diff --git a/pyproject.toml b/pyproject.toml index 4ace332fd..ab51a5161 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -74,7 +74,7 @@ optional-dependencies.dev = [ "pylint-per-file-ignores==3.2.1", "pyproject-fmt==2.21.1", "pyrefly==0.62.0", - "pyright==1.1.408", + "pyright==1.1.409", "pyroma==5.0.1", "pytest==9.0.3", "pytest-beartype-tests==2026.4.20", diff --git a/spelling_private_dict.txt b/spelling_private_dict.txt index b1ad02e08..51024a882 100644 --- a/spelling_private_dict.txt +++ b/spelling_private_dict.txt @@ -89,6 +89,7 @@ reportAssignmentType reportAttributeAccessIssue reportGeneralTypeIssues reportMissingTypeStubs +reportPrivateImportUsage reportUnknownArgumentType reportUnknownMemberType reportUnknownVariableType diff --git a/src/mock_vws/image_matchers.py b/src/mock_vws/image_matchers.py index 686957ad2..363bf75bb 100644 --- a/src/mock_vws/image_matchers.py +++ b/src/mock_vws/image_matchers.py @@ -81,7 +81,12 @@ def __call__( second_image_resized = second_image.resize(size=target_size) first_image_np = np.array(object=first_image_resized, dtype=np.float32) - first_image_tensor = torch.tensor(data=first_image_np).float() / 255 + first_image_tensor = ( + torch.tensor( # pyright: ignore[reportPrivateImportUsage] + data=first_image_np, + ).float() + / 255 + ) first_image_tensor = first_image_tensor.view( first_image_resized.size[1], first_image_resized.size[0], @@ -92,7 +97,12 @@ def __call__( object=second_image_resized, dtype=np.float32, ) - second_image_tensor = torch.tensor(data=second_image_np).float() / 255 + second_image_tensor = ( + torch.tensor( # pyright: ignore[reportPrivateImportUsage] + data=second_image_np, + ).float() + / 255 + ) second_image_tensor = second_image_tensor.view( second_image_resized.size[1], second_image_resized.size[0], diff --git a/src/mock_vws/target_raters.py b/src/mock_vws/target_raters.py index 3358ca483..c844db550 100644 --- a/src/mock_vws/target_raters.py +++ b/src/mock_vws/target_raters.py @@ -28,7 +28,12 @@ def _get_brisque_target_tracking_rating(*, image_content: bytes) -> int: image_file = io.BytesIO(initial_bytes=image_content) with Image.open(fp=image_file) as image: image_np = np.array(object=image, dtype=np.float32) - image_tensor = torch.tensor(data=image_np).float() / 255 + image_tensor = ( + torch.tensor( # pyright: ignore[reportPrivateImportUsage] + data=image_np, + ).float() + / 255 + ) image_tensor = image_tensor.view( image.size[1], image.size[0],