code: def after_create_session(self, session, coord):
      checkpoint = tf.train.latest_checkpoint(self.checkpoints_path)
      # wait until a new check point is available
      total_waited_secs = 0
      while self.lastest_checkpoint == checkpoint:
          time.sleep(
              30
          )  # sleep 30 seconds waiting for a new checkpoint
          checkpoint = tf.train.latest_checkpoint(self.checkpoints_path)
          total_waited_secs += 30
          if total_waited_secs > 30 * 60 * 60:
              raise EvaluatorStops(
                  "Waited more than half an hour to load a new checkpoint"
              )
  
      # restore the checkpoint
      self.saver.restore(session, checkpoint)
      self.lastest_checkpoint = checkpoint
      self.eval_step = int(self.lastest_checkpoint.split("-")[-1])
  
imports: import argparse
  import logging
  import multiprocessing
  import os
  import random
  import sys
  import time
  from xml.etree import ElementTree
  import numpy
  import tensorflow
  from tensorflow.contrib import slim
  from tensorflow.contrib.slim.python.slim.nets.inception_v3 import inception_v3, inception_v3_arg_scope
  from tensorflow.python.framework.errors_impl import OutOfRangeError
  from tensorflow.python.training import session_run_hook
  from tensorflow.python.training.basic_session_run_hooks import StopAtStepHook
  from tensorflow.python.training.monitored_session import SingularMonitoredSession
  import tensorlayer
label_desc: Use image node_id 2 for calling the EvaluatorHook obj's underlying member method code with example usage: obj.after_create_session(session, coord) without return types