inductor: remove duplicate triton configs for autotuning #142254
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/142254
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (3 Unrelated Failures)As of commit 5cc9e03 with merge base 960a81f ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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) Summary: # Why - sampling the same config multiple times is wasteful, especially on exhaustive - for AMD we rewrite the configs to have a specific number of stages, which might lead to some configs appearing multiple times # What cast the configs, already defined as a tuple, through a set to remove duplicates Test Plan: taken from the `mm_kernel_configs` logic in the same file ``` >>> mm_kernel_configs = [ {"config": (BLOCK_M, BLOCK_N, BLOCK_K, num_stages, num_warps), "cond": True} for BLOCK_M, BLOCK_N, BLOCK_K in itertools.product( [16, 32, 64, 128, 256], repeat=3 ) for num_stages in [1, 2, 3, 4, 5] for num_warps in [2, 4, 8] ] >>> configs = [c['config'] for c in mm_kernel_configs] >>> a = tuple((c[0], c[1], c[2], 0, c[4]) for c in configs) >>> len(set(a)) 375 >>> len(a) 1875 >>> ``` Differential Revision: D66893774
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) Summary: # Why - sampling the same config multiple times is wasteful, especially on exhaustive - for AMD we rewrite the configs to have a specific number of stages, which might lead to some configs appearing multiple times # What cast the configs, already defined as a tuple, through a set to remove duplicates Test Plan: taken from the `mm_kernel_configs` logic in the same file ``` >>> mm_kernel_configs = [ {"config": (BLOCK_M, BLOCK_N, BLOCK_K, num_stages, num_warps), "cond": True} for BLOCK_M, BLOCK_N, BLOCK_K in itertools.product( [16, 32, 64, 128, 256], repeat=3 ) for num_stages in [1, 2, 3, 4, 5] for num_warps in [2, 4, 8] ] >>> configs = [c['config'] for c in mm_kernel_configs] >>> a = tuple((c[0], c[1], c[2], 0, c[4]) for c in configs) >>> len(set(a)) 375 >>> len(a) 1875 >>> ``` Differential Revision: D66893774
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) Summary: # Why - sampling the same config multiple times is wasteful, especially on exhaustive - for AMD we rewrite the configs to have a specific number of stages, which might lead to some configs appearing multiple times # What cast the configs, already defined as a tuple, through a set to remove duplicates Test Plan: taken from the `mm_kernel_configs` logic in the same file ``` >>> mm_kernel_configs = [ {"config": (BLOCK_M, BLOCK_N, BLOCK_K, num_stages, num_warps), "cond": True} for BLOCK_M, BLOCK_N, BLOCK_K in itertools.product( [16, 32, 64, 128, 256], repeat=3 ) for num_stages in [1, 2, 3, 4, 5] for num_warps in [2, 4, 8] ] >>> configs = [c['config'] for c in mm_kernel_configs] >>> a = tuple((c[0], c[1], c[2], 0, c[4]) for c in configs) >>> len(set(a)) 375 >>> len(a) 1875 >>> ``` Differential Revision: D66893774
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@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
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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Summary:
Why
What
cast the configs, already defined as a tuple, through a set to remove duplicates
Test Plan:
taken from the
mm_kernel_configslogic in the same fileDifferential Revision: D66893774
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov