[proto] Reduce number of calls of __torch_function__ (#6681)

* [proto] Reduce number of calls of __torch_function__

* Use DisableTorchFunction and super

* Use self._tensor

* Fixes mypy and color space handling

* revert Image.new_like

* WIP

* Perf opt with ref to tensor and properties

* Removed requires_grad property

* Use _tensor ref

* Revert "Use _tensor ref"

This reverts commit 38f8e21242830fed46ddf31287edb67c1abd124a.

* Update torchvision/prototype/features/_feature.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

torchvision/prototype/features/_feature.py

@@ -6,6 +6,7 @@ from typing import Any, Callable, List, Mapping, Optional, Sequence, Tuple, Type
 import PIL.Image
 import torch
 from torch._C import DisableTorchFunction
+from torch.types import _device, _dtype, _size
 from torchvision.transforms import InterpolationMode
 
 
@@ -128,6 +129,28 @@ class _Feature(torch.Tensor):
             _Feature.__F = functional
         return _Feature.__F
 
+    # Add properties for common attributes like shape, dtype, device, ndim etc
+    # this way we return the result without passing into __torch_function__
+    @property
+    def shape(self) -> _size:  # type: ignore[override]
+        with DisableTorchFunction():
+            return super().shape
+
+    @property
+    def ndim(self) -> int:  # type: ignore[override]
+        with DisableTorchFunction():
+            return super().ndim
+
+    @property
+    def device(self, *args: Any, **kwargs: Any) -> _device:  # type: ignore[override]
+        with DisableTorchFunction():
+            return super().device
+
+    @property
+    def dtype(self) -> _dtype:  # type: ignore[override]
+        with DisableTorchFunction():
+            return super().dtype
+
     def horizontal_flip(self) -> _Feature:
         return self
 

torchvision/prototype/features/_video.py

@@ -15,9 +15,9 @@ class Video(_Feature):
 
     @classmethod
     def _wrap(cls, tensor: torch.Tensor, *, color_space: ColorSpace) -> Video:
-        image = tensor.as_subclass(cls)
-        image.color_space = color_space
-        return image
+        video = tensor.as_subclass(cls)
+        video.color_space = color_space
+        return video
 
     def __new__(
         cls,