More mypy fixes/ignores (#8412)

torchvision/transforms/v2/_auto_augment.py

@@ -1,5 +1,5 @@
 import math
-from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
+from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Type, Union
 
 import PIL.Image
 import torch
@@ -94,6 +94,8 @@ def _apply_image_or_video_transform(
         interpolation: Union[InterpolationMode, int],
         fill: Dict[Union[Type, str], _FillTypeJIT],
     ) -> ImageOrVideo:
+        # Note: this cast is wrong and is only here to make mypy happy (it disagrees with torchscript)
+        image = cast(torch.Tensor, image)
         fill_ = _get_fill(fill, type(image))
 
         if transform_id == "Identity":
@@ -322,7 +324,7 @@ def _get_policies(
 
     def forward(self, *inputs: Any) -> Any:
         flat_inputs_with_spec, image_or_video = self._flatten_and_extract_image_or_video(inputs)
-        height, width = get_size(image_or_video)
+        height, width = get_size(image_or_video)  # type: ignore[arg-type]
 
         policy = self._policies[int(torch.randint(len(self._policies), ()))]
 
@@ -411,7 +413,7 @@ def __init__(
 
     def forward(self, *inputs: Any) -> Any:
         flat_inputs_with_spec, image_or_video = self._flatten_and_extract_image_or_video(inputs)
-        height, width = get_size(image_or_video)
+        height, width = get_size(image_or_video)  # type: ignore[arg-type]
 
         for _ in range(self.num_ops):
             transform_id, (magnitudes_fn, signed) = self._get_random_item(self._AUGMENTATION_SPACE)
@@ -480,7 +482,7 @@ def __init__(
 
     def forward(self, *inputs: Any) -> Any:
         flat_inputs_with_spec, image_or_video = self._flatten_and_extract_image_or_video(inputs)
-        height, width = get_size(image_or_video)
+        height, width = get_size(image_or_video)  # type: ignore[arg-type]
 
         transform_id, (magnitudes_fn, signed) = self._get_random_item(self._AUGMENTATION_SPACE)
 
@@ -572,7 +574,7 @@ def _sample_dirichlet(self, params: torch.Tensor) -> torch.Tensor:
 
     def forward(self, *inputs: Any) -> Any:
         flat_inputs_with_spec, orig_image_or_video = self._flatten_and_extract_image_or_video(inputs)
-        height, width = get_size(orig_image_or_video)
+        height, width = get_size(orig_image_or_video)  # type: ignore[arg-type]
 
         if isinstance(orig_image_or_video, torch.Tensor):
             image_or_video = orig_image_or_video
@@ -613,9 +615,7 @@ def forward(self, *inputs: Any) -> Any:
                 else:
                     magnitude = 0.0
 
-                aug = self._apply_image_or_video_transform(
-                    aug, transform_id, magnitude, interpolation=self.interpolation, fill=self._fill
-                )
+                aug = self._apply_image_or_video_transform(aug, transform_id, magnitude, interpolation=self.interpolation, fill=self._fill)  # type: ignore[assignment]
             mix.add_(combined_weights[:, i].reshape(batch_dims) * aug)
         mix = mix.reshape(orig_dims).to(dtype=image_or_video.dtype)
 

torchvision/transforms/v2/functional/_color.py

@@ -730,7 +730,7 @@ def permute_channels_image(image: torch.Tensor, permutation: List[int]) -> torch
 
 
 @_register_kernel_internal(permute_channels, PIL.Image.Image)
-def _permute_channels_image_pil(image: PIL.Image.Image, permutation: List[int]) -> PIL.Image:
+def _permute_channels_image_pil(image: PIL.Image.Image, permutation: List[int]) -> PIL.Image.Image:
     return to_pil_image(permute_channels_image(pil_to_tensor(image), permutation=permutation))
 
 

torchvision/transforms/v2/functional/_geometry.py

@@ -113,7 +113,7 @@ def vertical_flip_image(image: torch.Tensor) -> torch.Tensor:
 
 
 @_register_kernel_internal(vertical_flip, PIL.Image.Image)
-def _vertical_flip_image_pil(image: PIL.Image) -> PIL.Image:
+def _vertical_flip_image_pil(image: PIL.Image.Image) -> PIL.Image.Image:
     return _FP.vflip(image)