code: def check_flags():
      """Additional logic to make sure flags are set appropriately."""
  
      if _CUSTOMIZED_MODEL.value is not None:
          use_saved_model = tf.io.gfile.exists(
              _CUSTOMIZED_MODEL.value
          ) and tf.io.gfile.exists(
              f"{_CUSTOMIZED_MODEL.value}/saved_model.pb"
          )
  
          if use_saved_model:
              logging.info(
                  "Using saved model: %s", str(use_saved_model)
              )
          elif (
              not tf.io.gfile.exists(
                  _CUSTOMIZED_MODEL.value + ".data-00000-of-00001"
              )
              or not tf.io.gfile.exists(
                  _CUSTOMIZED_MODEL.value + ".index"
              )
              or (
                  _USE_SLIM_MODEL.value
                  and not tf.io.gfile.exists(
                      _CUSTOMIZED_MODEL.value + ".meta"
                  )
              )
          ):
              raise RuntimeError(
                  "The model files {}* do not exist. Potentially "
                  "relevant issue: "
                  "https://github.com/google/deepvariant/blob/r1.6/docs/"
                  "FAQ.md#why-cant-it-find-one-of-the-input-files-eg-"
                  "could-not-open".format(_CUSTOMIZED_MODEL.value)
              )
          logging.info(
              (
                  "You set --customized_model. Instead of using the default "
                  "model for %s, `call_variants` step will load %s* "
                  "instead."
              ),
              _MODEL_TYPE.value,
              _CUSTOMIZED_MODEL.value,
          )
  
imports: import os
  import subprocess
  import sys
  import tempfile
  from typing import Any, Dict, Optional, Tuple
  from absl import app
  from absl import flags
  from absl import logging
  import tensorflow
label_desc: Use image node_id 13 for calling a global function with example usage: check_flags() without return types