Implement all missing docstrings (#5298)

Co-authored-by: snyk-bot <snyk-bot@snyk.io>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/models/nas/model.py

@@ -23,6 +23,26 @@ from .val import NASValidator
 
 
 class NAS(Model):
+    """
+    YOLO NAS model for object detection.
+
+    This class provides an interface for the YOLO-NAS models and extends the `Model` class from Ultralytics engine.
+    It is designed to facilitate the task of object detection using pre-trained or custom-trained YOLO-NAS models.
+
+    Example:
+        ```python
+        from ultralytics import NAS
+
+        model = NAS('yolo_nas_s')
+        results = model.predict('ultralytics/assets/bus.jpg')
+        ```
+
+    Attributes:
+        model (str): Path to the pre-trained model or model name. Defaults to 'yolo_nas_s.pt'.
+
+    Note:
+        YOLO-NAS models only support pre-trained models. Do not provide YAML configuration files.
+    """
 
     def __init__(self, model='yolo_nas_s.pt') -> None:
         """Initializes the NAS model with the provided or default 'yolo_nas_s.pt' model."""

ultralytics/models/nas/predict.py

@@ -8,6 +8,29 @@ from ultralytics.utils import ops
 
 
 class NASPredictor(BasePredictor):
+    """
+    Ultralytics YOLO NAS Predictor for object detection.
+
+    This class extends the `BasePredictor` from Ultralytics engine and is responsible for post-processing the
+    raw predictions generated by the YOLO NAS models. It applies operations like non-maximum suppression and
+    scaling the bounding boxes to fit the original image dimensions.
+
+    Attributes:
+        args (Namespace): Namespace containing various configurations for post-processing.
+
+    Example:
+        ```python
+        from ultralytics import NAS
+
+        model = NAS('yolo_nas_s')
+        predictor = model.predictor
+        # Assumes that raw_preds, img, orig_imgs are available
+        results = predictor.postprocess(raw_preds, img, orig_imgs)
+        ```
+
+    Note:
+        Typically, this class is not instantiated directly. It is used internally within the `NAS` class.
+    """
 
     def postprocess(self, preds_in, img, orig_imgs):
         """Postprocess predictions and returns a list of Results objects."""

ultralytics/models/nas/val.py

@@ -9,6 +9,30 @@ __all__ = ['NASValidator']
 
 
 class NASValidator(DetectionValidator):
+    """
+    Ultralytics YOLO NAS Validator for object detection.
+
+    Extends `DetectionValidator` from the Ultralytics models package and is designed to post-process the raw predictions
+    generated by YOLO NAS models. It performs non-maximum suppression to remove overlapping and low-confidence boxes,
+    ultimately producing the final detections.
+
+    Attributes:
+        args (Namespace): Namespace containing various configurations for post-processing, such as confidence and IoU thresholds.
+        lb (torch.Tensor): Optional tensor for multilabel NMS.
+
+    Example:
+        ```python
+        from ultralytics import NAS
+
+        model = NAS('yolo_nas_s')
+        validator = model.validator
+        # Assumes that raw_preds are available
+        final_preds = validator.postprocess(raw_preds)
+        ```
+
+    Note:
+        This class is generally not instantiated directly but is used internally within the `NAS` class.
+    """
 
     def postprocess(self, preds_in):
         """Apply Non-maximum suppression to prediction outputs."""