fix: Raise error when receive non-positive value in RandAugment.

test/test_transforms_v2.py

@@ -3514,6 +3514,14 @@ def test_aug_mix_severity_error(self, severity):
         with pytest.raises(ValueError, match="severity must be between"):
             transforms.AugMix(severity=severity)
 
+    @pytest.mark.parametrize("num_ops", [-1, 1.1])
+    def test_rand_augment_num_ops_error(self, num_ops):
+        with pytest.raises(
+            ValueError,
+            match=re.escape(f"num_ops should be a non-negative integer, but got {num_ops} instead."),
+        ):
+            transforms.RandAugment(num_ops=num_ops)
+
 
 class TestConvertBoundingBoxFormat:
     old_new_formats = list(itertools.permutations(SUPPORTED_BOX_FORMATS, 2))

torchvision/transforms/v2/_auto_augment.py

@@ -361,7 +361,8 @@ class RandAugment(_AutoAugmentBase):
     If img is PIL Image, it is expected to be in mode "L" or "RGB".
 
     Args:
-        num_ops (int, optional): Number of augmentation transformations to apply sequentially.
+        num_ops (int, optional): Number of augmentation transformations to apply sequentially,
+            must be non-negative integer. Default: 2.
         magnitude (int, optional): Magnitude for all the transformations.
         num_magnitude_bins (int, optional): The number of different magnitude values.
         interpolation (InterpolationMode, optional): Desired interpolation enum defined by
@@ -407,6 +408,8 @@ def __init__(
         fill: Union[_FillType, Dict[Union[Type, str], _FillType]] = None,
     ) -> None:
         super().__init__(interpolation=interpolation, fill=fill)
+        if not isinstance(num_ops, int) or (num_ops < 0):
+            raise ValueError(f"num_ops should be a non-negative integer, but got {num_ops} instead.")
         self.num_ops = num_ops
         self.magnitude = magnitude
         self.num_magnitude_bins = num_magnitude_bins