code: def testGatherAll(self):
      spec = specs.TensorSpec([], tf.int32, "action")
      replay_buffer = episodic_replay_buffer.EpisodicReplayBuffer(
          spec,
          begin_episode_fn=lambda _: False,
          end_episode_fn=lambda _: False,
      )
      replay_buffer_stateful = (
          episodic_replay_buffer.StatefulEpisodicReplayBuffer(
              replay_buffer, num_episodes=1
          )
      )
  
      action_state = common.create_variable(
          "counter", -1, dtype=spec.dtype
      )
      action = lambda: tf.expand_dims(action_state.assign_add(1), 0)
  
      # pylint: disable=unnecessary-lambda
      items = lambda: replay_buffer.gather_all()
      expected = [list(range(10))]
      if tf.executing_eagerly():
          add_op = lambda: replay_buffer_stateful.add_batch(action())
      else:
          add_op = replay_buffer_stateful.add_batch(action())
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(tf.compat.v1.local_variables_initializer())
  
      for _ in range(10):
          self.evaluate(add_op)
  
      items_ = self.evaluate(items())
      self.assertAllClose(expected, items_)
  
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 10 for calling the StatefulEpisodicReplayBufferTest obj's underlying member method code with example usage: obj.testGatherAll() without return types