def test_enqueue_dequeue(self):
    """Test enqueueing a dequeueing from a NeuralQueueCell.

    The sequence of operations is:
      enqueue([1.0, 0.0, 0.0])
      enqueue([0.0, 1.0, 0.0])
      dequeue()
    """
    input_values = np.array([[[[1.0, 0.0, 0.0]],
                              [[0.0, 1.0, 0.0]],
                              [[0.0, 0.0, 1.0]]]])
    expected_values = np.array([[[1.0, 0.0, 0.0],
                                 [0.0, 1.0, 0.0],
                                 [0.0, 0.0, 1.0],
                                 [0.0, 0.0, 0.0],
                                 [0.0, 0.0, 0.0],
                                 [0.0, 0.0, 0.0]]])
    expected_read_strengths = np.array([
        [[[0.0], [1.0], [0.0], [0.0], [0.0], [0.0]]]])
    expected_write_strengths = np.array([
        [[[0.0], [0.0], [0.0], [1.0], [0.0], [0.0]]]])
    expected_front = np.array([[[0.0, 1.0, 0.0]]])

    batch_size = 1
    num_units = 8
    embedding_size = 3
    memory_size = 6

    queue = neural_stack.NeuralQueueCell(num_units, memory_size, embedding_size)
    rnn_input = tf.constant(input_values, dtype=tf.float32)

    queue_zero_state = tf.zeros([batch_size, num_units])
    controller_outputs = queue.call_controller(None, None, queue_zero_state,
                                               batch_size)
    assert_controller_shapes(self, controller_outputs,
                             queue.get_controller_shape(batch_size))

    (outputs, state) = tf.nn.dynamic_rnn(cell=queue,
                                         inputs=rnn_input,
                                         time_major=False,
                                         dtype=tf.float32)

    with self.test_session() as sess:
      sess.run(tf.global_variables_initializer())
      _, state_vals = sess.run([outputs, state])
      (_, queue_front, values, read_strengths, write_strengths) = state_vals

      self.assertAllClose(expected_values, values)
      self.assertAllClose(expected_write_strengths, write_strengths)
      self.assertAllClose(expected_read_strengths, read_strengths)
      self.assertAllClose(expected_front, queue_front)
Test enqueueing a dequeueing from a NeuralQueueCell.

    The sequence of operations is:
      enqueue([1.0, 0.0, 0.0])
      enqueue([0.0, 1.0, 0.0])
      dequeue()
    
tensor2tensor/models/research/neural_stack_test.py