Finally, it has a JIT (Just-In-Time) component that takes your code and optimizes it for the XLA compiler, resulting in significant performance improvements over TensorFlow and PyTorch.

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

As of today, PyTorch/XLA support for Cloud TPUs — Google’s managed TPU service — is now generally available, enabling PyTorch users to take advantage of TPUs using first-party integrations.

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.

Other new improvements in PyTorch 1.8.1 include enabling autocast for PyTorch xla, making the torch. submodule import more autocomplete-friendly, and more. The full release notes for PyTorch 1.8.1 ...

The general availability on PyTorch/XLA means users can access cloud TPU accelerators via a stable integration, the companies said Tuesday (Sept. 29). Separately, promoters of the programming language ...

PALO ALTO, Calif., Sept. 29, 2020 — The PyTorch machine learning (ML) framework is popular in the ML community for its flexibility and ease-of-use, and we are excited to support it across Google Cloud ...