evaluation_test.py 文件源码

def testFinalOpsOnEvaluationLoop(self):
    value_op, update_op = slim.metrics.streaming_accuracy(
        self._predictions, self._labels)
    init_op = tf.group(tf.initialize_all_variables(),
                       tf.initialize_local_variables())
    # Create Checkpoint and log directories
    chkpt_dir = os.path.join(self.get_temp_dir(), 'tmp_logs/')
    gfile.MakeDirs(chkpt_dir)
    logdir = os.path.join(self.get_temp_dir(), 'tmp_logs2/')
    gfile.MakeDirs(logdir)

    # Save initialized variables to checkpoint directory
    saver = tf.train.Saver()
    with self.test_session() as sess:
      init_op.run()
      saver.save(sess, os.path.join(chkpt_dir, 'chkpt'))

    # Now, run the evaluation loop:
    accuracy_value = slim.evaluation.evaluation_loop(
        '', chkpt_dir, logdir, eval_op=update_op, final_op=value_op,
        max_number_of_evaluations=1)
    self.assertAlmostEqual(accuracy_value, self._expected_accuracy)