[prototype] Speed up `adjust_contrast_image_tensor` (#6933)

* Avoid double casting on adjust_contrast

* Handle properly ints.

torchvision/prototype/transforms/functional/_color.py

@@ -79,9 +79,14 @@ def adjust_contrast_image_tensor(image: torch.Tensor, contrast_factor: float) ->
     c = image.shape[-3]
     if c not in [1, 3]:
         raise TypeError(f"Input image tensor permitted channel values are {[1, 3]}, but found {c}")
-    dtype = image.dtype if torch.is_floating_point(image) else torch.float32
-    grayscale_image = _rgb_to_gray(image) if c == 3 else image
-    mean = torch.mean(grayscale_image.to(dtype), dim=(-3, -2, -1), keepdim=True)
+    fp = image.is_floating_point()
+    if c == 3:
+        grayscale_image = _rgb_to_gray(image, cast=False)
+        if not fp:
+            grayscale_image = grayscale_image.floor_()
+    else:
+        grayscale_image = image if fp else image.to(torch.float32)
+    mean = torch.mean(grayscale_image, dim=(-3, -2, -1), keepdim=True)
     return _blend(image, mean, contrast_factor)
 
 

torchvision/prototype/transforms/functional/_meta.py

@@ -213,10 +213,12 @@ def _gray_to_rgb(grayscale: torch.Tensor) -> torch.Tensor:
     return grayscale.repeat(repeats)
 
 
-def _rgb_to_gray(image: torch.Tensor) -> torch.Tensor:
+def _rgb_to_gray(image: torch.Tensor, cast: bool = True) -> torch.Tensor:
     r, g, b = image.unbind(dim=-3)
-    l_img = (0.2989 * r).add_(g, alpha=0.587).add_(b, alpha=0.114)
-    l_img = l_img.to(image.dtype).unsqueeze(dim=-3)
+    l_img = r.mul(0.2989).add_(g, alpha=0.587).add_(b, alpha=0.114)
+    if cast:
+        l_img = l_img.to(image.dtype)
+    l_img = l_img.unsqueeze(dim=-3)
     return l_img