[DTensor][Bug Fix]Fix 2D DTensor mm with mesh_shape (1, n) or (n, 1) #139134
Conversation
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
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/139134
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit e012ff9 with merge base 7c7b2d8 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
pytorch-bot
bot
added
the
oncall: distributed
wz337
added
module: dtensor
wz337
changed the title
wz337
changed the title
|
@pytorchmergebot rebase |
|
@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
|
Successfully rebased |
|
The failing tests looks legit. We should fix them first. |
Seems there are some issues when using "gloo" backend. So just skip the non gpu tests now and will follow up by looking into DTensorTestbase. |
kwen2501
reviewed
Oct 29, 2024
Comment on lines
+354
to
+356
| mesh_0 = init_device_mesh(self.device_type, (self.world_size // 2, 2)) | ||
| mesh_1 = init_device_mesh(self.device_type, (self.world_size, 1)) | ||
| mesh_2 = init_device_mesh(self.device_type, (1, self.world_size)) |
There was a problem hiding this comment.
nit: better to put init_device_mesh in the loop?
fegin
approved these changes
Oct 30, 2024
|
@pytorchmergebot 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 |
rahulsingh-intel
pushed a commit
to rahulsingh-intel/pytorch
that referenced
this pull request
Nov 5, 2024
…ytorch#139134) Fixes pytorch#138742. In the issue, the matrix multiplication with DTensor failed when the size of one of mesh dimension is 1 when the mesh is > 1D. We are missing tests for covering this corner case where mesh_shape is (n, 1) or (1, n). The DTensor mm op is correct when the 1D mesh is of shape (self.world_size, ) or 2D mesh with none of the mesh_dimension has a size of 1. In this PR, we fixed the corner case by updating `gen_einsum_strategies` in `_einsum_strategy.py`. Specifically, we cannot skip generating `mesh_dim_strategies` when `mesh_dim <= 1`, as this is not valid for nD mesh with one of the mesh dimension sizes being 1. Without the fix, the OpStrategy generated for 2D mesh with mesh_shape of (1,n) or (n,1) is wrong, as the OpStrategy generated is 1D. ``` all_mesh_dim_strategies=[[[Replicate(), Replicate(), Replicate()], [Partial(sum), Shard(dim=1), Shard(dim=0)], [Shard(dim=0), Shard(dim=0), Replicate()], [Shard(dim=1), Replicate(), Shard(dim=1)]]] OpStrategy(all_strategies)::: [(R, R) -> R, (S(1), S(0)) -> P, (S(0), R) -> S(0), (R, S(1)) -> S(1)] @ mesh: (4, 1)[(R, R) -> R, (S(1), S(0)) -> P, (S(0), R) -> S(0), (R, S(1)) -> S(1)] @ mesh: (4, 1) ``` After the fix, we can see the OpStrategy generated is correct with 2D strategy. ``` all_mesh_dim_strategies=[[[Replicate(), Replicate(), Replicate()], [Partial(sum), Shard(dim=1), Shard(dim=0)], [Shard(dim=0), Shard(dim=0), Replicate()], [Shard(dim=1), Replicate(), Shard(dim=1)]]][[[Replicate(), Replicate(), Replicate()], [Partial(sum), Shard(dim=1), Shard(dim=0)], [Shard(dim=0), Shard(dim=0), Replicate()], [Shard(dim=1), Replicate(), Shard(dim=1)]]] OpStrategy(all_strategies) = [(RR, RR) -> RR, (RS(1), RS(0)) -> RP, (RS(0), RR) -> RS(0), (RR, RS(1)) -> RS(1), (S(1)R, S(0)R) -> PR, (S(1)S(1), S(0)S(0)) -> PP, (S(1)S(0), S(0)R) -> PS(0), (S(1)R, S(0)S(1)) -> PS(1), (S(0)R, RR) -> S(0)R, (S(0)S(1), RS(0)) -> S(0)P, (S(0)S(0), RR) -> S(0)S(0), (S(0)R, RS(1)) -> S(0)S(1), (RR, S(1)R) -> S(1)R, (RS(1), S(1)S(0)) -> S(1)P, (RS(0), S(1)R) -> S(1)S(0), (RR, S(1)S(1)) -> S(1)S(1)] @ mesh: (4, 1) ``` ******* As a follow up, we should add more test coverage for DTensor op with 2D mesh and 2D mesh with one of the size of mesh dimension being 1. ******* Pull Request resolved: pytorch#139134 Approved by: https://github.com/fegin
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
4 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):
Fixes #138742. In the issue, the matrix multiplication with DTensor failed when the size of one of mesh dimension is 1 when the mesh is > 1D. We are missing tests for covering this corner case where mesh_shape is (n, 1) or (1, n). The DTensor mm op is correct when the 1D mesh is of shape (self.world_size, ) or 2D mesh with none of the mesh_dimension has a size of 1.
In this PR, we fixed the corner case by updating
gen_einsum_strategiesin_einsum_strategy.py. Specifically, we cannot skip generatingmesh_dim_strategieswhenmesh_dim <= 1, as this is not valid for nD mesh with one of the mesh dimension sizes being 1.Without the fix, the OpStrategy generated for 2D mesh with mesh_shape of (1,n) or (n,1) is wrong, as the OpStrategy generated is 1D.
After the fix, we can see the OpStrategy generated is correct with 2D strategy.
As a follow up, we should add more test coverage for DTensor op with 2D mesh and 2D mesh with one of the size of mesh dimension being 1.
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wconstab @d4l3k @c-p-i-o @tianyu-l @XilunWu