Tests and docstrings improvements (#4475)

ultralytics/utils/callbacks/clearml.py

@@ -29,8 +29,7 @@ def _log_debug_samples(files, title='Debug Samples') -> None:
         files (list): A list of file paths in PosixPath format.
         title (str): A title that groups together images with the same values.
     """
-    task = Task.current_task()
-    if task:
+    if task := Task.current_task():
         for f in files:
             if f.exists():
                 it = re.search(r'_batch(\d+)', f.name)
@@ -63,8 +62,7 @@ def _log_plot(title, plot_path) -> None:
 def on_pretrain_routine_start(trainer):
     """Runs at start of pretraining routine; initializes and connects/ logs task to ClearML."""
     try:
-        task = Task.current_task()
-        if task:
+        if task := Task.current_task():
             # Make sure the automatic pytorch and matplotlib bindings are disabled!
             # We are logging these plots and model files manually in the integration
             PatchPyTorchModelIO.update_current_task(None)
@@ -86,21 +84,19 @@ def on_pretrain_routine_start(trainer):
 
 
 def on_train_epoch_end(trainer):
-    task = Task.current_task()
-
-    if task:
-        """Logs debug samples for the first epoch of YOLO training."""
+    """Logs debug samples for the first epoch of YOLO training and report current training progress."""
+    if task := Task.current_task():
+        # Log debug samples
         if trainer.epoch == 1:
             _log_debug_samples(sorted(trainer.save_dir.glob('train_batch*.jpg')), 'Mosaic')
-        """Report the current training progress."""
+        # Report the current training progress
         for k, v in trainer.validator.metrics.results_dict.items():
             task.get_logger().report_scalar('train', k, v, iteration=trainer.epoch)
 
 
 def on_fit_epoch_end(trainer):
     """Reports model information to logger at the end of an epoch."""
-    task = Task.current_task()
-    if task:
+    if task := Task.current_task():
         # You should have access to the validation bboxes under jdict
         task.get_logger().report_scalar(title='Epoch Time',
                                         series='Epoch Time',
@@ -120,8 +116,7 @@ def on_val_end(validator):
 
 def on_train_end(trainer):
     """Logs final model and its name on training completion."""
-    task = Task.current_task()
-    if task:
+    if task := Task.current_task():
         # Log final results, CM matrix + PR plots
         files = [
             'results.png', 'confusion_matrix.png', 'confusion_matrix_normalized.png',

ultralytics/utils/callbacks/dvc.py

@@ -40,7 +40,7 @@ def _log_images(path, prefix=''):
 
         # Group images by batch to enable sliders in UI
         if m := re.search(r'_batch(\d+)', name):
-            ni = m.group(1)
+            ni = m[1]
             new_stem = re.sub(r'_batch(\d+)', '_batch', path.stem)
             name = (Path(new_stem) / ni).with_suffix(path.suffix)