A minor correction in a comment

export.py

@@ -742,9 +742,9 @@ def pipeline_coreml(model, im, file, names, y, prefix=colorstr("CoreML Pipeline:
     model = ct.models.MLModel(pipeline.spec)
     model.input_description["image"] = "Input image"
     model.input_description["iouThreshold"] = f"(optional) IOU Threshold override (default: {nms.iouThreshold})"
-    model.input_description[
-        "confidenceThreshold"
-    ] = f"(optional) Confidence Threshold override (default: {nms.confidenceThreshold})"
+    model.input_description["confidenceThreshold"] = (
+        f"(optional) Confidence Threshold override (default: {nms.confidenceThreshold})"
+    )
     model.output_description["confidence"] = 'Boxes × Class confidence (see user-defined metadata "classes")'
     model.output_description["coordinates"] = "Boxes × [x, y, width, height] (relative to image size)"
     model.save(f)  # pipelined

models/experimental.py

@@ -1,5 +1,6 @@
 # YOLOv5 🚀 by Ultralytics, AGPL-3.0 license
 """Experimental modules."""
+
 import math
 
 import numpy as np

utils/loggers/__init__.py

@@ -1,5 +1,6 @@
 # YOLOv5 🚀 by Ultralytics, AGPL-3.0 license
 """Logging utils."""
+
 import json
 import os
 import warnings

utils/loggers/clearml/clearml_utils.py

@@ -1,4 +1,5 @@
 """Main Logger class for ClearML experiment tracking."""
+
 import glob
 import re
 from pathlib import Path

utils/loss.py

@@ -9,7 +9,7 @@
 
 
 def smooth_BCE(eps=0.1):
-    """Returns label smoothing BCE targets for reducing overfitting; pos: `1.0 - 0.5*eps`, neg: `0.5*eps`. For details see ttps://github.com/ultralytics/yolov3/issues/238#issuecomment-598028441"""
+    """Returns label smoothing BCE targets for reducing overfitting; pos: `1.0 - 0.5*eps`, neg: `0.5*eps`. For details see https://github.com/ultralytics/yolov3/issues/238#issuecomment-598028441"""
     return 1.0 - 0.5 * eps, 0.5 * eps