[DTensor] layernorm output meta#175652
Closed
pianpwk wants to merge 2 commits intogh/pianpwk/100/basefrom
Closed
Conversation
[ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/175652
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit 1733897 with merge base e81980e ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
This comment was automatically generated by Dr. CI and updates every 15 minutes. |
[ghstack-poisoned]
wconstab
approved these changes
Feb 25, 2026
Contributor
Author
|
@pytorchbot merge |
Collaborator
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 |
Collaborator
|
The merge job was canceled or timed out. This most often happen if two merge requests were issued for the same PR, or if merge job was waiting for more than 6 hours for tests to finish. In later case, please do not hesitate to reissue the merge command |
Contributor
Author
|
@pytorchbot merge |
Collaborator
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 |
postmath
pushed a commit
to postmath/pytorch
that referenced
this pull request
Feb 26, 2026
autoparallel has its own layernorm fwd/bwd registrations, because pytorch's version reports the wrong tensor meta for (out, mean, rstd), by coping out's meta to all 3. This creates separate metas for each. The other issue is layernorm always produces contiguous outputs - fixes this too. https://github.com/meta-pytorch/autoparallel/blob/454780d2a27456a380c0d8e997c8fc2cf82ef5d8/autoparallel/shardings/propagation_rules.py#L460-L611 Pull Request resolved: pytorch#175652 Approved by: https://github.com/wconstab
sandy-gags
pushed a commit
to sandy-gags/pytorch
that referenced
this pull request
Mar 12, 2026
ghstack-source-id: d09bfc5 Pull Request resolved: pytorch/pytorch#175652
pianpwk
added a commit
to pianpwk/autoparallel
that referenced
this pull request
Mar 18, 2026
…_layer_norm, and native_layer_norm_backward These three rules were carried as local overrides in autoparallel while upstream PyTorch lacked proper handling: - constant_pad_nd: non-replicate strategy filtering on padded dims (upstreamed in pytorch/pytorch#175656) - native_layer_norm forward: correct per-output shapes and contiguous strides (upstreamed in pytorch/pytorch#175652) - native_layer_norm backward: contiguous stride handling for grad_input (upstreamed in a companion PR to pytorch/pytorch) With all three fixes now in upstream PyTorch, the overrides can be removed and autoparallel defers to the upstream register_op_strategy implementations. Authored with Claude.
EmanueleCoradin
pushed a commit
to EmanueleCoradin/pytorch
that referenced
this pull request
Mar 30, 2026
autoparallel has its own layernorm fwd/bwd registrations, because pytorch's version reports the wrong tensor meta for (out, mean, rstd), by coping out's meta to all 3. This creates separate metas for each. The other issue is layernorm always produces contiguous outputs - fixes this too. https://github.com/meta-pytorch/autoparallel/blob/454780d2a27456a380c0d8e997c8fc2cf82ef5d8/autoparallel/shardings/propagation_rules.py#L460-L611 Pull Request resolved: pytorch#175652 Approved by: https://github.com/wconstab
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Stack from ghstack (oldest at bottom):
autoparallel has its own layernorm fwd/bwd registrations, because pytorch's version reports the wrong tensor meta for (out, mean, rstd), by coping out's meta to all 3. This creates separate metas for each.
The other issue is layernorm always produces contiguous outputs - fixes this too.
https://github.com/meta-pytorch/autoparallel/blob/454780d2a27456a380c0d8e997c8fc2cf82ef5d8/autoparallel/shardings/propagation_rules.py#L460-L611