Dec 17, 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-scale …

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

Aug 29, 2024 · Graph mode (torch.compile) now has an enabled Intel GPU back end to implement the optimization for Intel GPUs and to integrate Triton. Furthermore, data types such as FP32, BF16, …

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

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

Apr 23, 2025 · Enable torch.compile on Windows 11 for Intel GPUs, delivering the performance advantages over eager mode as on Linux. Optimize the performance of PyTorch 2 Export Post …

Oct 17, 2024 · This API leverages torch.compile to generate a fused FlashAttention kernel, which eliminates extra memory allocation and achieves performance comparable to handwritten …

PyTorch has two primitives to work with data: torch.utils.data.DataLoader and torch.utils.data.Dataset. Dataset stores the samples and their corresponding labels, and DataLoader wraps an iterable …

pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126 Installing on Windows PyTorch can be installed and used on various Windows distributions. Depending on your system and …