Chainer
The facts below are what the maker publishes about Chainer, checked and dated. Our editors have not written about it yet.
The facts
Each one read from Chainer's own pages, with the date it was checked.
What it does
- Automatic differentiation
- It provides automatic differentiation APIs using the define-by-run approach, also known as dynamic computational graphs.checked 11 Oct 2026
- Community support
- The documentation links to Chainer community Slack chat and forums.checked 11 Oct 2026
- Development status
- Chainer is in maintenance phase, with further development limited to bug fixes and maintenance.checked 11 Oct 2026
- Extensions
- ChainerRL implements deep reinforcement-learning algorithms, and ChainerCV provides tools for computer-vision neural networks.checked 11 Oct 2026
- GPU computing
- Chainer supports CUDA computation and can run on multiple GPUs; CUDA support requires installing CuPy separately.checked 11 Oct 2026
- GPU support
- Chainer supports CUDA computation and multi-GPU use; CUDA support requires CuPy, and cuDNN support is optional.checked 11 Oct 2026
- Installation
- The documentation recommends installing Chainer with pip and also describes installation from a source tarball or Git repository.checked 11 Oct 2026
- Integrations
- The v7 release announcement says ONNX-Chainer is integrated into Chainer and that most Chainer features, including ChainerMN, are compatible with ChainerX ndarray.checked 11 Oct 2026
- License
- The GitHub repository identifies Chainer's license as the MIT License.checked 11 Oct 2026
- Maintenance status
- Chainer is in maintenance, with further development limited to bug fixes and maintenance.checked 11 Oct 2026
- Migration
- The maker says it chose PyTorch as Chainer's replacement and released migration resources for users moving to PyTorch.checked 11 Oct 2026
- Model types
- It supports feed-forward, convolutional, recurrent, recursive, and per-batch network architectures.checked 11 Oct 2026
- Network architectures
- It supports feed-forward, convolutional, recurrent, and recursive networks, as well as per-batch architectures.checked 11 Oct 2026
- Optional capabilities
- Optional dependencies enable image-dataset support, HDF5 serialization, and distributed deep learning with ChainerMN.checked 11 Oct 2026
- Optional features
- Image dataset support, HDF5 serialization, and distributed deep learning with ChainerMN require optional dependencies.checked 11 Oct 2026
- Product
- Chainer is a Python-based, standalone open-source framework for building deep-learning models.checked 11 Oct 2026
- Python control flow
- Forward computation can use Python control-flow statements while retaining backpropagation, which the site says makes code intuitive and easy to debug.checked 11 Oct 2026
- Python support
- Chainer v7 supports Python 3.5.2 and later versions through 3.8, while Python 2 is unsupported.checked 11 Oct 2026
- Target users
- The maker describes Chainer as supporting deep-learning research and development, and says it chose PyTorch as the replacement framework for its own development efforts.checked 11 Oct 2026
The company
- Founded
- 2015checked 28 Sep 2026
Where it runs
- Platform limits
- The documentation recommends 64-bit Ubuntu 14.04 or 16.04 and CentOS 7, and says it cannot guarantee operation on Windows or macOS.checked 11 Oct 2026
- Platforms
- The recommended environments are 64-bit Ubuntu 14.04/16.04 LTS and CentOS 7; the documentation says it cannot guarantee operation on Windows or macOS.checked 11 Oct 2026
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