Jan 9, 2026 · Distributed Training Scalable distributed training and performance optimization in research and production is enabled by the torch.distributed backend.

Extending PyTorch Extending torch.func with autograd.Function Frequently Asked Questions Getting Started on Intel GPU Gradcheck mechanics HIP (ROCm) semantics Features for large-scale …

Speed up your models with minimal code changes using torch.compile, the latest PyTorch compiler solution.

CUDA 13.0 ROCm 6.4 CPU pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126

OSX macOS is currently not supported in LTS. Linux and Windows # CUDA 10.2 pip3 install torch==1.8.2 torchvision==0.9.2 torchaudio==0.8.2 --extra-index-url …

PyTorch is an open source machine learning framework that accelerates the path from research prototyping to production deployment. Built to offer maximum flexibility and speed, PyTorch supports …

Intro # This is a collection of beginner-friendly resources to help you get started with PyTorch. These tutorials cover fundamental concepts, basic operations, and essential workflows to build a solid …

PyTorch on XLA Devices PyTorch runs on XLA devices, like TPUs, with the torch_xla package. This document describes how to run your models on these devices.

torch-0.3.0.post4-cp27-cp27m-linux_x86_64.whl torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl torch-0.3.0.post4-cp35-cp35m-linux_x86_64.whl torch-0.3.0.post4-cp36 ...

Learn about PyTorch 2.x: faster performance, dynamic shapes, distributed training, and torch.compile.