Code Refactor ruff check --fix --extend-select I (#13672)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/reference/utils/callbacks/mlflow.md

@@ -11,6 +11,10 @@ keywords: MLflow, Ultralytics YOLO, logging, metrics, parameters, model artifact
 
 <br><br>
 
+## ::: ultralytics.utils.callbacks.mlflow.sanitize_dict
+
+<br><br>
+
 ## ::: ultralytics.utils.callbacks.mlflow.on_pretrain_routine_end
 
 <br><br>

ultralytics/cfg/datasets/lvis.yaml

@@ -221,8 +221,7 @@ names:
   204: cape
   205: cappuccino/coffee cappuccino
   206: car/car automobile/auto/auto automobile/automobile
-  207: railcar/railcar part of a train/railway car/railway car part of a train/railroad
-    car/railroad car part of a train
+  207: railcar/railcar part of a train/railway car/railway car part of a train/railroad car/railroad car part of a train
   208: elevator car
   209: car battery/automobile battery
   210: identity card
@@ -241,8 +240,7 @@ names:
   223: cast/plaster cast/plaster bandage
   224: cat
   225: cauliflower
-  226: cayenne/cayenne spice/cayenne pepper/cayenne pepper spice/red pepper/red pepper
-    spice
+  226: cayenne/cayenne spice/cayenne pepper/cayenne pepper spice/red pepper/red pepper spice
   227: CD player
   228: celery
   229: cellular telephone/cellular phone/cellphone/mobile phone/smart phone
@@ -258,8 +256,7 @@ names:
   239: chessboard
   240: chicken/chicken animal
   241: chickpea/garbanzo
-  242: chili/chili vegetable/chili pepper/chili pepper vegetable/chilli/chilli vegetable/chilly/chilly
-    vegetable/chile/chile vegetable
+  242: chili/chili vegetable/chili pepper/chili pepper vegetable/chilli/chilli vegetable/chilly/chilly vegetable/chile/chile vegetable
   243: chime/gong
   244: chinaware
   245: crisp/crisp potato chip/potato chip
@@ -1061,8 +1058,7 @@ names:
   1041: sweater
   1042: sweatshirt
   1043: sweet potato
-  1044: swimsuit/swimwear/bathing suit/swimming costume/bathing costume/swimming trunks/bathing
-    trunks
+  1044: swimsuit/swimwear/bathing suit/swimming costume/bathing costume/swimming trunks/bathing trunks
   1045: sword
   1046: syringe
   1047: Tabasco sauce

ultralytics/data/explorer/gui/dash.py

@@ -259,7 +259,7 @@ def layout():
 
     with col2:
         similarity_form(selected_imgs)
-        display_labels = st.checkbox("Labels", value=False, key="display_labels")
+        st.checkbox("Labels", value=False, key="display_labels")
         utralytics_explorer_docs_callback()
 
 

ultralytics/nn/tasks.py

@@ -293,8 +293,12 @@ class DetectionModel(BaseModel):
         if isinstance(m, Detect):  # includes all Detect subclasses like Segment, Pose, OBB, WorldDetect
             s = 256  # 2x min stride
             m.inplace = self.inplace
-            forward = lambda x: self.forward(x)[0] if isinstance(m, (Segment, Pose, OBB)) else self.forward(x)
-            m.stride = torch.tensor([s / x.shape[-2] for x in forward(torch.zeros(1, ch, s, s))])  # forward
+
+            def _forward(x):
+                """Performs a forward pass through the model, handling different Detect subclass types accordingly."""
+                return self.forward(x)[0] if isinstance(m, (Segment, Pose, OBB)) else self.forward(x)
+
+            m.stride = torch.tensor([s / x.shape[-2] for x in _forward(torch.zeros(1, ch, s, s))])  # forward
             self.stride = m.stride
             m.bias_init()  # only run once
         else:

ultralytics/utils/callbacks/mlflow.py

@@ -34,11 +34,13 @@ try:
     from pathlib import Path
 
     PREFIX = colorstr("MLflow: ")
-    SANITIZE = lambda x: {k.replace("(", "").replace(")", ""): float(v) for k, v in x.items()}
 
 except (ImportError, AssertionError):
     mlflow = None
 
+def sanitize_dict(x):
+    """Sanitize dictionary keys by removing parentheses and converting values to floats."""
+    return {k.replace("(", "").replace(")", ""): float(v) for k, v in x.items()}
 
 def on_pretrain_routine_end(trainer):
     """
@@ -88,8 +90,8 @@ def on_train_epoch_end(trainer):
     if mlflow:
         mlflow.log_metrics(
             metrics={
-                **SANITIZE(trainer.lr),
-                **SANITIZE(trainer.label_loss_items(trainer.tloss, prefix="train")),
+                **sanitize_dict(trainer.lr),
+                **sanitize_dict(trainer.label_loss_items(trainer.tloss, prefix="train")),
             },
             step=trainer.epoch,
         )
@@ -98,7 +100,7 @@ def on_train_epoch_end(trainer):
 def on_fit_epoch_end(trainer):
     """Log training metrics at the end of each fit epoch to MLflow."""
     if mlflow:
-        mlflow.log_metrics(metrics=SANITIZE(trainer.metrics), step=trainer.epoch)
+        mlflow.log_metrics(metrics=sanitize_dict(trainer.metrics), step=trainer.epoch)
 
 
 def on_train_end(trainer):