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,
@@ -5473,14 +5472,14 @@ def test_functional(self, make_input):
             (F.equalize_image, tv_tensors.Image),
             (F.equalize_video, tv_tensors.Video),
             pytest.param(
-                F._color._equalize_cvcuda,
-                "cvcuda.Tensor",
+                F._color._equalize_image_cvcuda,
+                None,
                 marks=pytest.mark.skipif(not CVCUDA_AVAILABLE, reason="CVCUDA not available"),
             ),
         ],
     )
     def test_functional_signature(self, kernel, input_type):
-        if input_type == "cvcuda.Tensor":
+        if kernel is F._color._equalize_image_cvcuda:
             input_type = _import_cvcuda().Tensor
         check_functional_kernel_signature_match(F.equalize, kernel=kernel, input_type=input_type)
 
@@ -5526,7 +5525,7 @@ def test_image_correctness(self, low, high, tensor_type, fn):
         actual = fn(image)
 
         if tensor_type == "cvcuda.Tensor":
-            image = cvcuda_to_pil_compatible_tensor(image)
+            image = F.cvcuda_to_tensor(image)[0].cpu()
 
         expected = F.to_image(F.equalize(F.to_pil_image(image)))
 

torchvision/transforms/v2/_color.py

@@ -5,10 +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 query_chw
-from .functional._utils import is_cvcuda_tensor
+
+
+CVCUDA_AVAILABLE = _is_cvcuda_available()
 
 
 class Grayscale(Transform):
@@ -266,7 +269,8 @@ class RandomEqualize(_RandomApplyTransform):
 
     _v1_transform_cls = _transforms.RandomEqualize
 
-    _transformed_types = _RandomApplyTransform._transformed_types + (is_cvcuda_tensor,)
+    if CVCUDA_AVAILABLE:
+        _transformed_types = _RandomApplyTransform._transformed_types + (_is_cvcuda_tensor,)
 
     def transform(self, inpt: Any, params: dict[str, Any]) -> Any:
         return self._call_kernel(F.equalize, inpt)

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

@@ -659,15 +659,15 @@ def equalize_video(video: torch.Tensor) -> torch.Tensor:
     return equalize_image(video)
 
 
-def _equalize_cvcuda(
+def _equalize_image_cvcuda(
     image: "cvcuda.Tensor",
 ) -> "cvcuda.Tensor":
     cvcuda = _import_cvcuda()
     return cvcuda.histogrameq(image, dtype=image.dtype)
 
 
 if CVCUDA_AVAILABLE:
-    _register_kernel_internal(equalize, _import_cvcuda().Tensor)(_equalize_cvcuda)
+    _register_kernel_internal(equalize, _import_cvcuda().Tensor)(_equalize_image_cvcuda)
 
 
 def invert(inpt: torch.Tensor) -> 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(