PyTorch Hub custom model to CUDA device fix (ultralytics#2636)

Fix for ultralytics#2630 raised by @Pro100rus32

(cherry picked from commit ee16983)

hubconf.py

@@ -128,7 +128,10 @@ def custom(path_or_model='path/to/model.pt', autoshape=True):
     hub_model = Model(model.yaml).to(next(model.parameters()).device)  # create
     hub_model.load_state_dict(model.float().state_dict())  # load state_dict
     hub_model.names = model.names  # class names
-    return hub_model.autoshape() if autoshape else hub_model
+    if autoshape:
+        hub_model = hub_model.autoshape()  # for file/URI/PIL/cv2/np inputs and NMS
+    device = select_device('0' if torch.cuda.is_available() else 'cpu')  # default to GPU if available
+    return hub_model.to(device)
 
 
 if __name__ == '__main__':