code: def fetch_ad_md(url: str, filepath: Union[str, os.PathLike]) -> None:
      """
      Download model and distilled model.
  
      Parameters
      ----------
      url
          URL to fetch detector from.
      filepath
          Local directory to save detector to.
      """
      url_models = _join_url(url, "model")
      model_path = Path(filepath).joinpath("model").resolve()
      if not model_path.is_dir():
          model_path.mkdir(parents=True, exist_ok=True)
      # encoder and decoder
      tf.keras.utils.get_file(
          model_path.joinpath("model.h5"),
          _join_url(url_models, "model.h5"),
      )
      tf.keras.utils.get_file(
          model_path.joinpath("distilled_model.h5"),
          _join_url(url_models, "distilled_model.h5"),
      )
  
imports: import logging
  import os
  from io import BytesIO
  from pathlib import Path
  from typing import Union, TYPE_CHECKING, Tuple
  import dill
  import requests
  from requests import RequestException
  import tensorflow
  from tensorflow.python.keras import backend
  from alibi_detect.models.tensorflow import PixelCNN
  from alibi_detect.saving import load_detector
  from alibi_detect.utils.url import _join_url
label_desc: Use image node_id 6 for calling a global function with example usage: fetch_ad_md(url, filepath) without return types