Bump torch from 1.9.0 to 1.13.1 #4

Merged
dependabot[bot] merged 1 commits from dependabot/pip/torch-1.13.1 into master 2024-02-03 20:00:24 +00:00
dependabot[bot] commented 2024-02-03 19:59:12 +00:00 (Migrated from github.com)

Bumps torch from 1.9.0 to 1.13.1.

Release notes

Sourced from torch's releases.

PyTorch 1.13.1 Release, small bug fix release

This release is meant to fix the following issues (regressions / silent correctness):

  • RuntimeError by torch.nn.modules.activation.MultiheadAttention with bias=False and batch_first=True #88669
  • Installation via pip on Amazon Linux 2, regression #88869
  • Installation using poetry on Mac M1, failure #88049
  • Missing masked tensor documentation #89734
  • torch.jit.annotations.parse_type_line is not safe (command injection) #88868
  • Use the Python frame safely in _pythonCallstack #88993
  • Double-backward with full_backward_hook causes RuntimeError #88312
  • Fix logical error in get_default_qat_qconfig #88876
  • Fix cuda/cpu check on NoneType and unit test #88854 and #88970
  • Onnx ATen Fallback for BUILD_CAFFE2=0 for ONNX-only ops #88504
  • Onnx operator_export_type on the new registry #87735
  • torchrun AttributeError caused by file_based_local_timer on Windows #85427

The release tracker should contain all relevant pull requests related to this release as well as links to related issues

PyTorch 1.13: beta versions of functorch and improved support for Apple’s new M1 chips are now available

Pytorch 1.13 Release Notes

  • Highlights
  • Backwards Incompatible Changes
  • New Features
  • Improvements
  • Performance
  • Documentation
  • Developers

Highlights

We are excited to announce the release of PyTorch 1.13! This includes stable versions of BetterTransformer. We deprecated CUDA 10.2 and 11.3 and completed migration of CUDA 11.6 and 11.7. Beta includes improved support for Apple M1 chips and functorch, a library that offers composable vmap (vectorization) and autodiff transforms, being included in-tree with the PyTorch release. This release is composed of over 3,749 commits and 467 contributors since 1.12.1. We want to sincerely thank our dedicated community for your contributions.

Summary:

  • The BetterTransformer feature set supports fastpath execution for common Transformer models during Inference out-of-the-box, without the need to modify the model. Additional improvements include accelerated add+matmul linear algebra kernels for sizes commonly used in Transformer models and Nested Tensors is now enabled by default.

  • Timely deprecating older CUDA versions allows us to proceed with introducing the latest CUDA version as they are introduced by Nvidia®, and hence allows support for C++17 in PyTorch and new NVIDIA Open GPU Kernel Modules.

  • Previously, functorch was released out-of-tree in a separate package. After installing PyTorch, a user will be able to import functorch and use functorch without needing to install another package.

  • PyTorch is offering native builds for Apple® silicon machines that use Apple's new M1 chip as a beta feature, providing improved support across PyTorch's APIs.

Stable Beta Prototype
Better TransformerCUDA 10.2 and 11.3 CI/CD Deprecation Enable Intel® VTune™ Profiler's Instrumentation and Tracing Technology APIsExtend NNC to support channels last and bf16Functorch now in PyTorch Core LibraryBeta Support for M1 devices Arm® Compute Library backend support for AWS Graviton CUDA Sanitizer

You can check the blogpost that shows the new features here.

Backwards Incompatible changes

... (truncated)

Changelog

Sourced from torch's changelog.

Releasing PyTorch

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

| PyTorch version | Python | Stable CUDA | Experimental CUDA |

... (truncated)

Commits

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Bumps [torch](https://github.com/pytorch/pytorch) from 1.9.0 to 1.13.1. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/pytorch/pytorch/releases">torch's releases</a>.</em></p> <blockquote> <h2>PyTorch 1.13.1 Release, small bug fix release</h2> <p>This release is meant to fix the following issues (regressions / silent correctness):</p> <ul> <li>RuntimeError by torch.nn.modules.activation.MultiheadAttention with bias=False and batch_first=True <a href="https://redirect.github.com/pytorch/pytorch/issues/88669">#88669</a></li> <li>Installation via pip on Amazon Linux 2, regression <a href="https://redirect.github.com/pytorch/pytorch/issues/88869">#88869</a></li> <li>Installation using poetry on Mac M1, failure <a href="https://redirect.github.com/pytorch/pytorch/issues/88049">#88049</a></li> <li>Missing masked tensor documentation <a href="https://redirect.github.com/pytorch/pytorch/issues/89734">#89734</a></li> <li>torch.jit.annotations.parse_type_line is not safe (command injection) <a href="https://redirect.github.com/pytorch/pytorch/issues/88868">#88868</a></li> <li>Use the Python frame safely in _pythonCallstack <a href="https://redirect.github.com/pytorch/pytorch/issues/88993">#88993</a></li> <li>Double-backward with full_backward_hook causes RuntimeError <a href="https://redirect.github.com/pytorch/pytorch/issues/88312">#88312</a></li> <li>Fix logical error in get_default_qat_qconfig <a href="https://redirect.github.com/pytorch/pytorch/issues/88876">#88876</a></li> <li>Fix cuda/cpu check on NoneType and unit test <a href="https://redirect.github.com/pytorch/pytorch/issues/88854">#88854</a> and <a href="https://redirect.github.com/pytorch/pytorch/issues/88970">#88970</a></li> <li>Onnx ATen Fallback for BUILD_CAFFE2=0 for ONNX-only ops <a href="https://redirect.github.com/pytorch/pytorch/issues/88504">#88504</a></li> <li>Onnx operator_export_type on the new registry <a href="https://redirect.github.com/pytorch/pytorch/issues/87735">#87735</a></li> <li>torchrun AttributeError caused by file_based_local_timer on Windows <a href="https://redirect.github.com/pytorch/pytorch/issues/85427">#85427</a></li> </ul> <p>The <a href="https://redirect.github.com/pytorch/pytorch/issues/89855">release tracker</a> should contain all relevant pull requests related to this release as well as links to related issues</p> <h2>PyTorch 1.13: beta versions of functorch and improved support for Apple’s new M1 chips are now available</h2> <h1>Pytorch 1.13 Release Notes</h1> <ul> <li>Highlights</li> <li>Backwards Incompatible Changes</li> <li>New Features</li> <li>Improvements</li> <li>Performance</li> <li>Documentation</li> <li>Developers</li> </ul> <h1>Highlights</h1> <p>We are excited to announce the release of PyTorch 1.13! This includes stable versions of BetterTransformer. We deprecated CUDA 10.2 and 11.3 and completed migration of CUDA 11.6 and 11.7. Beta includes improved support for Apple M1 chips and functorch, a library that offers composable vmap (vectorization) and autodiff transforms, being included in-tree with the PyTorch release. This release is composed of over 3,749 commits and 467 contributors since 1.12.1. We want to sincerely thank our dedicated community for your contributions.</p> <p>Summary:</p> <ul> <li> <p>The BetterTransformer feature set supports fastpath execution for common Transformer models during Inference out-of-the-box, without the need to modify the model. Additional improvements include accelerated add+matmul linear algebra kernels for sizes commonly used in Transformer models and Nested Tensors is now enabled by default.</p> </li> <li> <p>Timely deprecating older CUDA versions allows us to proceed with introducing the latest CUDA version as they are introduced by Nvidia®, and hence allows support for C++17 in PyTorch and new NVIDIA Open GPU Kernel Modules.</p> </li> <li> <p>Previously, functorch was released out-of-tree in a separate package. After installing PyTorch, a user will be able to <code>import functorch</code> and use functorch without needing to install another package.</p> </li> <li> <p>PyTorch is offering native builds for Apple® silicon machines that use Apple's new M1 chip as a beta feature, providing improved support across PyTorch's APIs.</p> </li> </ul> <table> <thead> <tr> <th>Stable</th> <th>Beta</th> <th>Prototype</th> </tr> </thead> <tbody> <tr> <td><!-- raw HTML omitted --><!-- raw HTML omitted -->Better Transformer<!-- raw HTML omitted --><!-- raw HTML omitted -->CUDA 10.2 and 11.3 CI/CD Deprecation <!-- raw HTML omitted --><!-- raw HTML omitted --></td> <td><!-- raw HTML omitted --><!-- raw HTML omitted -->Enable Intel® VTune™ Profiler's Instrumentation and Tracing Technology APIs<!-- raw HTML omitted --><!-- raw HTML omitted -->Extend NNC to support channels last and bf16<!-- raw HTML omitted --><!-- raw HTML omitted -->Functorch now in PyTorch Core Library<!-- raw HTML omitted --><!-- raw HTML omitted -->Beta Support for M1 devices<!-- raw HTML omitted --><!-- raw HTML omitted --></td> <td><!-- raw HTML omitted --><!-- raw HTML omitted -->Arm® Compute Library backend support for AWS Graviton<!-- raw HTML omitted --><!-- raw HTML omitted --> CUDA Sanitizer<!-- raw HTML omitted --><!-- raw HTML omitted --></td> </tr> </tbody> </table> <p>You can check the blogpost that shows the new features <a href="https://pytorch.org/blog/PyTorch-1.13-release/">here</a>.</p> <h1>Backwards Incompatible changes</h1> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/pytorch/pytorch/blob/main/RELEASE.md">torch's changelog</a>.</em></p> <blockquote> <h1>Releasing PyTorch</h1> <!-- raw HTML omitted --> <ul> <li><a href="https://github.com/pytorch/pytorch/blob/main/#release-compatibility-matrix">Release Compatibility Matrix</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#release-cadence">Release Cadence</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#general-overview">General Overview</a> <ul> <li><a href="https://github.com/pytorch/pytorch/blob/main/#frequently-asked-questions">Frequently Asked Questions</a></li> </ul> </li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#cutting-a-release-branch-preparations">Cutting a release branch preparations</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#cutting-release-branches">Cutting release branches</a> <ul> <li><a href="https://github.com/pytorch/pytorch/blob/main/#pytorchpytorch"><code>pytorch/pytorch</code></a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#pytorchbuilder--pytorch-domain-libraries"><code>pytorch/builder</code> / PyTorch domain libraries</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#making-release-branch-specific-changes-for-pytorch">Making release branch specific changes for PyTorch</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#making-release-branch-specific-changes-for-domain-libraries">Making release branch specific changes for domain libraries</a></li> </ul> </li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#running-launch-execution-team-core-xfn-sync">Running Launch Execution team Core XFN sync</a></li> <li><a href="#drafting-rcs-release-candidates-for-pytorch-and-domain-libraries">Drafting RCs (https://github.com/pytorch/pytorch/blob/main/Release Candidates) for PyTorch and domain libraries</a> 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href="https://github.com/pytorch/pytorch/blob/main/#submitting-tutorials">Submitting Tutorials</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#special-topics">Special Topics</a> <ul> <li><a href="https://github.com/pytorch/pytorch/blob/main/#updating-submodules-for-a-release">Updating submodules for a release</a></li> <li><a href="https://github.com/pytorch/pytorch/blob/main/#triton-dependency-for-the-release">Triton dependency for the release</a></li> </ul> </li> </ul> <!-- raw HTML omitted --> <h2>Release Compatibility Matrix</h2> <p>Following is the Release Compatibility Matrix for PyTorch releases:</p> <p>| PyTorch version | Python | Stable CUDA | Experimental CUDA |</p> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/pytorch/pytorch/commit/49444c3e546bf240bed24a101e747422d1f8a0ee"><code>49444c3</code></a> [BE] Do not package caffe2 in wheel (<a href="https://redirect.github.com/pytorch/pytorch/issues/87986">#87986</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/90433">#90433</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/56de8a39c595777f35e342a7cde9d602d57cca32"><code>56de8a3</code></a> Add manual cuda deps search logic (<a href="https://redirect.github.com/pytorch/pytorch/issues/90411">#90411</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/90426">#90426</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/a4d16e0fb670246f18d8c07396808cd5e3766f0b"><code>a4d16e0</code></a> Fix ATen Fallback for BUILD_CAFFE2=0 for ONNX-only ops (<a href="https://redirect.github.com/pytorch/pytorch/issues/88504">#88504</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/90104">#90104</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/80abad3e7460415efe480ab21c1d5c90fc345a27"><code>80abad3</code></a> Handle Tensor.<strong>deepcopy</strong> via clone(), on IPU (<a href="https://redirect.github.com/pytorch/pytorch/issues/89129">#89129</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/89999">#89999</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/73a852acd7946dff8beb818ec723ffa453e7b242"><code>73a852a</code></a> [Release only change] Fix rocm5.1.1 docker image (<a href="https://redirect.github.com/pytorch/pytorch/issues/90321">#90321</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/029ec163f2b3a7c46ccb3e8d8b377c9319db463a"><code>029ec16</code></a> Add platform markers for linux only extra_install_requires (<a href="https://redirect.github.com/pytorch/pytorch/issues/88826">#88826</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/89924">#89924</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/197c5c0b849cfdb4f6844f90c49bb8adba85e1bb"><code>197c5c0</code></a> Fix cuda/cpu check on NoneType (<a href="https://redirect.github.com/pytorch/pytorch/issues/88854">#88854</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/90068">#90068</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/aadbeb7416e20a9be694f1da415626135c5c1097"><code>aadbeb7</code></a> Make TorchElastic timer importable on Windows (<a href="https://redirect.github.com/pytorch/pytorch/issues/88522">#88522</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/90045">#90045</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/aa9443306a3ba6e8412e24dd99d17eab3f90e818"><code>aa94433</code></a> Mark IPU device as not supports_as_strided (<a href="https://redirect.github.com/pytorch/pytorch/issues/89130">#89130</a>) (<a href="https://redirect.github.com/pytorch/pytorch/issues/89998">#89998</a>)</li> <li><a href="https://github.com/pytorch/pytorch/commit/59b4f3be3bd073b1243e20284fbd09ff43bc66f5"><code>59b4f3b</code></a> Use the Python frame safely in _pythonCallstack (<a href="https://redirect.github.com/pytorch/pytorch/issues/89997">#89997</a>)</li> <li>Additional commits viewable in <a href="https://github.com/pytorch/pytorch/compare/v1.9.0...v1.13.1">compare view</a></li> </ul> </details> <br /> [![Dependabot compatibility score](https://dependabot-badges.githubapp.com/badges/compatibility_score?dependency-name=torch&package-manager=pip&previous-version=1.9.0&new-version=1.13.1)](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores) Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. 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