use /( in regex match

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weifengpy · Apr 27, 2024 · 8e3de02 · 8e3de02
1 parent 857b8db
commit 8e3de02
Showing 1 changed file with 12 additions and 12 deletions.
diff --git a/test/dtypes/test_nf4.py b/test/dtypes/test_nf4.py
@@ -285,7 +285,7 @@ def test_tensor_new_zeros_invalid(self, input_size: Union[Tuple[int], int]):
         else:
             new_size = (input_size[0] + 1, input_size[1])
         nf4_tensor = to_nf4(torch.randn(input_size))
-        with self.assertRaisesRegex(NotImplementedError, "aten.new_zeros\\(NF4Tensor\\) with new size"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.new_zeros\(NF4Tensor\) with new size"):
             nf4_tensor_zeros = nf4_tensor.new_zeros(new_size)
 
     @parametrize("input_size", [512 * 512, (512 * 512,), (512, 512)])
@@ -305,20 +305,20 @@ def test_tensor_slice_valid(self, input_size: Union[Tuple[int], int]):
 
     def test_tensor_slice_1d_invalid(self):
         nf4_tensor = to_nf4(torch.randn(512 * 512))
-        with self.assertRaisesRegex(NotImplementedError, "aten.slice\\(NF4Tensor\\) with step"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.slice\(NF4Tensor\) with step"):
             nf4_tensor[..., ::2]
-        with self.assertRaisesRegex(NotImplementedError, "aten.slice\\(NF4Tensor\\) with start"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.slice\(NF4Tensor\) with start"):
             nf4_tensor[1:]
-        with self.assertRaisesRegex(NotImplementedError, "aten.slice\\(NF4Tensor\\) with end "):
+        with self.assertRaisesRegex(NotImplementedError, "aten.slice\(NF4Tensor\) with end "):
             nf4_tensor[:2]
 
     def test_tensor_slice_2d_invalid(self):
         nf4_tensor = to_nf4(torch.randn((512, 512)))
-        with self.assertRaisesRegex(NotImplementedError, "aten.slice\\(NF4Tensor\\) with dim"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.slice\(NF4Tensor\) with dim"):
             nf4_tensor[:, :511]
-        with self.assertRaisesRegex(NotImplementedError, "aten.slice\\(NF4Tensor\\) with start"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.slice\(NF4Tensor\) with start"):
             nf4_tensor[1:]
-        with self.assertRaisesRegex(NotImplementedError, "aten.slice\\(NF4Tensor\\) with end"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.slice\(NF4Tensor\) with end"):
             nf4_tensor[:2]
 
     @parametrize("input_size", [(512 * 512,), (512, 512)])
@@ -334,9 +334,9 @@ def test_tensor_view_valid(self, input_size: Union[Tuple[int], int]):
     @parametrize("input_size", [(512 * 512,), (512, 512)])
     def test_tensor_view_invalid(self, input_size: Union[Tuple[int], int]):
         nf4_tensor = to_nf4(torch.randn(input_size))
-        with self.assertRaisesRegex(NotImplementedError, "aten.view\\(NF4Tensor\\) with size"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.view\(NF4Tensor\) with size"):
             nf4_tensor.view(input_size)
-        with self.assertRaisesRegex(NotImplementedError, "aten.view\\(NF4Tensor\\) with size"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.view\(NF4Tensor\) with size"):
             nf4_tensor.view(input_size)
 
     @parametrize("input_size", [512 * 512, (512 * 512,), (512, 512)])
@@ -361,13 +361,13 @@ def test_tensor_as_strided_invalid(self, input_size: Union[Tuple[int], int]):
             size = (input_size[0] - 1, )
         else:
             size = (input_size[0] - 1, input_size[1])
-        with self.assertRaisesRegex(NotImplementedError, "aten.as_strided\\(NF4Tensor\\) different numel"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.as_strided\(NF4Tensor\) different numel"):
             torch.as_strided(nf4_tensor, size, nf4_tensor.stride(), nf4_tensor.storage_offset())
-        with self.assertRaisesRegex(NotImplementedError, "aten.as_strided\\(NF4Tensor\\) only support original storage offset"):
+        with self.assertRaisesRegex(NotImplementedError, "aten.as_strided\(NF4Tensor\) only support original storage offset"):
             torch.as_strided(nf4_tensor, nf4_tensor.size(), nf4_tensor.stride(), 1)
 
         if len(input_size) == 2:
-            with self.assertRaisesRegex(NotImplementedError, "aten.as_strided\\(NF4Tensor\\) only support continuous stride"):
+            with self.assertRaisesRegex(NotImplementedError, "aten.as_strided\(NF4Tensor\) only support continuous stride"):
                 stride = (nf4_tensor.stride()[1], nf4_tensor.stride()[0])
                 torch.as_strided(nf4_tensor, nf4_tensor.size(), stride, nf4_tensor.storage_offset())