code: def testAddStepsGetEpisodes(self):
      spec = specs.TensorSpec([5], tf.int32, "lidar")
      replay_buffer = episodic_replay_buffer.EpisodicReplayBuffer(
          spec,
          capacity=2,
          begin_episode_fn=lambda _: False,
          end_episode_fn=lambda _: False,
      )
      episode_id_0 = replay_buffer.create_episode_ids()
      episode_id_1 = replay_buffer.create_episode_ids()
  
      values = np.ones(spec.shape.as_list())
      # Add episode_0 with 3 steps
      values_0 = np.stack((values, 10 * values, 100 * values))
      episode_id_0 = replay_buffer.add_sequence(values_0, episode_id_0)
      episode_0 = replay_buffer._get_episode(episode_id_0)
      # Add episode_1 with 2 steps
      values_1 = np.stack((2 * values, 20 * values))
      episode_id_1 = replay_buffer.add_sequence(values_1, episode_id_1)
      episode_1 = replay_buffer._get_episode(episode_id_1)
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(tf.compat.v1.local_variables_initializer())
      episode_0_value = self.evaluate(episode_0)
      episode_1_value = self.evaluate(episode_1)
  
      self.assertEqual(
          1, self.evaluate(replay_buffer._get_last_episode_id())
      )
      self.assertAllEqual(values_0, episode_0_value)
      self.assertAllEqual(values_1, episode_1_value)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.replay_buffers import episodic_replay_buffer
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
  from tensorflow.python.ops import list_ops
label_desc: Use image node_id 19 for calling the EpisodicReplayBufferTest obj's underlying member method code with example usage: obj.testAddStepsGetEpisodes() without return types