diff --git a/test/test_transforms_v2_refactored.py b/test/test_transforms_v2_refactored.py index 9de1ed6d78a..544484b8fff 100644 --- a/test/test_transforms_v2_refactored.py +++ b/test/test_transforms_v2_refactored.py @@ -459,7 +459,7 @@ def _compute_output_size(self, *, input_size, size, max_size): @pytest.mark.parametrize("antialias", [True, False]) @pytest.mark.parametrize("dtype", [torch.float32, torch.uint8]) @pytest.mark.parametrize("device", cpu_and_cuda()) - def test_kernel_image_tensor(self, size, interpolation, use_max_size, antialias, dtype, device): + def test_kernel_image(self, size, interpolation, use_max_size, antialias, dtype, device): if not (max_size_kwarg := self._make_max_size_kwarg(use_max_size=use_max_size, size=size)): return @@ -830,7 +830,7 @@ def test_float16_no_rounding(self): class TestHorizontalFlip: @pytest.mark.parametrize("dtype", [torch.float32, torch.uint8]) @pytest.mark.parametrize("device", cpu_and_cuda()) - def test_kernel_image_tensor(self, dtype, device): + def test_kernel_image(self, dtype, device): check_kernel(F.horizontal_flip_image, make_image(dtype=dtype, device=device)) @pytest.mark.parametrize("format", list(tv_tensors.BoundingBoxFormat)) @@ -980,7 +980,7 @@ def _check_kernel(self, kernel, input, *args, **kwargs): ) @pytest.mark.parametrize("dtype", [torch.float32, torch.uint8]) @pytest.mark.parametrize("device", cpu_and_cuda()) - def test_kernel_image_tensor(self, param, value, dtype, device): + def test_kernel_image(self, param, value, dtype, device): if param == "fill": value = adapt_fill(value, dtype=dtype) self._check_kernel( @@ -1280,7 +1280,7 @@ def test_transform_unknown_fill_error(self): class TestVerticalFlip: @pytest.mark.parametrize("dtype", [torch.float32, torch.uint8]) @pytest.mark.parametrize("device", cpu_and_cuda()) - def test_kernel_image_tensor(self, dtype, device): + def test_kernel_image(self, dtype, device): check_kernel(F.vertical_flip_image, make_image(dtype=dtype, device=device)) @pytest.mark.parametrize("format", list(tv_tensors.BoundingBoxFormat)) @@ -1404,7 +1404,7 @@ class TestRotate: ) @pytest.mark.parametrize("dtype", [torch.float32, torch.uint8]) @pytest.mark.parametrize("device", cpu_and_cuda()) - def test_kernel_image_tensor(self, param, value, dtype, device): + def test_kernel_image(self, param, value, dtype, device): kwargs = {param: value} if param != "angle": kwargs["angle"] = self._MINIMAL_AFFINE_KWARGS["angle"] @@ -2382,7 +2382,7 @@ def _make_displacement(self, inpt): ) @pytest.mark.parametrize("dtype", [torch.float32, torch.uint8]) @pytest.mark.parametrize("device", cpu_and_cuda()) - def test_kernel_image_tensor(self, param, value, dtype, device): + def test_kernel_image(self, param, value, dtype, device): image = make_image_tensor(dtype=dtype, device=device) check_kernel(