Facebook Artificial Intelligence Blog
by Joe Spisak, Jeff Smith, Dmytro Dzhulgakov, Lin Qiao, Greg Chanan
May 1, 2019
Since its release just a few months ago, PyTorch 1.0 has been rapidly adopted as a powerful, flexible deep learning platform that enables engineers and researchers to move quickly from research to production. As part of Facebook’s F8 Conference this year, we are highlighting some of the ways the AI engineering and research community is using PyTorch 1.0. We’re also sharing new details about the latest release, PyTorch 1.1, and showcasing some of the new development tools created by the community.
Building on the initial launch of PyTorch in 2017, Facebook partnered with the AI community to ship the stable release of PyTorch 1.0 last December. Along with enhanced production-oriented capabilities and deep integration with leading cloud platforms, PyTorch 1.0 expands on the open source library’s core features, with the addition of PyTorch JIT (Just in time compilation) that seamlessly transitions between eager mode and graph mode to provide both flexibility and speed…
