def METHOD_NAME(self):
    """ Test utility for inserting upsample op """
    tf.compat.v1.reset_default_graph()
    inputs = tf.keras.Input(shape=(2, 2, 3,))
    # Insert channel in index position 1
    output = _insert_downsample_or_upsample_ops_if_needed(inputs, [1, 0, 1, 1], [1, 1, 1, 1])
    self.assertEqual([None, 2, 2, 4], output.shape.as_list())
    with tf.compat.v1.Session() as sess:
        random_input = tf.random.uniform(shape=(1, 2, 2, 3))
        inp = random_input.eval(session=sess)
        inputs_eval = sess.run(inputs, feed_dict={inputs: inp})
        output_eval = sess.run(output, feed_dict={inputs: inp})
    sess.close()
    # Check that inputs_eval and output_eval are equal once channel 1 is removed from output_eval
    self.assertTrue(np.array_equal(np.concatenate((output_eval[:, :, :, 0:1],
                                                   output_eval[:, :, :, 2:]),
                                                  axis=-1),
                                   inputs_eval))
    # Check that output_eval channel 1 is all zeros
    self.assertTrue(np.array_equal(np.zeros(output_eval[:, :, :, 1:2].shape), output_eval[:, :, :, 1:2]))