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[CPU SDP] Remove mem efficient attn checks in CPU #112375
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It doesn't seem like memory efficient attention can be used on CPU, as we don't check for it when iterating backends in `select_sdp_backend_cpp`. So removing some of the logic around mem efficient attention. Created from CodeHub with https://fburl.com/edit-in-codehub Differential Revision: [D50775562](https://our.internmc.facebook.com/intern/diff/D50775562/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D50775562/)! [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/112375
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 2e774d4 with merge base a26cb0a (): This comment was automatically generated by Dr. CI and updates every 15 minutes. |
It doesn't seem like memory efficient attention can be used on CPU, as we don't check for it when iterating backends in `select_sdp_backend_cpp`. So removing some of the logic around mem efficient attention. Created from CodeHub with https://fburl.com/edit-in-codehub Differential Revision: [D50775562](https://our.internmc.facebook.com/intern/diff/D50775562/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D50775562/)! ghstack-source-id: 205746438 Pull Request resolved: #112375
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Thanks!
@pytorchbot merge -f "CI done" |
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 |
It doesn't seem like memory efficient attention can be used on CPU, as we don't check for it when iterating backends in `select_sdp_backend_cpp`. So removing some of the logic around mem efficient attention selection. Created from CodeHub with https://fburl.com/edit-in-codehub Differential Revision: [D50775562](https://our.internmc.facebook.com/intern/diff/D50775562/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D50775562/)! Pull Request resolved: pytorch#112375 Approved by: https://github.com/drisspg
It doesn't seem like memory efficient attention can be used on CPU, as we don't check for it when iterating backends in `select_sdp_backend_cpp`. So removing some of the logic around mem efficient attention selection. Created from CodeHub with https://fburl.com/edit-in-codehub Differential Revision: [D50775562](https://our.internmc.facebook.com/intern/diff/D50775562/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D50775562/)! Pull Request resolved: pytorch#112375 Approved by: https://github.com/drisspg
It doesn't seem like memory efficient attention can be used on CPU, as we don't check for it when iterating backends in `select_sdp_backend_cpp`. So removing some of the logic around mem efficient attention selection. Created from CodeHub with https://fburl.com/edit-in-codehub Differential Revision: [D50775562](https://our.internmc.facebook.com/intern/diff/D50775562/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D50775562/)! Pull Request resolved: pytorch#112375 Approved by: https://github.com/drisspg
Stack from ghstack (oldest at bottom):
It doesn't seem like memory efficient attention can be used on CPU, as we don't check for it when iterating backends in
select_sdp_backend_cpp
. So removing some of the logic around mem efficient attention selection.Created from CodeHub with https://fburl.com/edit-in-codehub
Differential Revision: D50775562
NOTE FOR REVIEWERS: This PR has internal Meta-specific changes or comments, please review them on Phabricator!