PyTorch 2.0: Our next generation release that is faster, more Pythonic and Dynamic as ever

PyTorch 2.0: Our next generation release that is faster, more Pythonic and Dynamic as ever pytorch / pytorch Public Notifications You must be signed in to change notification settings Fork 30.5k Star 103k PyTorch 2.0: Our next generation release that is faster, more Pythonic and Dynamic as ever drisspg released this 15 Mar 19:38 · 37 commits to release/2.0 since this release v2.0.0 c263bd4 This commit was created on GitHub.com and signed with GitHub’s verified signature . GPG key ID: 4AEE18F83AFDEB23 Expired Verified Learn about vigilant mode .

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• pytorch / pytorch Public Notifications You must be signed in to change notification settings Fork 30.5k Star 103k PyTorch 2.0: Our next generation release that is faster, more Pythonic and Dynamic as ever drisspg released this 15 Mar 19:38 · 37 commits to release/2.0 since this release v2.0.0 c263bd4 This commit was created on GitHub.com and signed with GitHub’s verified signature .
• GPG key ID: 4AEE18F83AFDEB23 Expired Verified Learn about vigilant mode .
• PyTorch 2.0 Release notes Highlights Backwards Incompatible Changes Deprecations New Features Improvements Bug fixes Performance Documentation Highlights We are excited to announce the release of PyTorch® 2.0 ( release note ) which we highlighted during the PyTorch Conference on 12/2/22!
• PyTorch 2.0 offers the same eager-mode development and user experience, while fundamentally changing and supercharging how PyTorch operates at compiler level under the hood with faster performance and support for Dynamic Shapes and Distributed.
• This next-generation release includes a Stable version of Accelerated Transformers (formerly called Better Transformers); Beta includes torch.compile as the main API for PyTorch 2.0, the scaled_dot_product_attention function as part of torch.nn.functional, the MPS backend, functorch APIs in the torch.func module; and other Beta/Prototype improvements across various inferences, performance and training optimization features on GPUs and CPUs.
• For a comprehensive introduction and technical overview of torch.compile, please visit the 2.0 Get Started page .