[proto] Clean-ups from 6512 (part 2) (#6523)

* Moving `_parse_pad_padding()` to functional geometry

* Other updates to make previous commit consistent
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

torchvision/prototype/transforms/_geometry.py

@@ -12,16 +12,7 @@ from torchvision.prototype.transforms import functional as F, InterpolationMode,
 from typing_extensions import Literal
 
 from ._transform import _RandomApplyTransform
-from ._utils import (
-    _check_sequence_input,
-    _parse_pad_padding,
-    _setup_angle,
-    _setup_size,
-    has_all,
-    has_any,
-    query_bounding_box,
-    query_chw,
-)
+from ._utils import _check_sequence_input, _setup_angle, _setup_size, has_all, has_any, query_bounding_box, query_chw
 
 
 class RandomHorizontalFlip(_RandomApplyTransform):
@@ -433,7 +424,7 @@ class RandomCrop(Transform):
             padding = self.padding
             if isinstance(padding, Sequence):
                 padding = list(padding)
-            pad_left, pad_right, pad_top, pad_bottom = _parse_pad_padding(padding)
+            pad_left, pad_right, pad_top, pad_bottom = F._geometry._parse_pad_padding(padding)
             height += pad_top + pad_bottom
             width += pad_left + pad_right
 

torchvision/prototype/transforms/_utils.py

@@ -6,7 +6,6 @@ from torchvision._utils import sequence_to_str
 from torchvision.prototype import features
 
 from torchvision.prototype.transforms.functional._meta import get_chw
-from torchvision.transforms.functional_tensor import _parse_pad_padding  # noqa: F401
 from torchvision.transforms.transforms import _check_sequence_input, _setup_angle, _setup_size  # noqa: F401
 
 

torchvision/prototype/transforms/functional/_geometry.py

@@ -15,6 +15,7 @@ from torchvision.transforms.functional import (
     pil_to_tensor,
     to_pil_image,
 )
+from torchvision.transforms.functional_tensor import _parse_pad_padding
 
 from ._meta import convert_bounding_box_format, get_dimensions_image_pil, get_dimensions_image_tensor
 
@@ -564,7 +565,7 @@ def _pad_with_vector_fill(
         raise ValueError(f"Padding mode '{padding_mode}' is not supported if fill is not scalar")
 
     output = pad_image_tensor(img, padding, fill=0, padding_mode="constant")
-    left, right, top, bottom = _FT._parse_pad_padding(padding)
+    left, right, top, bottom = _parse_pad_padding(padding)
     fill = torch.tensor(fill, dtype=img.dtype, device=img.device).view(-1, 1, 1)
 
     if top > 0:
@@ -595,7 +596,7 @@ def pad_segmentation_mask(
 def pad_bounding_box(
     bounding_box: torch.Tensor, padding: Union[int, List[int]], format: features.BoundingBoxFormat
 ) -> torch.Tensor:
-    left, _, top, _ = _FT._parse_pad_padding(padding)
+    left, _, top, _ = _parse_pad_padding(padding)
 
     bounding_box = bounding_box.clone()