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torch.where # torch.where(condition, input, other, *, out=None) → Tensor # Return a tensor of elements selected from either input or other, depending on condition. The operation is defined as:
PyTorch documentation # PyTorch is an optimized tensor library for deep learning using GPUs and CPUs. Features described in this documentation are classified by release status: Stable (API-Stable): These features will be maintained long-term and there should generally be no major performance limitations or gaps in documentation. We also expect to maintain backwards compatibility (although ...
We are excited to announce the release of PyTorch® 2.7 (release notes)! This release features: support for the NVIDIA Blackwell GPU architecture and pre-built wheels for CUDA 12.8 across Linux x86 and arm64 architectures. torch.compile support for Torch Function Modes which enables users to override any *torch.** operation to implement custom user-defined behavior. Mega Cache which allows ...
torch.library # Created On: Jun 13, 2022 | Last Updated On: Jun 07, 2025 torch.library is a collection of APIs for extending PyTorch’s core library of operators. It contains utilities for testing custom operators, creating new custom operators, and extending operators defined with PyTorch’s C++ operator registration APIs (e.g. aten operators). For a detailed guide on effectively using ...
Inductor CUTLASS backend support for both torch.compile and AOTInductor, as well as GEMMs such as mm, fp8 mm, addmm, and bmm. and more! See below. This release is composed of 4164 commits from 585 contributors since PyTorch 2.7. We want to sincerely thank our dedicated community for your contributions.
We are excited to announce the release of PyTorch® 2.6 (release notes)! This release features multiple improvements for PT2: torch.compile can now be used with Python 3.13; new performance-related knob torch. compiler. set_stance; several AOTInductor enhancements. Besides the PT2 improvements, another highlight is FP16 support on X86 CPUs.