test only smaller block_k for mm_plus_mm #96385
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/96385
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torch/_inductor/kernel/mm_plus_mm.py
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| # Splitting this into two loops causes an internal triton LLVM error | ||
| # https://github.com/openai/triton/issues/967 |
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This comment is stale now, right?
torch/_inductor/kernel/mm_plus_mm.py
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| # rematerialize rm and rn to save registers | ||
| rm = pid_m * BLOCK_M + tl.arange(0, BLOCK_M) | ||
| rn = pid_n * BLOCK_N + tl.arange(0, BLOCK_N) | ||
| #rm = pid_m * BLOCK_M + tl.arange(0, BLOCK_M) | ||
| #rn = pid_n * BLOCK_N + tl.arange(0, BLOCK_N) |
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Is this rematerialization a bad idea now, or is it temporary? Probably we should either delete it (or drop in a comment describing why it's temporary).
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Didn't see any difference with or without, deleted
torch/_inductor/kernel/mm_plus_mm.py
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| (mat1, mat2, mat3, mat4), | ||
| layout, | ||
| **mm_options(config, k, layout), | ||
| if config.kwargs['BLOCK_K'] < k: |
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Maybe add a comment with a pointer to the triton issue so we can revisit someday.
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@pytorchbot merge -f "dla102 test flaky" |
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Trim number of tested mm_plus_mm configs to work around triton-lang/triton#1298 Pull Request resolved: pytorch#96385 Approved by: https://github.com/bertmaher, https://github.com/jansel
Trim number of tested mm_plus_mm configs to work around triton-lang/triton#1298 Pull Request resolved: pytorch/pytorch#96385 Approved by: https://github.com/bertmaher, https://github.com/jansel
Trim number of tested mm_plus_mm configs to work around triton-lang/triton#1298 Pull Request resolved: pytorch#96385 Approved by: https://github.com/bertmaher, https://github.com/jansel
Trim number of tested mm_plus_mm configs to work around triton-lang/triton#1298
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