code: def testDeterministicAsDatasetWithNumSteps(self):
      max_length = 4
      buffer_batch_size = 5
      unused_rb, rb_values = self._create_collect_rb_dataset(
          max_length,
          buffer_batch_size,
          num_adds=4,
          sample_batch_size=None,
          num_steps=2,
      )
  
      # Expect to get each episode 2 frames at a time when
      # num_steps=2 and max_length=4.  Once an episode is finished, move on
      # to the next episode.
      expected = np.asarray(
          [
              # First 2 batches are ep0 frames 0..3.
              [0, 1],
              [2, 3],
              # Next 2 batches are ep1 frames 0..3.
              [10, 11],
              [12, 13],
              # ...
              [20, 21],
              [22, 23],
              [30, 31],
              [32, 33],
              [40, 41],
              [42, 43],
          ]
      )
      self.assertAllEqual(expected, rb_values)
  
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 21 for calling the TFUniformReplayBufferTest obj's underlying member method code with example usage: obj.testDeterministicAsDatasetWithNumSteps() without return types