Use temp allocator for kernel registry #13012
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/13012
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 2 New Failures, 1 Unrelated FailureAs of commit c831756 with merge base 90ff059 ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Differential Revision: D79285675
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Differential Revision: D79285675
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Summary: Pull Request resolved: pytorch#13012 When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Differential Revision: D79285675
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: Pull Request resolved: pytorch#13012 When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: Pull Request resolved: pytorch#13012 When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: Pull Request resolved: pytorch#13012 When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Summary: Pull Request resolved: pytorch#13012 When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Reviewed By: larryliu0820 Differential Revision: D79285675
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Failing tests pre-existing. moshi from undefined libtorchaudio symbol, openvino from backend import. Landing. |
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed. Differential Revision: D79285675 cc @larryliu0820 @JacobSzwejbka @lucylq
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Summary: When indexing to the registry to get the op, memory is allocated from the method allocator to instantiate some TensorMeta and included objects. This memory is only used for that purpose and is not needed for the entire lifetime of the Method. Thus, we can instead use temp allocator which can later be reset and free up memory as needed.
Differential Revision: D79285675
cc @larryliu0820 @JacobSzwejbka @lucylq