plain_cnn.py 文件源码

def test(self, dataloader, backup_path, epoch, batch_size=128):
        gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.25)
        self.sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options))
        # ????
        self.saver = tf.train.Saver(write_version=tf.train.SaverDef.V2)
        model_path = os.path.join(backup_path, 'model_%d.ckpt' % (epoch))
        assert(os.path.exists(model_path+'.index'))
        self.saver.restore(self.sess, model_path)
        print('read model from %s' % (model_path))
        # ??????????
        accuracy_list = []
        test_images = dataloader.data_augmentation(dataloader.test_images,
            flip=False, crop=True, crop_shape=(24,24,3), whiten=True, noise=False)
        test_labels = dataloader.test_labels
        for i in range(0, dataloader.n_test, batch_size):
            batch_images = test_images[i: i+batch_size]
            batch_labels = test_labels[i: i+batch_size]
            [avg_accuracy] = self.sess.run(
                fetches=[self.accuracy], 
                feed_dict={self.images:batch_images, 
                           self.labels:batch_labels,
                           self.keep_prob:1.0})
            accuracy_list.append(avg_accuracy)
        print('test precision: %.4f' % (numpy.mean(accuracy_list)))
        self.sess.close()