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[ROCm] Prevent accidental enablement of efficient attention. #133331
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…d_tensors_cuda ROCm's Efficient Attention (GPU kernel shared with FA) is more tolerancing about the inputs.
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/133331
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit e094699 with merge base 89795da ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
BROKEN TRUNK - The following job failed but was present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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@xinyazhang is this read for review? If so, can you please remove draft status |
Yes this is ready. I'll implement your suggestion and move it out of draft status. |
@pytorchbot merge |
Merge failedReason: This PR needs a If not, please add the To add a label, you can comment to pytorchbot, for example For more information, see Details for Dev Infra teamRaised by workflow job |
@pytorchbot label "topic: not user facing" |
@pytorchbot merge |
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@pytorchbot merge -f "Unrelated CI failures. Critical fix needed for 2.4.1" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
@pytorchbot cherry-pick --onto release/2.4 -c critical |
Currently Efficient attention and Flash attention share the same set of GPU kernels on ROCM and have common limitations on head sizes. Fixes #132004 Pull Request resolved: #133331 Approved by: https://github.com/malfet, https://github.com/jithunnair-amd (cherry picked from commit 46ecc67)
Cherry picking #133331The cherry pick PR is at #134531 and it is recommended to link a critical cherry pick PR with an issue. The following tracker issues are updated: Details for Dev Infra teamRaised by workflow job |
[ROCm] Prevent accidental enablement of efficient attention. (#133331) Currently Efficient attention and Flash attention share the same set of GPU kernels on ROCM and have common limitations on head sizes. Fixes #132004 Pull Request resolved: #133331 Approved by: https://github.com/malfet, https://github.com/jithunnair-amd (cherry picked from commit 46ecc67) Co-authored-by: Xinya Zhang <Xinya.Zhang@amd.com>
…#134531) [ROCm] Prevent accidental enablement of efficient attention. (pytorch#133331) Currently Efficient attention and Flash attention share the same set of GPU kernels on ROCM and have common limitations on head sizes. Fixes pytorch#132004 Pull Request resolved: pytorch#133331 Approved by: https://github.com/malfet, https://github.com/jithunnair-amd (cherry picked from commit 46ecc67) Co-authored-by: Xinya Zhang <Xinya.Zhang@amd.com>
…#134531) (#1565) [ROCm] Prevent accidental enablement of efficient attention. (pytorch#133331) Currently Efficient attention and Flash attention share the same set of GPU kernels on ROCM and have common limitations on head sizes. Pull Request resolved: pytorch#133331 Approved by: https://github.com/malfet, https://github.com/jithunnair-amd (cherry picked from commit 46ecc67) Fixes pytorch#132004 Co-authored-by: pytorchbot <soumith+bot@pytorch.org>
…#133331) Currently Efficient attention and Flash attention share the same set of GPU kernels on ROCM and have common limitations on head sizes. Fixes pytorch#132004 Pull Request resolved: pytorch#133331 Approved by: https://github.com/malfet, https://github.com/jithunnair-amd
Currently Efficient attention and Flash attention share the same set of GPU
kernels on ROCM and have common limitations on head sizes.
Fixes #132004
cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang