diff --git a/torchvision/prototype/datapoints/_datapoint.py b/torchvision/prototype/datapoints/_datapoint.py
index 53d1b05fb3b..659d4e958cc 100644
--- a/torchvision/prototype/datapoints/_datapoint.py
+++ b/torchvision/prototype/datapoints/_datapoint.py
@@ -5,7 +5,7 @@
 
 import PIL.Image
 import torch
-from torch._C import DisableTorchFunction
+from torch._C import DisableTorchFunctionSubclass
 from torch.types import _device, _dtype, _size
 from torchvision.transforms import InterpolationMode
 
@@ -87,7 +87,7 @@ def __torch_function__(
         if not all(issubclass(cls, t) for t in types):
             return NotImplemented
 
-        with DisableTorchFunction():
+        with DisableTorchFunctionSubclass():
             output = func(*args, **kwargs or dict())
 
             wrapper = cls._NO_WRAPPING_EXCEPTIONS.get(func)
@@ -129,22 +129,22 @@ def _F(self) -> ModuleType:
     # this way we return the result without passing into __torch_function__
     @property
     def shape(self) -> _size:  # type: ignore[override]
-        with DisableTorchFunction():
+        with DisableTorchFunctionSubclass():
             return super().shape
 
     @property
     def ndim(self) -> int:  # type: ignore[override]
-        with DisableTorchFunction():
+        with DisableTorchFunctionSubclass():
             return super().ndim
 
     @property
     def device(self, *args: Any, **kwargs: Any) -> _device:  # type: ignore[override]
-        with DisableTorchFunction():
+        with DisableTorchFunctionSubclass():
             return super().device
 
     @property
     def dtype(self) -> _dtype:  # type: ignore[override]
-        with DisableTorchFunction():
+        with DisableTorchFunctionSubclass():
             return super().dtype
 
     def horizontal_flip(self) -> Datapoint: