Press Release: https://preferred.jp/en/news/pr20191205/

Preferred Networks Migrates its Deep Learning Research Platform to PyTorch

PFN to work with PyTorch and the open-source community to develop the framework and advance MN-Core processor support.

Preferred Networks, Inc. (PFN, Head Office: Tokyo, President & CEO: Toru Nishikawa) today announced plans to incrementally transition its deep learning framework (a fundamental technology in research and development) from PFN’s Chainer™ to PyTorch. Concurrently, PFN will collaborate with Facebook and the other contributors of the PyTorch community to actively participate in the development of PyTorch. With the latest major upgrade v7 released today, Chainer will move into a maintenance phase. PFN will provide documentation and a library to facilitate the migration to PyTorch for Chainer users.

PFN President and CEO Toru Nishikawa made the following comments on this business decision.

“Since the start of deep learning frameworks, Chainer has been PFN’s fundamental technology to support our joint research with Toyota, FANUC, and many other partners. Chainer provided PFN with opportunities to collaborate with major global companies, such as NVIDIA and Microsoft. Migrating to PyTorch from Chainer, which was developed with tremendous support from our partners, the community, and users, is an important decision for PFN. However, we firmly believe that by participating in the development of one of the most actively developed frameworks, PFN can further accelerate the implementation of deep learning technologies, while leveraging the technologies developed in Chainer and searching for new areas that can become a source of competitive advantage.”

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