autoencoder.py 文件源码

def conv_autoencode_mnist():
    (x_train, y_train), (x_test, y_test) = load_mnist(flatten=False)
    autoencoder = build_conv_autoencoder()
    autoencoder.summary()
    autoencoder.fit(x_train, x_train,
        epochs=55,
        batch_size=128,
        shuffle=True,
        validation_data=(x_test, x_test),
        callbacks=[TensorBoard(log_dir='./tmp/autoencoder')])   

    decoded_imgs = autoencoder.predict(x_test)
    plot_imgs_and_reconstructions(x_test, decoded_imgs, n=10)