code: def testSingleDeterministicPassAsDatasetWithNumStepsBatchSizeAndShift(
      self,
  ):
      # Add 6 episodes, repeating 3 episodes twice.
      replay_buffer = self._create_rb_and_add_3N_episodes(
          window_shift=1, drop_remainder=False, repeat=2
      )
      with self.cached_session() as session:
          pass
      itr = iterator_from_dataset(
          replay_buffer,
          batch_size=3,
          num_steps=5,
          single_deterministic_pass=True,
          session=session,
      )
  
      # Due to window_shift == 1, we see two instances of each block: the
      # original, and one shifted left by 1.  For example, if we have two episodes
      # in a batch entry, [1, 10, 100] and [1, 10, 100] again, then with num_steps
      # == 5 we'll see one block that's [1, 10, 100, 1, 10] and a second one
      # that's shifted: [10, 100, 1, 10, 100].
      tf.nest.map_structure(
          self.assertAllEqual,
          {
              "a": _a(
                  [
                      [1, 10, 100, 1, 10],
                      [2, 20, 200, 3, 30],
                      [-1, -10, -100, -1, -10],
                  ]
              )
          },
          next(itr),
      )
      tf.nest.map_structure(
          self.assertAllEqual,
          {
              "a": _a(
                  [
                      [10, 100, 1, 10, 100],
                      [20, 200, 3, 30, 300],
                      [-10, -100, -1, -10, -100],
                  ]
              )
          },
          next(itr),
      )
      tf.nest.map_structure(
          self.assertAllEqual,
          {
              "a": _a(
                  [
                      [200, 3, 30, 300, 2],
                      [3, 30, 300, 2, 20],
                      [30, 300, 2, 20, 200],
                  ]
              )
          },
          next(itr),
      )
      tf.nest.map_structure(
          self.assertAllEqual,
          {
              "a": _a(
                  [
                      [300, 2, 20, 200, 3],
                      [2, 20, 200, 3, 30],
                      [20, 200, 3, 30, 300],
                  ]
              )
          },
          next(itr),
      )
      with self.assertRaises(
          (tf.errors.OutOfRangeError, StopIteration)
      ):
          next(itr)
  
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 34 for calling the EpisodicReplayBufferTest obj's underlying member method code with example usage: obj.testSingleDeterministicPassAsDatasetWithNumStepsBatchSizeAndShift() without return types