Dec 1, 2025 · 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 …

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

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

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 …

The torch package contains data structures for multi-dimensional tensors and defines mathematical operations over these tensors. Additionally, it provides many utilities for efficient …

Jan 29, 2025 · Simplified Intel GPU software stack setup to enable one-click installation of the torch-xpu PIP wheels to run deep learning workloads in an out of the box fashion, eliminating …

class torch.nn.MSELoss(size_average=None, reduce=None, reduction='mean') [source] # Creates a criterion that measures the mean squared error (squared L2 norm) between each …

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

Dec 23, 2016 · Utility functions for initializing Module parameters. ... Utility classes and functions for pruning Module parameters. ... Parametrizations implemented using the new …