evaluation_test.py 文件源码

def testRestoredModelPerformance(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model.ckpt')
    log_dir = os.path.join(self.get_temp_dir(), 'log_dir1/')

    # First, save out the current model to a checkpoint:
    init_op = tf.group(tf.initialize_all_variables(),
                       tf.initialize_local_variables())
    saver = tf.train.Saver()
    with self.test_session() as sess:
      sess.run(init_op)
      saver.save(sess, checkpoint_path)

    # Next, determine the metric to evaluate:
    value_op, update_op = slim.metrics.streaming_accuracy(
        self._predictions, self._labels)

    # Run the evaluation and verify the results:
    accuracy_value = slim.evaluation.evaluate_once(
        '',
        checkpoint_path,
        log_dir,
        eval_op=update_op,
        final_op=value_op)
    self.assertAlmostEqual(accuracy_value, self._expected_accuracy)