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[ML] Upgrade to PyTorch 2.3.1 #2688
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Update Docker images and dependecy files with PyTorch 2.3.1. Testing on Linux x86_64 gives promising indications that this version of PyTorch may resolve some memory allocation issues related to the `pytorch_inference` process. Opening this PR to better test it across the range of platforms and architectures that we support.
Compilation errors for the macOS intel cross compilation build are due to a (now) too old compiler version
and for the macOS aarch64 build there's a problem with |
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LGTM. Just some minor suggestions.
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(cd ${REPO_ROOT} && ./gradlew --info -Dbuild.version_qualifier=${VERSION_QUALIFIER:-} -Dbuild.snapshot=$BUILD_SNAPSHOT -Dbuild.ml_debug=$ML_DEBUG $TASKS) || TEST_OUTCOME=$? | ||
(cd ${REPO_ROOT} && ./gradlew --info -Dbuild.version_qualifier=${VERSION_QUALIFIER:-} -Dbuild.snapshot=$BUILD_SNAPSHOT -Dbuild.ml_debug=$ML_DEBUG $TASKS) || TEST_OUTCOME=$? | ||
else |
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Is this the branch for testing Windows? If so, maybe you can add a comment so we can find our way around this file more easily in the future.
Co-authored-by: Valeriy Khakhutskyy <1292899+valeriy42@users.noreply.github.com>
Update Docker images and dependency files with PyTorch 2.3.1. Testing on Linux x86_64 gives promising indications that this version of PyTorch may resolve some memory allocation issues related to the `pytorch_inference` process. Co-authored-by: Valeriy Khakhutskyy <1292899+valeriy42@users.noreply.github.com>
…#2705) Release notes need updating following backport of PyTorch 2.3.1 changes to 8.15.1
…#2705) Release notes need updating following backport of PyTorch 2.3.1 changes to 8.15.1
Update Docker images and dependency files with PyTorch 2.3.1. Testing on Linux x86_64 gives promising indications that this version of PyTorch may resolve some memory allocation issues related to the `pytorch_inference` process. Co-authored-by: Valeriy Khakhutskyy <1292899+valeriy42@users.noreply.github.com> Backports #2688
Update Docker images and dependency files with PyTorch 2.3.1.
Testing on Linux x86_64 gives promising indications that this version of
PyTorch may resolve some memory allocation issues related to the
pytorch_inference
process.Opening this PR to better test it across the range of platforms and
architectures that we support.