[fbsync] fix: add appropriate error message when validating padding argument. (#8959)

Reviewed By: scotts

Differential Revision: D77998622

fbshipit-source-id: af1c52f8f1a4c98619bb9feb0cb29acce8c74a32

Co-authored-by: Nicolas Hug <[email protected]>
Co-authored-by: Nicolas Hug <[email protected]>

Author: NicolasHug

test/test_transforms_v2.py

@@ -3022,12 +3022,18 @@ def test_errors(self):
         with pytest.raises(ValueError, match="Please provide only two dimensions"):
             transforms.RandomCrop([10, 12, 14])
 
-        with pytest.raises(TypeError, match="Got inappropriate padding arg"):
+        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4"):
             transforms.RandomCrop([10, 12], padding="abc")
 
         with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4"):
             transforms.RandomCrop([10, 12], padding=[-0.7, 0, 0.7])
 
+        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4"):
+            transforms.RandomCrop([10, 12], padding=0.5)
+
+        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4"):
+            transforms.RandomCrop([10, 12], padding=[0.5, 0.5])
+
         with pytest.raises(TypeError, match="Got inappropriate fill arg"):
             transforms.RandomCrop([10, 12], padding=1, fill="abc")
 
@@ -3892,12 +3898,18 @@ def test_transform(self, make_input):
         check_transform(transforms.Pad(padding=[1]), make_input())
 
     def test_transform_errors(self):
-        with pytest.raises(TypeError, match="Got inappropriate padding arg"):
+        with pytest.raises(ValueError, match="Padding must be"):
             transforms.Pad("abc")
 
-        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4"):
+        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4 element of tuple or list"):
             transforms.Pad([-0.7, 0, 0.7])
 
+        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4 element of tuple or list"):
+            transforms.Pad(0.5)
+
+        with pytest.raises(ValueError, match="Padding must be an int or a 1, 2, or 4 element of tuple or list"):
+            transforms.Pad(padding=[0.5, 0.5])
+
         with pytest.raises(TypeError, match="Got inappropriate fill arg"):
             transforms.Pad(12, fill="abc")
 

torchvision/transforms/v2/_utils.py

@@ -81,11 +81,13 @@ def _get_fill(fill_dict, inpt_type):
 
 
 def _check_padding_arg(padding: Union[int, Sequence[int]]) -> None:
-    if not isinstance(padding, (numbers.Number, tuple, list)):
-        raise TypeError("Got inappropriate padding arg")
 
-    if isinstance(padding, (tuple, list)) and len(padding) not in [1, 2, 4]:
-        raise ValueError(f"Padding must be an int or a 1, 2, or 4 element tuple, not a {len(padding)} element tuple")
+    err_msg = f"Padding must be an int or a 1, 2, or 4 element of tuple or list, got {padding}."
+    if isinstance(padding, (tuple, list)):
+        if len(padding) not in [1, 2, 4] or not all(isinstance(p, int) for p in padding):
+            raise ValueError(err_msg)
+    elif not isinstance(padding, int):
+        raise ValueError(err_msg)
 
 
 # TODO: let's use torchvision._utils.StrEnum to have the best of both worlds (strings and enums)