[Inductor] support masked vectorization for the tail_loop for INT8 datatype#131155
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jiayisunx wants to merge 11 commits intogh/jiayisunx/15/basefrom
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[Inductor] support masked vectorization for the tail_loop for INT8 datatype#131155jiayisunx wants to merge 11 commits intogh/jiayisunx/15/basefrom
jiayisunx wants to merge 11 commits intogh/jiayisunx/15/basefrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/131155
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 31e3345 with merge base dc00eeb ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
jgong5
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Jul 24, 2024
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Please explain in the PR description why you need to change it.
leslie-fang-intel
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Jul 24, 2024
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@jansel , could you please review this PR? Thanks! |
jansel
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Aug 12, 2024
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@pytorchbot merge |
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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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Stack from ghstack (oldest at bottom):
This PR supports masked vectorization for the tail_loop for torch.uint8 and torch.int8 datatype to improve performance.
BTW, I fixed the UT of
byteby setting the range of the sample inputs to [0, 255] since the range oftorch.uint8is [0, 255].cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang