As always, we encourage you to try these out and report any issues as we improve 2.0 and the overall 2-series this year. We want to sincerely thank our dedicated community for your contributions. This release is composed of over 4,541 commits and 428 contributors since 1.13.1. More details can be found in this library blog. An update for TorchX is also being released as it moves to community supported mode.
For a comprehensive introduction and technical overview of pile, please visit the 2.0 Get Started page.Īlong with 2.0, we are also releasing a series of beta updates to the PyTorch domain libraries, including those that are in-tree, and separate libraries including TorchAudio, TorchVision, and TorchText. This next-generation release includes a Stable version of Accelerated Transformers (formerly called Better Transformers) Beta includes pile 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. We are excited to announce the release of PyTorch® 2.0 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.
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