Lab-10장 코드에 관한 질문입니다.

[minocrafft]

`with summary_writer.as_default(): # for tensorboard for epoch in range(start_epoch, training_epochs): for idx, (train_input, train_label) in enumerate(train_dataset):
grads = grad(network, train_input, train_label) optimizer.apply_gradients(grads_and_vars=zip(grads, network.variables))

            train_loss = loss_fn(network, train_input, train_label)
            train_accuracy = accuracy_fn(network, train_input, train_label)
            
            for test_input, test_label in test_dataset:                
                test_accuracy = accuracy_fn(network, test_input, test_label)

            tf.summary.scalar(name='train_loss', data=train_loss, step=counter)
            tf.summary.scalar(name='train_accuracy', data=train_accuracy, step=counter)
            tf.summary.scalar(name='test_accuracy', data=test_accuracy, step=counter)

            print(
                "Epoch: [%2d] [%5d/%5d] time: %4.4f, train_loss: %.8f, train_accuracy: %.4f, test_Accuracy: %.4f" \
                % (epoch, idx, training_iterations, time() - start_time, train_loss, train_accuracy,
                   test_accuracy))
            counter += 1                
    checkpoint.save(file_prefix=checkpoint_prefix + '-{}'.format(counter))`

부분에서 train 과정에서 test 데이터를 매 epoch마다 사용해서 검증하는 것이 이해가 잘 안되는데 이런 상황이면 test가 아니라 validation으로 봐야되지 않나요?

궁금해서 질문남깁니다.