code: def testAddStepsUnknownBatchDims(self):
      if tf.executing_eagerly():
          self.skipTest("b/123770194")
  
      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_ids = replay_buffer.create_episode_ids()
  
      values = np.ones(spec.shape.as_list())
      values = np.stack([values, 10 * values, 100 * values])
      batch = tf.compat.v1.placeholder(shape=[None, 3], dtype=tf.int32)
      sample, _ = sample_as_dataset(
          replay_buffer, num_steps=3, batch_size=10
      )
      with self.cached_session() as sess:
          sess.run(tf.compat.v1.global_variables_initializer())
          sess.run(tf.compat.v1.local_variables_initializer())
          sess.run(
              replay_buffer.add_sequence(batch, episode_ids),
              {batch: values},
          )
          sample_ = sess.run(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 20 for calling the EpisodicReplayBufferTest obj's underlying member method code with example usage: obj.testAddStepsUnknownBatchDims() without return types