[Inductor] Expose decomposeK knobs as envvars#158745
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PaulZhang12 wants to merge 5 commits intogh/PaulZhang12/19/basefrom
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[Inductor] Expose decomposeK knobs as envvars#158745PaulZhang12 wants to merge 5 commits intogh/PaulZhang12/19/basefrom
PaulZhang12 wants to merge 5 commits intogh/PaulZhang12/19/basefrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/158745
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit b04da7e with merge base 8e57cdb ( UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy chenyang78 kadeng muchulee8 amjames chauhang aakhundov coconutruben [ghstack-poisoned]
Fix up decomposeK autotuning, by removing condition to return more than `k_splits_limit` and setting default to 10 instead of 5. Allow `k_splits_limit` to be configurable to the user via `TORCHINDUCTOR_NUM_DECOMPOSE_K_SPLITS` and also allow user to configure threshold in which to use decompose_k via `TORCHINDUCTOR_DECOMPOSE_K_THRESHOLD` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy chenyang78 kadeng muchulee8 amjames chauhang aakhundov coconutruben [ghstack-poisoned]
eellison
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Jul 21, 2025
Fix up decomposeK autotuning, by removing condition to return more than `k_splits_limit` and setting default to 10 instead of 5. Allow `k_splits_limit` to be configurable to the user via `TORCHINDUCTOR_NUM_DECOMPOSE_K_SPLITS` and also allow user to configure threshold in which to use decompose_k via `TORCHINDUCTOR_DECOMPOSE_K_THRESHOLD` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy chenyang78 kadeng muchulee8 amjames chauhang aakhundov coconutruben [ghstack-poisoned]
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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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Jul 22, 2025
Fix up decomposeK autotuning, by removing condition to return more than `k_splits_limit` and setting default to 10 instead of 5. Allow `k_splits_limit` to be configurable to the user via `TORCHINDUCTOR_NUM_DECOMPOSE_K_SPLITS` and also allow user to configure threshold in which to use decompose_k via `TORCHINDUCTOR_DECOMPOSE_K_THRESHOLD` Pull Request resolved: pytorch#158745 Approved by: https://github.com/eellison
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@pytorchbot revert -c nosignal -m "sorry but rocm CI is broken due to this PR" |
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@pytorchbot successfully started a revert job. Check the current status here. |
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Jul 22, 2025
This reverts commit eac777c. Reverted #158745 on behalf of https://github.com/jeffdaily due to sorry but rocm CI is broken due to this PR ([comment](#158745 (comment)))
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@PaulZhang12 your PR has been successfully reverted. |
Fix up decomposeK autotuning, by removing condition to return more than `k_splits_limit` and setting default to 10 instead of 5. Allow `k_splits_limit` to be configurable to the user via `TORCHINDUCTOR_NUM_DECOMPOSE_K_SPLITS` and also allow user to configure threshold in which to use decompose_k via `TORCHINDUCTOR_DECOMPOSE_K_THRESHOLD` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy chenyang78 kadeng muchulee8 amjames chauhang aakhundov coconutruben [ghstack-poisoned]
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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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Fix up decomposeK autotuning, by removing condition to return more than
k_splits_limitand setting default to 10 instead of 5. Allowk_splits_limitto be configurable to the user viaTORCHINDUCTOR_NUM_DECOMPOSE_K_SPLITSand also allow user to configure threshold in which to use decompose_k viaTORCHINDUCTOR_DECOMPOSE_K_THRESHOLDcc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @coconutruben