move transformed tpyes to equalie transform class

Author: justincdavis

torchvision/transforms/v2/_color.py

@@ -8,6 +8,7 @@
 
 from ._transform import _RandomApplyTransform
 from ._utils import query_chw
+from .functional._utils import is_cvcuda_tensor
 
 
 class Grayscale(Transform):
@@ -265,6 +266,8 @@ class RandomEqualize(_RandomApplyTransform):
 
     _v1_transform_cls = _transforms.RandomEqualize
 
+    _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/_transform.py

@@ -11,7 +11,7 @@
 from torchvision.transforms.v2._utils import check_type, has_any, is_pure_tensor
 from torchvision.utils import _log_api_usage_once
 
-from .functional._utils import _get_kernel, is_cvcuda_tensor
+from .functional._utils import _get_kernel
 
 
 class Transform(nn.Module):
@@ -23,7 +23,7 @@ class Transform(nn.Module):
 
     # Class attribute defining transformed types. Other types are passed-through without any transformation
     # We support both Types and callables that are able to do further checks on the type of the input.
-    _transformed_types: tuple[type | Callable[[Any], bool], ...] = (torch.Tensor, PIL.Image.Image, is_cvcuda_tensor)
+    _transformed_types: tuple[type | Callable[[Any], bool], ...] = (torch.Tensor, PIL.Image.Image)
 
     def __init__(self) -> None:
         super().__init__()