Use TensorMeta to check if inputs and outputs are memory planned #5565
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Summary: Swap to using method meta so we can be finer grained about this check Reviewed By: dbort Differential Revision: D62983475
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/5565
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 253b136 with merge base 8be3ce5 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This pull request was exported from Phabricator. Differential Revision: D62983475 |
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This pull request has been merged in df72b8c. |
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@pytorchbot cherry-pick --onto release/0.4 -c fixnewfeature |
Cherry picking #5565The cherry pick PR is at #6114 and it is recommended to link a fixnewfeature cherry pick PR with an issue. The following tracker issues are updated: Details for Dev Infra teamRaised by workflow job |
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Use TensorMeta to check if inputs and outputs are memory planned (#5565) Summary: Pull Request resolved: #5565 Swap to using method meta so we can be finer grained about this check Reviewed By: dbort Differential Revision: D62983475 fbshipit-source-id: c4599c5ecad0409cd8b2670464c4e9e8809b49ad (cherry picked from commit df72b8c) Co-authored-by: Jacob Szwejbka <jakeszwe@meta.com>
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Summary: Swap to using method meta so we can be finer grained about this check
Reviewed By: dbort
Differential Revision: D62983475