code: def test_single_episode_dataset(self):
      sequence_length = 3
      self._insert_random_data(
          self._env,
          num_steps=sequence_length,
          sequence_length=sequence_length,
      )
  
      replay = reverb_replay_buffer.ReverbReplayBuffer(
          self._data_spec,
          self._table_name,
          sequence_length=None,
          local_server=self._server,
      )
  
      # Make sure observations are off by 1 given we are counting transitions in
      # the env observations.
      dataset = replay.as_dataset()
      for sample, _ in dataset.take(5):
          episode, step = sample.observation
          self.assertEqual((sequence_length,), episode.shape)
          self.assertEqual((sequence_length,), step.shape)
          self.assertAllEqual(
              [0] * sequence_length, episode - episode[:1]
          )
          self.assertAllEqual(
              list(range(sequence_length)), step - step[:1]
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import reverb
  import tensorflow
  from tf_agents.drivers import py_driver
  from tf_agents.environments import test_envs
  from tf_agents.policies import random_py_policy
  from tf_agents.replay_buffers import reverb_replay_buffer
  from tf_agents.replay_buffers import reverb_utils
  from tf_agents.specs import array_spec
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 7 for calling the ReverbReplayBufferTest obj's underlying member method code with example usage: obj.test_single_episode_dataset() without return types