code: def from_pretrained(
      cls,
      pretrained_model_name_or_path: Union[str, os.PathLike],
      **kwargs,
  ) -> "PretrainedConfig":
      config_dict, kwargs = cls.get_config_dict(
          pretrained_model_name_or_path, **kwargs
      )
  
      # get the image codebook config dict if we are loading from FlavaConfig
      if config_dict.get("model_type") == "flava":
          config_dict = config_dict["image_codebook_config"]
  
      if (
          "model_type" in config_dict
          and hasattr(cls, "model_type")
          and config_dict["model_type"] != cls.model_type
      ):
          logger.warning(
              f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
              f"{cls.model_type}. This is not supported for all configurations of models and can yield errors."
          )
  
      return cls.from_dict(config_dict, **kwargs)
  
imports: import copy
  import os
  from typing import Any, Dict, Union
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 2 for calling the FlavaImageCodebookConfig obj's underlying member method code with example usage: obj.from_pretrained(cls, pretrained_model_name_or_path) and returns: cls