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Recent studies have shown that large model training will be beneficial for improving model quality.…

We are excited to announce the release of PyTorch 1.11 (release notes). This release is…

We are introducing the beta release of TorchRec and a number of improvements to the…

Introduction Ease of use, expressivity, and debuggability are among the core principles of PyTorch. One…

Amazon Ads uses PyTorch, TorchServe, and AWS Inferentia to reduce inference costs by 71% and…

We are excited to announce TorchRec, a PyTorch domain library for Recommendation Systems. This new library…

Quantization is a cheap and easy way to make your DNN run faster and with…

TorchVision has a new backwards compatible API for building models with multi-weight support. The new…

Ensuring the right memory format for your inputs can significantly impact the running time of…

More than 1,900 people worked hard in this year’s PyTorch Annual Hackathon to create unique…

A few weeks ago, TorchVision v0.11 was released packed with numerous new primitives, models and…

Introduction FX based feature extraction is a new TorchVision utility that lets us access intermediate transformations of an…

Today, we are pleased to announce a new advanced CUDA feature, CUDA Graphs, has been…

We are excited to announce the release of PyTorch 1.10. This release is composed of…