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https://github.com/chainer/chainer

A flexible framework of neural networks for deep learning
https://github.com/chainer/chainer

chainer cuda cudnn cupy deep-learning gpu machine-learning neural-network neural-networks numpy python

Last synced: 10 days ago
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A flexible framework of neural networks for deep learning

Host: GitHub
URL: https://github.com/chainer/chainer
Owner: chainer
License: mit
Created: 2015-06-05T05:50:37.000Z (over 9 years ago)
Default Branch: master
Last Pushed: 2023-08-28T17:18:20.000Z (about 1 year ago)
Last Synced: 2024-08-04T22:09:34.930Z (3 months ago)
Topics: chainer, cuda, cudnn, cupy, deep-learning, gpu, machine-learning, neural-network, neural-networks, numpy, python
Language: Python
Homepage: https://chainer.org
Size: 51.2 MB
Stars: 5,883
Watchers: 287
Forks: 1,370
Open Issues: 12
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md

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my-awesome-starred - chainer - A flexible framework of neural networks for deep learning (Python)
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awesome-python-machine-learning - Chainer - Chainer is a Python-based deep learning framework aiming at flexibility. (Uncategorized / Uncategorized)
awesome-list - Chainer - A flexible framework of neural networks for deep learning. (Deep Learning Framework / High-Level DL APIs)

README

        ***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.***

----



# Chainer: A deep learning framework

[![pypi](https://img.shields.io/pypi/v/chainer.svg)](https://pypi.python.org/pypi/chainer)

[![GitHub license](https://img.shields.io/github/license/chainer/chainer.svg)](https://github.com/chainer/chainer)

[![travis](https://img.shields.io/travis/chainer/chainer/master.svg)](https://travis-ci.org/chainer/chainer)

[![coveralls](https://img.shields.io/coveralls/chainer/chainer.svg)](https://coveralls.io/github/chainer/chainer)

[![Read the Docs](https://readthedocs.org/projects/chainer/badge/?version=stable)](https://docs.chainer.org/en/stable/?badge=stable)

[![Optuna](https://img.shields.io/badge/Optuna-integrated-blue)](https://optuna.org)

[**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.

## 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)