def METHOD_NAME(self):
    positive_matches = tf.constant(
        [
            True,
            False,
            False,
            False,
            False,
            False,
            False,
            False,
            False,
            False,
        ]
    )
    negative_matches = tf.constant(
        [False, True, True, True, True, True, True, True, True, True]
    )
    num_samples = 5
    positive_fraction = 0.1
    res = balanced_sample(
        positive_matches, negative_matches, num_samples, positive_fraction
    )
    # no positive is chosen
    self.assertAllClose(res[0], 0)
    self.assertAllClose(tf.reduce_sum(res), 5)