code: def _load_IntegratedGradients(
      path: Union[str, os.PathLike],
      predictor: "Union[tensorflow.keras.Model]",
      meta: dict,
  ) -> "IntegratedGradients":
      from alibi.explainers.integrated_gradients import LayerState
  
      with open(Path(path, "explainer.dill"), "rb") as f:
          explainer = dill.load(f)
  
      explainer.reset_predictor(predictor)
      layer_meta = meta["params"]["layer"]
  
      if layer_meta == LayerState.CALLABLE:
          explainer.layer = explainer.callable_layer(predictor)
      elif isinstance(layer_meta, numbers.Integral):
          explainer.layer = predictor.layers[layer_meta]
  
      return explainer
  
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 5 for calling a global function with example usage: _load_IntegratedGradients(path, predictor, meta) and returns: explainer