@PyTorch: PyTorch releases include thousands of changes, and our Release Live Q&A gives you direct access to the maintainers and …

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PyTorch 2.12 release with major updates is highlighted, and a live Q&A event on May 20 with maintainers is announced to discuss compilation, distributed systems, quantization, and more.

PyTorch releases include thousands of changes, and our Release Live Q&A gives you direct access to the maintainers and contributors behind them. In this clip from our PyTorch 2.11 webinar, Nikita Shulga explains why quantization support is moving from PyTorch core to TorchAO and what that means for developers. Have questions? Join @AndreyTalman, @albanDesmaison, and @joespeez, moderated by @Chris_AI_HPC, on May 20 at 10:00 AM PT for a live Q&A covering PyTorch 2.12 and answering questions from the community. Register now: https://pytorch.org/event/pytorch-2-12-release-live-qa/…
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PyTorch releases include thousands of changes, and our Release Live Q&A gives you direct access to the maintainers and contributors behind them. In this clip from our PyTorch 2.11 webinar, Nikita Shulga explains why quantization support is moving from PyTorch core to TorchAO and what that means for developers. Have questions? Join @AndreyTalman, @albanDesmaison, and @joespeez, moderated by @Chris_AI_HPC, on May 20 at 10:00 AM PT for a live Q&A covering PyTorch 2.12 and answering questions from the community. Register now: https://pytorch.org/event/pytorch-2-12-release-live-qa/…


PyTorch 2.12 Release Live Q&A – PyTorch

Source: https://pytorch.org/event/pytorch-2-12-release-live-qa/

PyTorch 2.12 includes major updates across compilation, distributed systems, export, graph capture, and accelerator support. Highlights include a new device-agnostictorch\.accelerator\.GraphAPI, up to 100x faster batched eigenvalue decomposition on CUDA, support for microscaling quantization formats intorch\.export\.save, and expanded CUDA, ROCm, XPU, MPS, and Arm platform support.

Join us on Wednesday, May 20 at 10:00 AM PT for a live Q&A with panelists Andrey Talman, Alban Desmaison, and Joe Spisak, moderated by Chris Gottbrath. The panel will provide a brief overview of the release and answer your questions live.Register today!

Topics include:

  • Device-Agnostic Accelerator Graph Capture
  • ProcessGroup Support in Custom Ops
  • torch\.export\.saveSupport for Microscaling Quantization Formats
  • Fused Adagrad Optimizer Support
  • FlightRecorder Updates
  • Multi-GPU and Multi-Node Profiling Improvements
  • Updated Backend Selection fortorch\.linalg\.eighon CUDA
  • Expanded CUDA, ROCm, XPU, MPS, and Arm Platform Support

Register today.

Panelists

Andrey Talman Andrey Talman is a Software Engineer at Meta, primarily focused on open source releases for PyTorch and its ecosystem libraries. He works on release management, continuous integration, and process improvements, ensuring high-quality and timely delivery of PyTorch and related projects.

Alban Desmaison Alban Desmaison is a Research Engineer at Meta and the Lead Core Maintainer of PyTorch.

Joe Spisak Joe Spisak is Vice President of Product and Head of Open Source at Reflection AI. He is a PyTorch core maintainer, serves on the PyTorch Foundation Governing Board, and previously worked at Meta.

Moderator

Chris Gottbrath Chris Gottbrath is a Group Technical Program Manager supporting PyTorch at Meta and Chair of the PyTorch Foundation Marketing Committee.

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PyTorch 2.12 Release Highlights (7 minute read)

TLDR AI

PyTorch 2.12 introduces significant performance improvements including up to 100x faster batched eigendecomposition on CUDA, a new device-agnostic torch.accelerator.Graph API, and support for Microscaling quantization in torch.export, continuing the framework's evolution into a unified production platform.