Fix reduction + () + multi-level reduction optimization #111781
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/111781
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit a36e87a with merge base c65c068 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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malfet
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Oct 23, 2023
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@ipiszy please note that mypy failures seems relevant, if you want to suppress those, please add an assert |
jansel
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Oct 23, 2023
In #111122, an optimization is introduced for reduction() + () + multi-level reduction. In this case, we make a multi-level reduction first-level reduction ranges the same as the previous reduction ranges so that the Inductor has better chances to fuse the first reduction and the first-level reduction of the multi-level reduction kernel together. There is a corner case that the multi-level reduction kernel has `keepdim=True`. In this case, ranges of the multi-level reduction kernel is not empty, and the dim info needs to be used to create the inner loader of the first-level reduction kernel. To keep the logic simple, for now we simply disable optimization when `keepdim=True`. Differential Revision: [D50544876](https://our.internmc.facebook.com/intern/diff/D50544876) [ghstack-poisoned]
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Summary: In #111122, an optimization is introduced for reduction() + () + multi-level reduction. In this case, we make a multi-level reduction first-level reduction ranges the same as the previous reduction ranges so that the Inductor has better chances to fuse the first reduction and the first-level reduction of the multi-level reduction kernel together. There is a corner case that the multi-level reduction kernel has `keepdim=True`. In this case, ranges of the multi-level reduction kernel is not empty, and the dim info needs to be used to create the inner loader of the first-level reduction kernel. To keep the logic simple, for now we simply disable optimization when `keepdim=True`. imported-using-ghimport Test Plan: Imported from OSS Reviewed By: malfet Differential Revision: D50544876 Pulled By: ipiszy
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In pytorch#111122, an optimization is introduced for reduction() + () + multi-level reduction. In this case, we make a multi-level reduction first-level reduction ranges the same as the previous reduction ranges so that the Inductor has better chances to fuse the first reduction and the first-level reduction of the multi-level reduction kernel together. There is a corner case that the multi-level reduction kernel has `keepdim=True`. In this case, ranges of the multi-level reduction kernel is not empty, and the dim info needs to be used to create the inner loader of the first-level reduction kernel. To keep the logic simple, for now we simply disable optimization when `keepdim=True`. Differential Revision: [D50544876](https://our.internmc.facebook.com/intern/diff/D50544876) Pull Request resolved: pytorch#111781 Approved by: https://github.com/malfet, https://github.com/jansel
Skylion007
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Nov 14, 2023
In pytorch#111122, an optimization is introduced for reduction() + () + multi-level reduction. In this case, we make a multi-level reduction first-level reduction ranges the same as the previous reduction ranges so that the Inductor has better chances to fuse the first reduction and the first-level reduction of the multi-level reduction kernel together. There is a corner case that the multi-level reduction kernel has `keepdim=True`. In this case, ranges of the multi-level reduction kernel is not empty, and the dim info needs to be used to create the inner loader of the first-level reduction kernel. To keep the logic simple, for now we simply disable optimization when `keepdim=True`. Differential Revision: [D50544876](https://our.internmc.facebook.com/intern/diff/D50544876) Pull Request resolved: pytorch#111781 Approved by: https://github.com/malfet, https://github.com/jansel
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In #111122, an optimization is introduced for reduction() + () + multi-level reduction. In this case, we make a multi-level reduction first-level reduction ranges the same as the previous reduction ranges so that the Inductor has better chances to fuse the first reduction and the first-level reduction of the multi-level reduction kernel together.
There is a corner case that the multi-level reduction kernel has
keepdim=True. In this case, ranges of the multi-level reduction kernel is not empty, and the dim info needs to be used to create the inner loader of the first-level reduction kernel. To keep the logic simple, for now we simply disable optimization whenkeepdim=True.Stack from ghstack (oldest at bottom):
Differential Revision: D50544876
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