code: def load_checkpoint(sess, checkpoint):
      """Loads a checkpoint file into the session.
  
      Args:
        sess: tf.Session, the TF session to load variables from the checkpoint to.
        checkpoint: str, path to the checkpoint file.
      """
      model_saver = tf.train.Saver(tf.global_variables())
      checkpoint = os.path.expanduser(checkpoint)
      if tf.gfile.IsDirectory(checkpoint):
          checkpoint = tf.train.latest_checkpoint(checkpoint)
          tf.logging.info(
              "loading latest checkpoint file: {}".format(checkpoint)
          )
      model_saver.restore(sess, checkpoint)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tempfile
  from magenta.models.arbitrary_image_stylization import arbitrary_image_stylization_build_mobilenet_model
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: load_checkpoint(sess, checkpoint) without return types