Chainer is a powerful, flexible and intuitive deep learning framework.
- Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
- Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures.
- Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug.
Note
As announced, Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.
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examples/index Colab Notebook Examples <https://chainer-colab-notebook.readthedocs.io/en/latest/> Awesome Chainer <https://github.com/chainer-community/awesome-chainer>
reference/index install chainerx/index chainermn/index onnx_chainer/index
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Slack Chat <https://bit.ly/go-chainer-slack> Forums <https://groups.google.com/forum/#!forum/chainer>