fix

optimum/onnxruntime/modeling_ort.py

@@ -187,17 +187,20 @@ def shared_attributes_init(
         model: ort.InferenceSession,
         use_io_binding: Optional[bool] = None,
         model_save_dir: Optional[Union[str, Path, TemporaryDirectory]] = None,
+        preprocessors: Optional[List[Any]] = None,
         **kwargs,
     ):
         """
         Initializes attributes that may be shared among several ONNX Runtime inference sesssions.
         """
+
         # TODO: remove at version 2.0
         if kwargs.pop("latest_model_name", None) is not None:
             logger.warning(
                 f"The latest_model_name argument to create an {self.__class__.__name__} is deprecated, and not used "
                 "anymore."
             )
+
         if kwargs:
             raise ValueError(
                 f"{self.__class__.__name__} received {', '.join(kwargs.keys())}, but do not accept those arguments."
@@ -227,9 +230,6 @@ def shared_attributes_init(
         else:
             self.model_save_dir = Path(model._model_path).parent
 
-        # because OptimizedModel requires it
-        self.preprocessors = kwargs.pop("preprocessors", [])
-
         # Registers the ORTModelForXXX classes into the transformers AutoModel classes to avoid warnings when creating
         # a pipeline https://github.com/huggingface/transformers/blob/cad61b68396a1a387287a8e2e2fef78a25b79383/src/transformers/pipelines/base.py#L863
         AutoConfig.register(self.model_type, AutoConfig)
@@ -239,13 +239,16 @@ def shared_attributes_init(
         # Define the pattern here to avoid recomputing it everytime.
         self.output_shape_inference_pattern = re.compile(r"([a-zA-Z_]+)|([0-9]+)|([+-/*])|([\(\)])")
 
+        # because OptimizedModel requires it
+        self.preprocessors = preprocessors
+
     def __init__(
         self,
         model: ort.InferenceSession,
         config: "PretrainedConfig",
         use_io_binding: Optional[bool] = None,
         model_save_dir: Optional[Union[str, Path, TemporaryDirectory]] = None,
-        preprocessors: Optional[List] = None,
+        preprocessors: Optional[List[Any]] = None,
         **kwargs,
     ):
         super().__init__(model, config)