code: def testCheckpoint(self):
      spec = self.default_specs()
      replay_table = episodic_table.EpisodicTable(spec, capacity=3)
      empty_values = self.np_values(spec, 0)
      test_values = self.np_values(spec, 5)
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(replay_table.append(1, test_values))
  
      checkpoint = tf.train.Checkpoint(table=replay_table)
      tmpdir = self.get_temp_dir()
      if tf.executing_eagerly():
          location = checkpoint.save(os.path.join(tmpdir, "ckpt"))
      else:
          with self.cached_session() as sess:
              location = checkpoint.save(
                  os.path.join(tmpdir, "ckpt"), session=sess
              )
      reload_replay_table = episodic_table.EpisodicTable(
          spec, capacity=3
      )
      reload_checkpoint = tf.train.Checkpoint(table=reload_replay_table)
      status = reload_checkpoint.restore(location)
      status.assert_consumed()
      with self.cached_session() as sess:
          status.initialize_or_restore(session=sess)
      self._test_episode_lists(replay_table, empty_values, test_values)
      self._test_episode_lists(
          reload_replay_table, empty_values, test_values
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.replay_buffers import episodic_table
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 14 for calling the EpisodicTableTest obj's underlying member method code with example usage: obj.testCheckpoint() without return types