accept kwargs in image proc from_pretrained

Author: yonigozlan

src/transformers/image_processing_base.py

@@ -362,25 +362,15 @@ def from_dict(cls, image_processor_dict: dict[str, Any], **kwargs):
         """
         image_processor_dict = image_processor_dict.copy()
         return_unused_kwargs = kwargs.pop("return_unused_kwargs", False)
-
-        # The `size` parameter is a dict and was previously an int or tuple in feature extractors.
-        # We set `size` here directly to the `image_processor_dict` so that it is converted to the appropriate
-        # dict within the image processor and isn't overwritten if `size` is passed in as a kwarg.
-        if "size" in kwargs and "size" in image_processor_dict:
-            image_processor_dict["size"] = kwargs.pop("size")
-        if "crop_size" in kwargs and "crop_size" in image_processor_dict:
-            image_processor_dict["crop_size"] = kwargs.pop("crop_size")
-
+        # remove _from_auto from kwargs before updating the image processor dict
+        kwargs.pop("_from_auto", None)
+        image_processor_dict.update(kwargs)
         image_processor = cls(**image_processor_dict)
 
-        # Update image_processor with kwargs if needed
-        to_remove = []
-        for key, value in kwargs.items():
+        # Remove kwargs that are used to initialize the image processor attributes
+        for key in list(kwargs):
             if hasattr(image_processor, key):
-                setattr(image_processor, key, value)
-                to_remove.append(key)
-        for key in to_remove:
-            kwargs.pop(key, None)
+                kwargs.pop(key)
 
         logger.info(f"Image processor {image_processor}")
         if return_unused_kwargs: