ultralytics 8.0.120 CLI support for SAM, RTDETR (#3273)

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

ultralytics/vit/rtdetr/model.py

@@ -5,6 +5,8 @@ RT-DETR model interface
 
 from pathlib import Path
 
+import torch.nn as nn
+
 from ultralytics.nn.tasks import RTDETRDetectionModel, attempt_load_one_weight, yaml_model_load
 from ultralytics.yolo.cfg import get_cfg
 from ultralytics.yolo.engine.exporter import Exporter
@@ -37,7 +39,7 @@ class RTDETR:
         self.task = 'detect'
         self.model = RTDETRDetectionModel(cfg_dict, verbose=verbose)  # build model
 
-        # Below added to allow export from yamls
+        # Below added to allow export from YAMLs
         self.model.args = DEFAULT_CFG_DICT  # attach args to model
         self.model.task = self.task
 
@@ -125,6 +127,23 @@ class RTDETR:
         """Get model info"""
         return model_info(self.model, verbose=verbose)
 
+    def _check_is_pytorch_model(self):
+        """
+        Raises TypeError is model is not a PyTorch model
+        """
+        pt_str = isinstance(self.model, (str, Path)) and Path(self.model).suffix == '.pt'
+        pt_module = isinstance(self.model, nn.Module)
+        if not (pt_module or pt_str):
+            raise TypeError(f"model='{self.model}' must be a *.pt PyTorch model, but is a different type. "
+                            f'PyTorch models can be used to train, val, predict and export, i.e. '
+                            f"'yolo export model=yolov8n.pt', but exported formats like ONNX, TensorRT etc. only "
+                            f"support 'predict' and 'val' modes, i.e. 'yolo predict model=yolov8n.onnx'.")
+
+    def fuse(self):
+        """Fuse PyTorch Conv2d and BatchNorm2d layers."""
+        self._check_is_pytorch_model()
+        self.model.fuse()
+
     @smart_inference_mode()
     def export(self, **kwargs):
         """