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update torch.nn.RelicationPad{1,2,3}d deternimistic documentation #148633
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/148633
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (6 Unrelated Failures)As of commit b12c9a5 with merge base bc88f6f ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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@isuruf Could you help me merge it? |
@malfet Could you help me merge it? |
@colesbury Could you help me merge it? |
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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@pytorchbot merge |
Pull workflow has not been scheduled for the PR yet. It could be because author doesn't have permissions to run those or skip-checks keywords were added to PR/commits, aborting merge. Please get/give approval for the workflows and/or remove skip ci decorators before next merge attempt. If you think this is a mistake, please contact PyTorch Dev Infra. |
@colesbury Could you help me merge it? |
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 mandatory check(s) failed. The first few are: Dig deeper by viewing the failures on hud |
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
…torch#148633) pytorch#115395 This issue mentioned that when deterministic mode is turned on, added a decomp for replication_pad_{1,2,3}d to make the backward function deterministic. @malfet Pull Request resolved: pytorch#148633 Approved by: https://github.com/isuruf
#115395
This issue mentioned that when deterministic mode is turned on, added a decomp for replication_pad_{1,2,3}d
to make the backward function deterministic.
@malfet