code: def testAddSteps(self):
      spec = specs.TensorSpec([3], tf.int32, "lidar")
      replay_buffer = episodic_replay_buffer.EpisodicReplayBuffer(
          spec,
          capacity=2,
          begin_episode_fn=lambda _: False,
          end_episode_fn=lambda _: False,
      )
      episode_id = replay_buffer.create_episode_ids()
  
      values = np.ones(spec.shape.as_list())
      values = np.stack([values, 10 * values, 100 * values])
      episode_id = replay_buffer.add_sequence(values, episode_id)
      sample = lambda: sample_as_dataset(replay_buffer, 3, 10)[0]
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(tf.compat.v1.local_variables_initializer())
      self.evaluate(episode_id)
      sample_ = self.evaluate(sample())
      self._assertContains([values], list(sample_))
  
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 17 for calling the EpisodicReplayBufferTest obj's underlying member method code with example usage: obj.testAddSteps() without return types