During last year’s F8 developer conference, Facebook announced the 1.0 launch of PyTorch, the company’s open source deep learning platform. At this year’s F8, the company launched version 1.1. The small increase in version numbers belies the importance of this release, which focuses on making the tool more appropriate for production usage, including improvements to how the tool handles distributed training.
“What we’re seeing with PyTorch is incredible moment internally at Facebook to ship it and then an echo of that externally with large companies,” Joe Spisak, Facebook AI’s product manager for PyTorch, told me. “Make no mistake, we’re not trying to monetize PyTorch […] but we want to see PyTorch have a community. And that community is starting to shift from a very research-centric community — and that continues to grow fast — into the production world.”
So with this release, the team and the over 1,000 open-source committers that have worked on this project are addressing the shortcoming of the earlier release as users continue to push the limits. Some of those users, for example, include Microsoft, which is using PyTorch for its language models that scale to a billion words and Toyota, which is using it for