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Skip on sm100 later since Tests are non determinisitic (#163552)

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This is tracked https://github.com/pytorch/pytorch/issues/163462

skipping since we are seeing sporadic errors locally and on CI,
Pull Request resolved: https://github.com/pytorch/pytorch/pull/163552
Approved by: https://github.com/eqy, https://github.com/Skylion007
ghstack dependencies: #163460, #163537
This commit is contained in:
drisspg 2025-09-22 23:04:57 +00:00 committed by PyTorch MergeBot
parent 0f674077f4
commit b3cf5c79dd
1 changed files with 1 additions and 2 deletions
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test/test_matmul_cuda.py
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@ -515,13 +515,12 @@ class TestMatmulCuda(InductorTestCase):
@unittest.skipIf(TEST_WITH_ROCM, "ROCm doesn't support CUTLASS")
# TODO(future PR): enable compile for torch._grouped_mm fallback path
@unittest.skipIf(not SM90OrLater, "Grouped gemm with compile supported on SM90")
@unittest.skipIf(SM100OrLater, "Grouped gemm is inconsistently raising numeric issues see: #163462 ")
@parametrize("op", ["2d/2d", "2d/3d", "3d/2d", "3d/3d"])
@parametrize("a_row_major", [False, True])
@parametrize("b_row_major", [False, True])
@parametrize("max_autotune", [False, True])
def test_grouped_gemm_compiled(self, op, a_row_major, b_row_major, max_autotune):
if max_autotune and SM100OrLater:
self.skipTest("Triton templates not supported on SM100+ for grouped_mm")
device = "cuda"
dtype_AB = torch.bfloat16
dtype_offset = torch.int32