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Typehint on torchvision.transforms.functional.pad should support both PIL.Image and Tensor #9258

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Typehint on torchvision.transforms.functional.pad should support both PIL.Image and Tensor #9258

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a7d9f57
Update input type for pad function to include Image
dimidagd Nov 5, 2025
ec9cd25
Merge pull request #1 from dimidagd/fix/transforms-pad-type-hint
dimidagd Nov 5, 2025
63aa0eb
Update img parameter type to support PIL images
dimidagd Nov 5, 2025
9945468
Update input type annotations for resize and pad functions
dimidagd Nov 5, 2025
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4 changes: 2 additions & 2 deletions torchvision/transforms/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -385,7 +385,7 @@ def _compute_resized_output_size(


def resize(
img: Tensor,
img: Union[PIL.Image.Image, Tensor],
size: list[int],
interpolation: InterpolationMode = InterpolationMode.BILINEAR,
max_size: Optional[int] = None,
Expand Down Expand Up @@ -479,7 +479,7 @@ def resize(
return F_t.resize(img, size=output_size, interpolation=interpolation.value, antialias=antialias)


def pad(img: Tensor, padding: list[int], fill: Union[int, float] = 0, padding_mode: str = "constant") -> Tensor:
def pad(img: Union[PIL.Image.Image, Tensor], padding: list[int], fill: Union[int, float] = 0, padding_mode: str = "constant") -> Tensor:
r"""Pad the given image on all sides with the given "pad" value.
If the image is torch Tensor, it is expected
to have [..., H, W] shape, where ... means at most 2 leading dimensions for mode reflect and symmetric,
Expand Down
4 changes: 2 additions & 2 deletions torchvision/transforms/v2/functional/_geometry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -236,7 +236,7 @@ def _compute_resized_output_size(


def resize(
inpt: torch.Tensor,
inpt: Union[PIL.Image.Image, torch.Tensor],
size: Optional[list[int]],
interpolation: Union[InterpolationMode, int] = InterpolationMode.BILINEAR,
max_size: Optional[int] = None,
Expand Down Expand Up @@ -1509,7 +1509,7 @@ def rotate_video(


def pad(
inpt: torch.Tensor,
inpt: Union[PIL.Image.Image, torch.Tensor],
padding: list[int],
fill: Optional[Union[int, float, list[float]]] = None,
padding_mode: str = "constant",
Expand Down