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[B200][MXFP8] Fix regex in test_blockwise_mxfp8_nvfp4_error_messages_recipe_mxfp8_cuda (#162180)

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to unblock https://github.com/pytorch/pytorch/pull/159494

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162180
Approved by: https://github.com/Skylion007, https://github.com/drisspg, https://github.com/nWEIdia
This commit is contained in:
Eddie Yan 2025-09-04 23:29:10 +00:00 committed by PyTorch MergeBot
parent 9499c8761c
commit c7e41071a0
1 changed files with 8 additions and 11 deletions
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19
test/test_matmul_cuda.py
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@ -1799,10 +1799,9 @@ class TestFP8Matmul(TestCase):
# Test wrong scale tensor size for scale_a with correct dtype # Test wrong scale tensor size for scale_a with correct dtype
with self.assertRaisesRegex( with self.assertRaisesRegex(
RuntimeError, RuntimeError,
re.escape( f".*For Block[W,w]ise.*scaling.*scale_a should have {expected_a_size} "
f"For BlockWise scaling: Expected scale_a size to be {expected_a_size} " f"elements.*"
f"but got {expected_a_size - 1}" ,
),
): ):
incorrect_size_a = torch.ones(expected_a_size - 1, device=device, dtype=scale_dtype) incorrect_size_a = torch.ones(expected_a_size - 1, device=device, dtype=scale_dtype)
correct_size_b = torch.ones(expected_b_size, device=device, dtype=scale_dtype) correct_size_b = torch.ones(expected_b_size, device=device, dtype=scale_dtype)
@ -1817,10 +1816,9 @@ class TestFP8Matmul(TestCase):
# Test wrong scale tensor size for scale_b with correct dtype # Test wrong scale tensor size for scale_b with correct dtype
with self.assertRaisesRegex( with self.assertRaisesRegex(
RuntimeError, RuntimeError,
re.escape( f"For Block[W,w]ise.*scaling.*scale_b should have {expected_b_size} "
f"For BlockWise scaling: Expected scale_b size to be {expected_b_size} " f"elements.*"
f"but got {expected_b_size + 1}" ,
),
): ):
correct_size_a = torch.ones(expected_a_size, device=device, dtype=scale_dtype) correct_size_a = torch.ones(expected_a_size, device=device, dtype=scale_dtype)
incorrect_size_b = torch.ones(expected_b_size + 1, device=device, dtype=scale_dtype) incorrect_size_b = torch.ones(expected_b_size + 1, device=device, dtype=scale_dtype)
@ -1835,9 +1833,8 @@ class TestFP8Matmul(TestCase):
# Test non-contiguous scale tensors with correct dtype # Test non-contiguous scale tensors with correct dtype
with self.assertRaisesRegex( with self.assertRaisesRegex(
RuntimeError, RuntimeError,
re.escape( "For Block[W,w]ise.*scaling.*both should be contiguous"
"For BlockWise scaling: Both scale_a and scale_b must be contiguous" ,
),
): ):
non_contiguous_a = torch.ones(expected_a_size * 2, device=device, dtype=scale_dtype)[::2] non_contiguous_a = torch.ones(expected_a_size * 2, device=device, dtype=scale_dtype)[::2]
contiguous_b = torch.ones(expected_b_size, device=device, dtype=scale_dtype) contiguous_b = torch.ones(expected_b_size, device=device, dtype=scale_dtype)