Chainer, a deep learning framework, and its extension libraries


Chainer™ is a Python-based deep learning framework developed and provided by PFN. First open-sourced in June 2015, Chainer has supported PFN’s growth as its deep learning research and development platform. Chainer was the first to adopt the define-by-run approach that allows developers to build complex neural networks in intuitive and flexible ways. The define-by-run approach has gained wide support from research and development communities and is now standard in PyTorch and other deep learning frameworks.

Chainer moved into a maintenance phase in December 2019 with the last v7 update. Currently, PFN is closely collaborating with the PyTorch community to migrate Chainer’s key elements and features to PyTorch.



Flexible: Flexibility to express complex models

Intuitive: Rapid prototyping and refinement support

Powerful: Powerful execution speed

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Chainer Extensions

Providing image recognition algorithms and dataset wrappers
ChainerCV – Blog

Deep reinforcement learning library

Visualization and experiment management tool for Chainer
ChainerUI – Blog

Graph convolutions for biology/chemistry tasks
Chainer Chemistry
Chainer Chemistry – Blog

Library for PyTorch with popular Chainer functions
pytorch-pfn-extras Migration from Chainer to PyTorch – Blog


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