mnist_deep.py 文件源码

def main(flags):
    # ???????
    ds = mnist.Data(flags.directory)
    # tensorflow ??
    config = tf.ConfigProto()
    config.gpu_options.allow_growth = True
    # ??session
    with tf.Session(config=config) as session:
        # ??????
        model = Model('Model',
                      session,
                      flags.height,
                      flags.width,
                      flags.depth,
                      flags.feature_size,
                      flags.num_classes).build()
        # ??slot
        train = model.get_slot('train')
        predict = model.get_slot('predict')
        # ?????
        session.run(tf.global_variables_initializer())
        # ????
        for i in range(1, flags.nloop + 1):
            # ????batch???
            images_batch, labels_batch = ds.next_batch(flags.bsize)
            loss, train_accuracy = train(images_batch, labels_batch, 0.5)
            # ?100?????????????batch??accuracy
            if i % 100 == 0:
                print('Loop {}:\tloss={}\ttrain accuracy={}'.format(i, loss, train_accuracy))
        # ????????accuracy
        accuracy = predict(ds.test_images, ds.test_labels, 1.0)
        print('Accuracy on test set: {}'.format(accuracy))
    return 0