Edward Yang

These sessions give participants an opportunity to meet some of the developers leading PyTorch to foster collaboration, gather feedback, and inspire contributions and collaboration . PyTorch core modules (e.g. torch.autograd, torch.optim, torch.nn) form the foundation for most AI research and...

This Deep Dive provides an update on PyTorch development since last conference and dives into key new features. We will explore how advancements across a number of PyTorch features combine to better support the full model development lifecycle across training, fine-tuning, and deployment.

Last year, we announced dynamic shapes support in PT2. We have come a long way since that announcement, with a lot new features, case studies and debugging tools for using dynamic shapes. This talk will dive into all of the new developments for dynamic shapes in PT2, arguably one of the most new...