Add Hyperparameter evolution Tuner() class (#4599)

ultralytics/utils/metrics.py

@@ -520,7 +520,6 @@ class Metric(SimpleClass):
             maps(): mAP of each class. Returns: Array of mAP scores, shape: (nc,).
             fitness(): Model fitness as a weighted combination of metrics. Returns: Float.
             update(results): Update metric attributes with new evaluation results.
-
         """
 
     def __init__(self) -> None:

ultralytics/utils/ops.py

@@ -17,6 +17,16 @@ from ultralytics.utils import LOGGER
 class Profile(contextlib.ContextDecorator):
     """
     YOLOv8 Profile class. Use as a decorator with @Profile() or as a context manager with 'with Profile():'.
+
+    Example:
+        ```python
+        from ultralytics.utils.ops import Profile
+
+        with Profile() as dt:
+            pass  # slow operation here
+
+        print(dt)  # prints "Elapsed time is 9.5367431640625e-07 s"
+        ```
     """
 
     def __init__(self, t=0.0):
@@ -39,6 +49,9 @@ class Profile(contextlib.ContextDecorator):
         self.dt = self.time() - self.start  # delta-time
         self.t += self.dt  # accumulate dt
 
+    def __str__(self):
+        return f'Elapsed time is {self.t} s'
+
     def time(self):
         """Get current time."""
         if self.cuda:

ultralytics/utils/tuner.py

@@ -1,5 +1,7 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
+import subprocess
+
 from ultralytics.cfg import TASK2DATA, TASK2METRIC
 from ultralytics.utils import DEFAULT_CFG_DICT, LOGGER, NUM_THREADS
 
@@ -24,13 +26,23 @@ def run_ray_tune(model,
     Returns:
         (dict): A dictionary containing the results of the hyperparameter search.
 
-    Raises:
-        ModuleNotFoundError: If Ray Tune is not installed.
+    Example:
+        ```python
+        from ultralytics import YOLO
+
+        # Load a YOLOv8n model
+        model = YOLO('yolov8n.pt')
+
+        # Start tuning hyperparameters for YOLOv8n training on the COCO8 dataset
+        result_grid = model.tune(data='coco8.yaml', use_ray=True)
+        ```
     """
     if train_args is None:
         train_args = {}
 
     try:
+        subprocess.run('pip install ray[tune]'.split(), check=True)
+
         from ray import tune
         from ray.air import RunConfig
         from ray.air.integrations.wandb import WandbLoggerCallback