mypy fixes

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
       - id: no-commit-to-branch
         args: ['--branch', 'main']
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.7.1
+    rev: v0.7.4
     hooks:
       - id: ruff
         args: [ --fix ]

doctr/models/kie_predictor/pytorch.py

@@ -51,8 +51,8 @@ def __init__(
         **kwargs: Any,
     ) -> None:
         nn.Module.__init__(self)
-        self.det_predictor = det_predictor.eval()  # type: ignore[attr-defined]
-        self.reco_predictor = reco_predictor.eval()  # type: ignore[attr-defined]
+        self.det_predictor = det_predictor.eval()
+        self.reco_predictor = reco_predictor.eval()
         _KIEPredictor.__init__(
             self,
             assume_straight_pages,

doctr/models/kie_predictor/tensorflow.py

@@ -102,7 +102,7 @@ def __call__(
             origin_page_shapes = [page.shape[:2] for page in pages]
 
             # Forward again to get predictions on straight pages
-            loc_preds = self.det_predictor(pages, **kwargs)  # type: ignore[assignment]
+            loc_preds = self.det_predictor(pages, **kwargs)
 
         dict_loc_preds: Dict[str, List[np.ndarray]] = invert_data_structure(loc_preds)  # type: ignore
 

doctr/models/predictor/pytorch.py

@@ -51,8 +51,8 @@ def __init__(
         **kwargs: Any,
     ) -> None:
         nn.Module.__init__(self)
-        self.det_predictor = det_predictor.eval()  # type: ignore[attr-defined]
-        self.reco_predictor = reco_predictor.eval()  # type: ignore[attr-defined]
+        self.det_predictor = det_predictor.eval()
+        self.reco_predictor = reco_predictor.eval()
         _OCRPredictor.__init__(
             self,
             assume_straight_pages,

doctr/models/predictor/tensorflow.py

@@ -100,12 +100,12 @@ def __call__(
             origin_page_shapes = [page.shape[:2] for page in pages]
 
             # forward again to get predictions on straight pages
-            loc_preds_dict = self.det_predictor(pages, **kwargs)  # type: ignore[assignment]
+            loc_preds_dict = self.det_predictor(pages, **kwargs)
 
         assert all(len(loc_pred) == 1 for loc_pred in loc_preds_dict), (
             "Detection Model in ocr_predictor should output only one class"
         )
-        loc_preds: List[np.ndarray] = [list(loc_pred.values())[0] for loc_pred in loc_preds_dict]  # type: ignore[union-attr]
+        loc_preds: List[np.ndarray] = [list(loc_pred.values())[0] for loc_pred in loc_preds_dict]
         # Detach objectness scores from loc_preds
         loc_preds, objectness_scores = detach_scores(loc_preds)
 

doctr/models/recognition/predictor/pytorch.py

@@ -66,7 +66,7 @@ def forward(
                 crops = new_crops
 
         # Resize & batch them
-        processed_batches = self.pre_processor(crops)
+        processed_batches = self.pre_processor(crops)  # type: ignore[arg-type]
 
         # Forward it
         _params = next(self.model.parameters())

pyproject.toml

@@ -192,7 +192,7 @@ select = [
     "E", "W", "F", "I", "N", "Q", "C4", "T10", "LOG",
     "D101", "D103", "D201","D202","D207","D208","D214","D215","D300","D301","D417", "D419", "D207"  # pydocstyle
 ]
-ignore = ["E402", "E203", "F403", "E731", "N812", "N817", "C408"]
+ignore = ["E402", "E203", "F403", "E731", "N812", "N817", "C408", "LOG015"]
 
 [tool.ruff.lint.isort]
 known-first-party = ["doctr", "app", "utils"]