code: def load_explainer(
      path: Union[str, os.PathLike], predictor
  ) -> "Explainer":
      """
      Load an explainer from disk.
  
      Parameters
      ----------
      path
          Path to a directory containing the saved explainer.
      predictor
          Model or prediction function used to originally initialize the explainer.
  
      Returns
      -------
      An explainer instance.
      """
      # load metadata
      with open(Path(path, "meta.dill"), "rb") as f:
          meta = dill.load(f)
  
      # check version
      if meta["version"] != __version__:
          warnings.warn(
              f'Trying to load explainer from version {meta["version"]} when using version {__version__}. '
              f"This may lead to breaking code or invalid results."
          )
  
      name = meta["name"]
      try:
          # get the explainer specific load function
          load_fn = getattr(thismodule, "_load_" + name)
      except AttributeError:
          load_fn = _simple_load
      return load_fn(path, predictor, meta)
  
imports: import copy
  import json
  import numbers
  import os
  from pathlib import Path
  import sys
  from typing import Callable, TYPE_CHECKING, Union
  import warnings
  import dill
  import numpy
  from alibi.version import __version__
label_desc: Use image node_id 1 for calling a global function with example usage: load_explainer(path, predictor) and returns: load_fn