reinstante antialias tests

Author: pmeier

test/test_transforms_v2.py

@@ -1331,6 +1331,7 @@ def test__transform(self, inpt):
 def test_antialias_warning():
     pil_img = PIL.Image.new("RGB", size=(10, 10), color=127)
     tensor_img = torch.randint(0, 256, size=(3, 10, 10), dtype=torch.uint8)
+    tensor_video = torch.randint(0, 256, size=(2, 3, 10, 10), dtype=torch.uint8)
 
     match = "The default value of the antialias parameter"
     with pytest.warns(UserWarning, match=match):
@@ -1342,6 +1343,14 @@ def test_antialias_warning():
     with pytest.warns(UserWarning, match=match):
         transforms.RandomResize(10, 20)(tensor_img)
 
+    with pytest.warns(UserWarning, match=match):
+        F.resized_crop(datapoints.Image(tensor_img), 0, 0, 10, 10, (20, 20))
+
+    with pytest.warns(UserWarning, match=match):
+        F.resize(datapoints.Video(tensor_video), (20, 20))
+    with pytest.warns(UserWarning, match=match):
+        F.resized_crop(datapoints.Video(tensor_video), 0, 0, 10, 10, (20, 20))
+
     with warnings.catch_warnings():
         warnings.simplefilter("error")
         transforms.RandomResizedCrop((20, 20))(pil_img)
@@ -1354,6 +1363,9 @@ def test_antialias_warning():
         transforms.RandomShortestSize((20, 20), antialias=True)(tensor_img)
         transforms.RandomResize(10, 20, antialias=True)(tensor_img)
 
+        F.resized_crop(datapoints.Image(tensor_img), 0, 0, 10, 10, (20, 20), antialias=True)
+        F.resized_crop(datapoints.Video(tensor_video), 0, 0, 10, 10, (20, 20), antialias=True)
+
 
 @pytest.mark.parametrize("image_type", (PIL.Image, torch.Tensor, datapoints.Image))
 @pytest.mark.parametrize("label_type", (torch.Tensor, int))