build(learning): bump torch from 1.13 to 1.13.1 in /python #3264
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Bumps [torch](https://github.com/pytorch/pytorch) from 1.13 to 1.13.1. - [Release notes](https://github.com/pytorch/pytorch/releases) - [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md) - [Commits](pytorch/pytorch@v1.13.0...v1.13.1) --- updated-dependencies: - dependency-name: torch dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com>
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LiSu
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LiSu
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I suggest we don't include pytorch in the requirements.txt, as what the user actually want may not be the version fetched using pip (e.g., they may require (or already have) a GPU-enabled variant). Like tensorflow, we could raise warnings or leave a note in the documentation to tell users to install pytorch properly. Or, we could have a profile like Besides, pin to a certain version of pytorch may causing issues in the user side as well, considering pytorch APIs are fairly stable, could we have something like |
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Bumps torch from 1.13 to 1.13.1.
Release notes
Sourced from torch's releases.
Changelog
Sourced from torch's changelog.
... (truncated)
Commits
49444c3[BE] Do not package caffe2 in wheel (#87986) (#90433)56de8a3Add manual cuda deps search logic (#90411) (#90426)a4d16e0Fix ATen Fallback for BUILD_CAFFE2=0 for ONNX-only ops (#88504) (#90104)80abad3Handle Tensor.deepcopy via clone(), on IPU (#89129) (#89999)73a852a[Release only change] Fix rocm5.1.1 docker image (#90321)029ec16Add platform markers for linux only extra_install_requires (#88826) (#89924)197c5c0Fix cuda/cpu check on NoneType (#88854) (#90068)aadbeb7Make TorchElastic timer importable on Windows (#88522) (#90045)aa94433Mark IPU device as not supports_as_strided (#89130) (#89998)59b4f3bUse the Python frame safely in _pythonCallstack (#89997)Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
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