update pad to main standards

Author: justincdavis

test/test_transforms_v2.py

@@ -25,7 +25,6 @@
     assert_equal,
     cache,
     cpu_and_cuda,
-    cvcuda_to_pil_compatible_tensor,
     freeze_rng_state,
     ignore_jit_no_profile_information_warning,
     make_bounding_boxes,
@@ -4750,14 +4749,14 @@ def test_functional(self, make_input):
             (F.pad_mask, tv_tensors.Mask),
             (F.pad_video, tv_tensors.Video),
             pytest.param(
-                F._geometry._pad_cvcuda,
-                "cvcuda.Tensor",
+                F._geometry._pad_image_cvcuda,
+                None,
                 marks=pytest.mark.skipif(not CVCUDA_AVAILABLE, reason="test requires CVCUDA"),
             ),
         ],
     )
     def test_functional_signature(self, kernel, input_type):
-        if input_type == "cvcuda.Tensor":
+        if kernel is F._geometry._pad_image_cvcuda:
             input_type = _import_cvcuda().Tensor
         check_functional_kernel_signature_match(F.pad, kernel=kernel, input_type=input_type)
 
@@ -4824,7 +4823,7 @@ def test_image_correctness(self, make_input, padding, padding_mode, fill, fn):
         actual = fn(image, padding=padding, padding_mode=padding_mode, fill=fill)
 
         if make_input is make_image_cvcuda:
-            image = cvcuda_to_pil_compatible_tensor(image)
+            image = F.cvcuda_to_tensor(image)[0].cpu()
 
         expected = F.to_image(F.pad(F.to_pil_image(image), padding=padding, padding_mode=padding_mode, fill=fill))
 

torchvision/transforms/v2/_geometry.py

@@ -26,7 +26,6 @@
     get_bounding_boxes,
     has_all,
     has_any,
-    is_cvcuda_tensor,
     is_pure_tensor,
     query_size,
 )
@@ -466,7 +465,8 @@ class Pad(Transform):
 
     _v1_transform_cls = _transforms.Pad
 
-    _transformed_types = Transform._transformed_types + (is_cvcuda_tensor,)
+    if CVCUDA_AVAILABLE:
+        _transformed_types = Transform._transformed_types + (_is_cvcuda_tensor,)
 
     def _extract_params_for_v1_transform(self) -> dict[str, Any]:
         params = super()._extract_params_for_v1_transform()

torchvision/transforms/v2/functional/_geometry.py

@@ -28,6 +28,7 @@
 
 from ._utils import (
     _FillTypeJIT,
+    _get_cvcuda_border_from_pad_mode,
     _get_kernel,
     _import_cvcuda,
     _is_cvcuda_available,
@@ -1682,26 +1683,15 @@ def _pad_with_vector_fill(
 _pad_image_pil = _register_kernel_internal(pad, PIL.Image.Image)(_FP.pad)
 
 
-if CVCUDA_AVAILABLE:
-    _pad_mode_to_cvcuda = {
-        "constant": cvcuda.Border.CONSTANT,
-        "reflect": cvcuda.Border.REFLECT101,
-        "replicate": cvcuda.Border.REPLICATE,
-        "edge": cvcuda.Border.REPLICATE,
-        "symmetric": cvcuda.Border.REFLECT,
-    }
-
-
-def _pad_cvcuda(
+def _pad_image_cvcuda(
     image: "cvcuda.Tensor",
     padding: list[int],
     fill: Optional[Union[int, float, list[float]]] = None,
     padding_mode: str = "constant",
 ) -> "cvcuda.Tensor":
     cvcuda = _import_cvcuda()
 
-    if _pad_mode_to_cvcuda.get(padding_mode) is None:
-        raise ValueError(f"Padding mode '{padding_mode}' is not supported with CVCUDA")
+    border_mode = _get_cvcuda_border_from_pad_mode(padding_mode)
 
     if fill is None:
         fill = 0
@@ -1712,7 +1702,7 @@ def _pad_cvcuda(
 
     return cvcuda.copymakeborder(
         image,
-        border_mode=_pad_mode_to_cvcuda[padding_mode],
+        border_mode=border_mode,
         border_value=fill,
         top=top,
         left=left,
@@ -1722,7 +1712,7 @@ def _pad_cvcuda(
 
 
 if CVCUDA_AVAILABLE:
-    _register_kernel_internal(pad, _import_cvcuda().Tensor)(_pad_cvcuda)
+    _register_kernel_internal(pad, _import_cvcuda().Tensor)(_pad_image_cvcuda)
 
 
 @_register_kernel_internal(pad, tv_tensors.Mask)

torchvision/transforms/v2/functional/_utils.py

@@ -1,10 +1,13 @@
 import functools
 from collections.abc import Sequence
-from typing import Any, Callable, Optional, Union
+from typing import Any, Callable, Optional, TYPE_CHECKING, Union
 
 import torch
 from torchvision import tv_tensors
 
+if TYPE_CHECKING:
+    import cvcuda  # type: ignore[import-not-found]
+
 _FillType = Union[int, float, Sequence[int], Sequence[float], None]
 _FillTypeJIT = Optional[list[float]]
 
@@ -177,3 +180,26 @@ def _is_cvcuda_tensor(inpt: Any) -> bool:
         return isinstance(inpt, cvcuda.Tensor)
     except ImportError:
         return False
+
+
+_pad_mode_to_cvcuda_border: dict[str, "cvcuda.Border"] = {}
+
+
+def _populate_cvcuda_pad_to_border_tables():
+    cvcuda = _import_cvcuda()
+
+    global _pad_mode_to_cvcuda_border
+
+    _pad_mode_to_cvcuda_border = {
+        "constant": cvcuda.Border.CONSTANT,
+        "reflect": cvcuda.Border.REFLECT101,
+        "replicate": cvcuda.Border.REPLICATE,
+        "edge": cvcuda.Border.REPLICATE,
+        "symmetric": cvcuda.Border.REFLECT,
+    }
+
+
+def _get_cvcuda_border_from_pad_mode(pad_mode: str) -> "cvcuda.Border":
+    if len(_pad_mode_to_cvcuda_border) == 0:
+        _populate_cvcuda_pad_to_border_tables()
+    return _pad_mode_to_cvcuda_border[pad_mode]