PyTorch 发布: PyTorch 2.11.0 Release

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# PyTorch 2.11.0 Release Notes - [Highlights](#highlights) - [Backwards Incompatible Changes](#backwards-incompatible-changes) - [Deprecations](#deprecations) - [New Features](#new-features) - [Improvements](#improvements) - [Bug fixes](#bug-fixes) - [Performance](#performance) - [Documentation](#documentation) - [Developers](#developers) - [Security](#security) # Highlights Added Support for Differentiable Collectives for Distributed Training FlexAttention now has a FlashAttention-4 backend on Hopper and Blackwell GPUs MPS (Apple Silicon) Comprehensive Operator Expansion Added RNN/LSTM GPU Export Support Added XPU Graph Support For more details about these highlighted features, you can look at the [release blogpost](https://pytorch.org/blog/pytorch-2-11-release-blog/). Below are the full release notes for this release. # Backwards Incompatible Changes ## Release Engineering ### Volta (SM 7.0) GPU support removed from CUDA 12.8 and 12.9 binary builds (#172598) Starting with PyTorch 2.11, the CUDA 12.8 and 12.9 pre-built binaries no longer include support for Volta GPUs (compute capability 7.0, e.g. V100). This change was necessary to enable updating to CuDNN 9.15.1, which is incompatible with Volta. Users with Volta GPUs who need CUDA 12.8+ should use the CUDA 12.6 builds, which continue to include Volta support. Alternatively, build PyTorch from source with Volta included in `TORCH_CUDA_ARCH_LIST`. Version 2.10: ``` # CUDA 12.8 builds supported Volta (SM 7.0) pip install torch --index-url https://download.pytorch.org/whl/cu128 # Works on V100 ``` Version 2.11: ``` # CUDA 12.8 builds no longer support Volta # For V100 users, use CUDA 12.6 builds instead: pip install torch --index-url https://download.pytorch.org/whl/cu126 ``` ### PyPI wheels now ship with CUDA 13.0 inst