diff --git a/torchvision/prototype/transforms/functional/_color.py b/torchvision/prototype/transforms/functional/_color.py
index 7cbf8885ca9..8460f9c6422 100644
--- a/torchvision/prototype/transforms/functional/_color.py
+++ b/torchvision/prototype/transforms/functional/_color.py
@@ -227,7 +227,7 @@ def equalize_image_tensor(image: torch.Tensor) -> torch.Tensor:
     if image.numel() == 0:
         return image
 
-    return _equalize_image_tensor_vec(image.view(-1, height, width)).view(image.shape)
+    return _equalize_image_tensor_vec(image.view(-1, height, width)).reshape(image.shape)
 
 
 equalize_image_pil = _FP.equalize
diff --git a/torchvision/transforms/functional_tensor.py b/torchvision/transforms/functional_tensor.py
index 20b76fbf079..4944c75fab8 100644
--- a/torchvision/transforms/functional_tensor.py
+++ b/torchvision/transforms/functional_tensor.py
@@ -875,7 +875,7 @@ def _scale_channel(img_chan: Tensor) -> Tensor:
     if img_chan.is_cuda:
         hist = torch.histc(img_chan.to(torch.float32), bins=256, min=0, max=255)
     else:
-        hist = torch.bincount(img_chan.view(-1), minlength=256)
+        hist = torch.bincount(img_chan.reshape(-1), minlength=256)
 
     nonzero_hist = hist[hist != 0]
     step = torch.div(nonzero_hist[:-1].sum(), 255, rounding_mode="floor")