Attempt to fix NAS models inference (#14630)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>

ultralytics/models/nas/model.py

@@ -17,7 +17,7 @@ import torch
 
 from ultralytics.engine.model import Model
 from ultralytics.utils.downloads import attempt_download_asset
-from ultralytics.utils.torch_utils import model_info, smart_inference_mode
+from ultralytics.utils.torch_utils import model_info
 
 from .predict import NASPredictor
 from .val import NASValidator
@@ -50,16 +50,25 @@ class NAS(Model):
         assert Path(model).suffix not in {".yaml", ".yml"}, "YOLO-NAS models only support pre-trained models."
         super().__init__(model, task="detect")
 
-    @smart_inference_mode()
-    def _load(self, weights: str, task: str):
+    def _load(self, weights: str, task=None) -> None:
         """Loads an existing NAS model weights or creates a new NAS model with pretrained weights if not provided."""
         import super_gradients
 
         suffix = Path(weights).suffix
         if suffix == ".pt":
             self.model = torch.load(attempt_download_asset(weights))
+
         elif suffix == "":
             self.model = super_gradients.training.models.get(weights, pretrained_weights="coco")
+
+        # Override the forward method to ignore additional arguments
+        def new_forward(x, *args, **kwargs):
+            """Ignore additional __call__ arguments."""
+            return self.model._original_forward(x)
+
+        self.model._original_forward = self.model.forward
+        self.model.forward = new_forward
+
         # Standardize model
         self.model.fuse = lambda verbose=True: self.model
         self.model.stride = torch.tensor([32])