code: def testGetNext(self):
      max_length = 3
      spec = specs.TensorSpec([], tf.int64, "observation")
      replay_buffer = tf_uniform_replay_buffer.TFUniformReplayBuffer(
          spec, batch_size=2, max_length=max_length
      )
  
      @common.function(autograph=True)
      def add_data():
          for t in range(4):
              obs = np.array([t, t + max_length], dtype=np.int64)
              replay_buffer.add_batch(obs)
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      add_data()
      self.evaluate_last_func_if_graph_mode()
  
      experience, _ = replay_buffer.get_next(
          sample_batch_size=256, num_steps=2, time_stacked=True
      )
      correct_next_state = tf.equal(
          experience[:, 0] + 1, experience[:, 1]
      )
      all_correct = self.evaluate(tf.reduce_all(correct_next_state))
      self.assertTrue(all_correct)
  
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 tf_uniform_replay_buffer
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 27 for calling the TFUniformReplayBufferTest obj's underlying member method code with example usage: obj.testGetNext() without return types