code: def create_defaults_and_kwargs_from_preprocessor_kwargs(
      self, preprocessor_kwargs
  ) -> Tuple[Dict[str, Any], Dict[str, Any]]:
      if preprocessor_kwargs is None:
          preprocessor_kwargs = {}
      kwargs = copy.deepcopy(preprocessor_kwargs)
      defaults = {}
      defaults["padding"] = kwargs.pop("padding", "max_length")
      defaults["truncation"] = kwargs.pop("truncation", True)
      defaults["max_length"] = kwargs.pop(
          "max_length", self.preprocessor.model_max_length
      )
      return defaults, kwargs
  
file_path: optimum/optimum/utils/preprocessing/text_classification.py
imports: import copy
  import logging
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
  from transformers import PreTrainedTokenizerBase
  from .base import TaskProcessor
label_desc: Use image node_id 1 for calling the TextClassificationProcessing obj's underlying member method code with example usage: obj.create_defaults_and_kwargs_from_preprocessor_kwargs(preprocessor_kwargs) and returns: defaults,  kwargs