code: def _export_model_variables(model, saved_model_path):
      """Saves model weights in checkpoint format under variables folder."""
      _get_or_create_variables_dir(saved_model_path)
      checkpoint_prefix = _get_variables_path(saved_model_path)
      model.save_weights(
          checkpoint_prefix, save_format="tf", overwrite=True
      )
      return checkpoint_prefix
  
imports: import os
  import warnings
  from tensorflow.python.checkpoint import graph_view
  from tensorflow.python.client import session
  from tensorflow.python.framework import ops
  from tensorflow.python.keras import backend
  from tensorflow.python.keras import optimizer_v1
  from tensorflow.python.keras.optimizer_v2 import optimizer_v2
  from tensorflow.python.keras.saving import model_config
  from tensorflow.python.keras.saving import saving_utils
  from tensorflow.python.keras.saving import utils_v1
  from tensorflow.python.keras.utils import mode_keys
  from tensorflow.python.keras.utils.generic_utils import LazyLoader
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import builder
  from tensorflow.python.saved_model import constants
  from tensorflow.python.saved_model import save
  from tensorflow.python.training import saver
  from tensorflow.python.util import compat
  from tensorflow.python.util import nest
label_desc: Use image node_id 3 for calling a global function with example usage: _export_model_variables(model, saved_model_path) and returns: checkpoint_prefix