update 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,
@@ -6431,7 +6430,7 @@ def test_functional(self, make_input):
             (F._color._rgb_to_grayscale_image_pil, PIL.Image.Image),
             (F.rgb_to_grayscale_image, tv_tensors.Image),
             pytest.param(
-                F._color._rgb_to_grayscale_cvcuda,
+                F._color._rgb_to_grayscale_image_cvcuda,
                 "cvcuda.Tensor",
                 marks=pytest.mark.skipif(not CVCUDA_AVAILABLE, reason="CVCUDA not available"),
             ),
@@ -6480,7 +6479,7 @@ def test_image_correctness(self, num_output_channels, color_space, make_input, f
         actual = fn(image, num_output_channels=num_output_channels)
 
         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.rgb_to_grayscale(F.to_pil_image(image), num_output_channels=num_output_channels))
 
@@ -6540,7 +6539,7 @@ def test_functional(self, make_input):
             (F._color._rgb_to_grayscale_image_pil, PIL.Image.Image),
             (F.rgb_to_grayscale_image, tv_tensors.Image),
             pytest.param(
-                F._color._rgb_to_grayscale_cvcuda,
+                F._color._rgb_to_grayscale_image_cvcuda,
                 "cvcuda.Tensor",
                 marks=pytest.mark.skipif(not CVCUDA_AVAILABLE, reason="CVCUDA not available"),
             ),
@@ -6581,7 +6580,7 @@ def test_image_correctness(self, make_input, fn):
         actual = fn(image)
 
         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.grayscale_to_rgb(F.to_pil_image(image)))
 

torchvision/transforms/v2/_color.py

@@ -5,9 +5,13 @@
 import torch
 from torchvision import transforms as _transforms
 from torchvision.transforms.v2 import functional as F, Transform
+from torchvision.transforms.v2.functional._utils import _is_cvcuda_available, _is_cvcuda_tensor
 
 from ._transform import _RandomApplyTransform
-from ._utils import is_cvcuda_tensor, query_chw
+from ._utils import query_chw
+
+
+CVCUDA_AVAILABLE = _is_cvcuda_available()
 
 
 class Grayscale(Transform):
@@ -22,7 +26,8 @@ class Grayscale(Transform):
 
     _v1_transform_cls = _transforms.Grayscale
 
-    _transformed_types = Transform._transformed_types + (is_cvcuda_tensor,)
+    if CVCUDA_AVAILABLE:
+        _transformed_types = Transform._transformed_types + (_is_cvcuda_tensor,)
 
     def __init__(self, num_output_channels: int = 1):
         super().__init__()
@@ -46,7 +51,8 @@ class RandomGrayscale(_RandomApplyTransform):
 
     _v1_transform_cls = _transforms.RandomGrayscale
 
-    _transformed_types = _RandomApplyTransform._transformed_types + (is_cvcuda_tensor,)
+    if CVCUDA_AVAILABLE:
+        _transformed_types = _RandomApplyTransform._transformed_types + (_is_cvcuda_tensor,)
 
     def __init__(self, p: float = 0.1) -> None:
         super().__init__(p=p)
@@ -66,7 +72,8 @@ class RGB(Transform):
     to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions
     """
 
-    _transformed_types = Transform._transformed_types + (is_cvcuda_tensor,)
+    if CVCUDA_AVAILABLE:
+        _transformed_types = Transform._transformed_types + (_is_cvcuda_tensor,)
 
     def __init__(self):
         super().__init__()

torchvision/transforms/v2/functional/_augment.py

@@ -1,5 +1,4 @@
 import io
-from typing import TYPE_CHECKING
 
 import PIL.Image
 
@@ -9,15 +8,7 @@
 from torchvision.transforms.functional import pil_to_tensor, to_pil_image
 from torchvision.utils import _log_api_usage_once
 
-from ._utils import _get_kernel, _import_cvcuda, _is_cvcuda_available, _register_kernel_internal
-
-
-CVCUDA_AVAILABLE = _is_cvcuda_available()
-
-if TYPE_CHECKING:
-    import cvcuda  # type: ignore[import-not-found]
-if CVCUDA_AVAILABLE:
-    cvcuda = _import_cvcuda()  # noqa: F811
+from ._utils import _get_kernel, _register_kernel_internal
 
 
 def erase(

torchvision/transforms/v2/functional/_color.py

@@ -73,7 +73,7 @@ def _rgb_to_grayscale_image_pil(image: PIL.Image.Image, num_output_channels: int
     return _FP.to_grayscale(image, num_output_channels=num_output_channels)
 
 
-def _rgb_to_grayscale_cvcuda(
+def _rgb_to_grayscale_image_cvcuda(
     image: "cvcuda.Tensor",
     num_output_channels: int = 1,
 ) -> "cvcuda.Tensor":
@@ -102,7 +102,7 @@ def _rgb_to_grayscale_cvcuda(
 
 
 if CVCUDA_AVAILABLE:
-    _register_kernel_internal(rgb_to_grayscale, _import_cvcuda().Tensor)(_rgb_to_grayscale_cvcuda)
+    _register_kernel_internal(rgb_to_grayscale, _import_cvcuda().Tensor)(_rgb_to_grayscale_image_cvcuda)
 
 
 def grayscale_to_rgb(inpt: torch.Tensor) -> torch.Tensor:
@@ -131,7 +131,7 @@ def grayscale_to_rgb_image_pil(image: PIL.Image.Image) -> PIL.Image.Image:
     return image.convert(mode="RGB")
 
 
-def _grayscale_to_rgb_cvcuda(
+def _grayscale_to_rgb_image_cvcuda(
     image: "cvcuda.Tensor",
 ) -> "cvcuda.Tensor":
     cvcuda = _import_cvcuda()
@@ -153,7 +153,7 @@ def _grayscale_to_rgb_cvcuda(
 
 
 if CVCUDA_AVAILABLE:
-    _register_kernel_internal(grayscale_to_rgb, _import_cvcuda().Tensor)(_grayscale_to_rgb_cvcuda)
+    _register_kernel_internal(grayscale_to_rgb, _import_cvcuda().Tensor)(_grayscale_to_rgb_image_cvcuda)
 
 
 def _blend(image1: torch.Tensor, image2: torch.Tensor, ratio: float) -> torch.Tensor:

torchvision/transforms/v2/functional/_misc.py

@@ -1,5 +1,5 @@
 import math
-from typing import Optional, TYPE_CHECKING
+from typing import Optional
 
 import PIL.Image
 import torch
@@ -13,14 +13,7 @@
 
 from ._meta import _convert_bounding_box_format
 
-from ._utils import _get_kernel, _import_cvcuda, _is_cvcuda_available, _register_kernel_internal, is_pure_tensor
-
-CVCUDA_AVAILABLE = _is_cvcuda_available()
-
-if TYPE_CHECKING:
-    import cvcuda  # type: ignore[import-not-found]
-if CVCUDA_AVAILABLE:
-    cvcuda = _import_cvcuda()  # noqa: F811
+from ._utils import _get_kernel, _register_kernel_internal, is_pure_tensor
 
 
 def normalize(