Removes unused argument `label_smoothing` (#16014)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
Co-authored-by: Francesco Mattioli <Francesco.mttl@gmail.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/macros/train-args.md

@@ -40,7 +40,6 @@
 | `dfl`             | `1.5`    | Weight of the distribution focal loss, used in certain YOLO versions for fine-grained classification.                                                                                                                                                        |
 | `pose`            | `12.0`   | Weight of the pose loss in models trained for pose estimation, influencing the emphasis on accurately predicting pose keypoints.                                                                                                                             |
 | `kobj`            | `2.0`    | Weight of the keypoint objectness loss in pose estimation models, balancing detection confidence with pose accuracy.                                                                                                                                         |
-| `label_smoothing` | `0.0`    | Applies label smoothing, softening hard labels to a mix of the target label and a uniform distribution over labels, can improve generalization.                                                                                                              |
 | `nbs`             | `64`     | Nominal batch size for normalization of loss.                                                                                                                                                                                                                |
 | `overlap_mask`    | `True`   | Determines whether object masks should be merged into a single mask for training, or kept separate for each object. In case of overlap, the smaller mask is overlayed on top of the larger mask during merge.                                                |
 | `mask_ratio`      | `4`      | Downsample ratio for segmentation masks, affecting the resolution of masks used during training.                                                                                                                                                             |

ultralytics/cfg/__init__.py

@@ -160,7 +160,6 @@ CFG_FRACTION_KEYS = {  # fractional float arguments with 0.0<=values<=1.0
     "weight_decay",
     "warmup_momentum",
     "warmup_bias_lr",
-    "label_smoothing",
     "hsv_h",
     "hsv_s",
     "hsv_v",
@@ -436,6 +435,9 @@ def _handle_deprecation(custom):
         if key == "line_thickness":
             deprecation_warn(key, "line_width")
             custom["line_width"] = custom.pop("line_thickness")
+        if key == "label_smoothing":
+            deprecation_warn(key)
+            custom.pop("label_smoothing")
 
     return custom
 

ultralytics/cfg/default.yaml

@@ -99,7 +99,6 @@ cls: 0.5 # (float) cls loss gain (scale with pixels)
 dfl: 1.5 # (float) dfl loss gain
 pose: 12.0 # (float) pose loss gain
 kobj: 1.0 # (float) keypoint obj loss gain
-label_smoothing: 0.0 # (float) label smoothing (fraction)
 nbs: 64 # (int) nominal batch size
 hsv_h: 0.015 # (float) image HSV-Hue augmentation (fraction)
 hsv_s: 0.7 # (float) image HSV-Saturation augmentation (fraction)

ultralytics/utils/__init__.py

@@ -1255,9 +1255,12 @@ class SettingsManager(JSONDict):
         self.update(self.defaults)
 
 
-def deprecation_warn(arg, new_arg):
+def deprecation_warn(arg, new_arg=None):
     """Issue a deprecation warning when a deprecated argument is used, suggesting an updated argument."""
-    LOGGER.warning(f"WARNING ⚠️ '{arg}' is deprecated and will be removed in in the future. Use '{new_arg}' instead.")
+    msg = f"WARNING ⚠️ '{arg}' is deprecated and will be removed in in the future."
+    if new_arg is not None:
+        msg += f" Use '{new_arg}' instead."
+    LOGGER.warning(msg)
 
 
 def clean_url(url):