Patch torch.load(..., weights_only=False) to reduce warnings (#14638)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/reference/utils/patches.md

@@ -23,6 +23,10 @@ keywords: Ultralytics, utils, patches, imread, imwrite, imshow, torch_save, Open
 
 <br><br><hr><br>
 
+## ::: ultralytics.utils.patches.torch_load
+
+<br><br><hr><br>
+
 ## ::: ultralytics.utils.patches.torch_save
 
 <br><br>

ultralytics/utils/__init__.py

@@ -1066,8 +1066,9 @@ TESTS_RUNNING = is_pytest_running() or is_github_action_running()
 set_sentry()
 
 # Apply monkey patches
-from ultralytics.utils.patches import imread, imshow, imwrite, torch_save
+from ultralytics.utils.patches import imread, imshow, imwrite, torch_load, torch_save
 
+torch.load = torch_load
 torch.save = torch_save
 if WINDOWS:
     # Apply cv2 patches for non-ASCII and non-UTF characters in image paths

ultralytics/utils/patches.py

@@ -57,7 +57,33 @@ def imshow(winname: str, mat: np.ndarray):
 
 
 # PyTorch functions ----------------------------------------------------------------------------------------------------
-_torch_save = torch.save  # copy to avoid recursion errors
+_torch_load = torch.load  # copy to avoid recursion errors
+_torch_save = torch.save
+
+
+def torch_load(*args, **kwargs):
+    """
+    Load a PyTorch model with updated arguments to avoid warnings.
+
+    This function wraps torch.load and adds the 'weights_only' argument for PyTorch 1.13.0+ to prevent warnings.
+
+    Args:
+        *args (Any): Variable length argument list to pass to torch.load.
+        **kwargs (Any): Arbitrary keyword arguments to pass to torch.load.
+
+    Returns:
+        (Any): The loaded PyTorch object.
+
+    Note:
+        For PyTorch versions 2.0 and above, this function automatically sets 'weights_only=False'
+        if the argument is not provided, to avoid deprecation warnings.
+    """
+    from ultralytics.utils.torch_utils import TORCH_1_13
+
+    if TORCH_1_13 and "weights_only" not in kwargs:
+        kwargs["weights_only"] = False
+
+    return _torch_load(*args, **kwargs)
 
 
 def torch_save(*args, use_dill=True, **kwargs):
@@ -68,7 +94,7 @@ def torch_save(*args, use_dill=True, **kwargs):
     Args:
         *args (tuple): Positional arguments to pass to torch.save.
         use_dill (bool): Whether to try using dill for serialization if available. Defaults to True.
-        **kwargs (any): Keyword arguments to pass to torch.save.
+        **kwargs (Any): Keyword arguments to pass to torch.save.
     """
     try:
         assert use_dill