test_metrics_tf.py 文件源码

def _test_metric_spec(self, metric_spec, hyps, refs, expected_scores):
        """Tests a MetricSpec"""
        predictions = {"predicted_tokens": tf.placeholder(dtype=tf.string)}
        labels = {"target_tokens": tf.placeholder(dtype=tf.string)}

        value, update_op = metric_spec.create_metric_ops(
            None, labels, predictions)

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())
            sess.run(tf.local_variables_initializer())

            scores = []
            for hyp, ref in zip(hyps, refs):
                hyp = hyp.split(" ")
                ref = ref.split(" ")
                sess.run(update_op, {
                    predictions["predicted_tokens"]: [hyp],
                    labels["target_tokens"]: [ref]
                })
                scores.append(sess.run(value))

            for score, expected in zip(scores, expected_scores):
                self.assertNDArrayNear(score, expected, 0.01)
                self.assertNDArrayNear(score, expected, 0.01)