PyTorch
4 days ago · Distributed Training Scalable distributed training and performance optimization in research and production is enabled by the torch.distributed backend.
PyTorch documentation — PyTorch 2.9 documentation
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 …
torch — PyTorch 2.9 documentation
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 …
PyTorch 2.x
Learn about PyTorch 2.x: faster performance, dynamic shapes, distributed training, and torch.compile.
Learning PyTorch with Examples
In PyTorch we can easily define our own autograd operator by defining a subclass of torch.autograd.Function and implementing the forward and backward functions. We can then use our …
PyTorch 2.5 Release Blog
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 …
Get Started - PyTorch
CUDA 13.0 ROCm 6.4 CPU pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
Learn the Basics — PyTorch Tutorials 2.9.0+cu128 documentation
Learn the Basics || Quickstart || Tensors || Datasets & DataLoaders || Transforms || Build Model || Autograd || Optimization || Save & Load Model Learn the Basics # Created On: Feb 09, 2021 | Last …
End-to-end Machine Learning Framework – PyTorch
## Save your model torch. jit. script (model). save ("my_mobile_model.pt") ## iOS prebuilt binary pod ‘LibTorch’ ## Android prebuilt binary implementation 'org.pytorch:pytorch_android:1.3.0' ## Run your …
Domains - PyTorch
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.