([en](https://bit.ly/go-chainer-slack), [ja](https://bit.ly/go-chainer-jp-slack))
| **Twitter** ([en](https://twitter.com/CuPy_Team), [ja](https://twitter.com/ChainerJP))
*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](https://github.com/cupy/cupy) for high performance training and inference.
For more details about Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter.
***Notice: As [announced](https://chainer.org/announcement/2019/12/05/released-v7.html), Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.***
## Installation
*For more details, see the [installation guide](https://docs.chainer.org/en/stable/install.html).*
To install Chainer, use `pip`.
```sh
$ pip install chainer
```
To enable CUDA support, [CuPy](https://github.com/cupy/cupy) is required.
Refer to the [CuPy installation guide](https://docs-cupy.chainer.org/en/stable/install.html).
## Docker image
We are providing the official Docker image.
This image supports [nvidia-docker](https://github.com/NVIDIA/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
See the [contribution guide](https://docs.chainer.org/en/stable/contribution.html).
## ChainerX
See the [ChainerX documentation](https://docs.chainer.org/en/stable/chainerx/index.html).
## License
MIT License (see `LICENSE` file).
## More information
- [Release notes](https://github.com/chainer/chainer/releases)
## References
Tokui, Seiya, et al. "Chainer: A Deep Learning Framework for Accelerating the Research Cycle." *Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining*. ACM, 2019.
[URL](https://dl.acm.org/citation.cfm?id=3330756) [BibTex](chainer2019_bibtex.txt)
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](http://learningsys.org/papers/LearningSys_2015_paper_33.pdf), [BibTex](chainer_bibtex.txt)
Akiba, T., Fukuda, K. and Suzuki, S.,
ChainerMN: Scalable Distributed Deep Learning Framework,
*Proceedings of Workshop on ML Systems in
The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS)*, (2017)
[URL](http://learningsys.org/nips17/assets/papers/paper_25.pdf), [BibTex](chainermn_bibtex.txt)
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