metric_ops_test.py 文件源码

def testSingleUpdateNormalizedByLabels(self):
    np_predictions = np.asarray([2, 4, 6, 8], dtype=np.float32)
    np_labels = np.asarray([1, 3, 2, 3], dtype=np.float32)
    expected_error = np.mean(
        np.divide(np.absolute(np_predictions - np_labels),
                  np_labels))

    predictions = tf.constant(np_predictions, shape=(1, 4), dtype=tf.float32)
    labels = tf.constant(np_labels, shape=(1, 4))

    error, update_op = metrics.streaming_mean_relative_error(
        predictions, labels, normalizer=labels)

    with self.test_session() as sess:
      sess.run(tf.initialize_local_variables())
      self.assertEqual(expected_error, sess.run(update_op))
      self.assertEqual(expected_error, error.eval())