chore(deps-dev): Bump pyright from 1.1.408 to 1.1.409

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",

spelling_private_dict.txt

@@ -89,6 +89,7 @@ reportAssignmentType
 reportAttributeAccessIssue
 reportGeneralTypeIssues
 reportMissingTypeStubs
+reportPrivateImportUsage
 reportUnknownArgumentType
 reportUnknownMemberType
 reportUnknownVariableType

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],

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],