autoencoders.py 文件源码

def conv_autoencoder(X):
    X = X.reshape(X.shape[0], 28, 28, 1)

    inputs = Input(shape=(28, 28, 1))
    h = Conv2D(4, 3, 3, activation='relu', border_mode='same')(inputs)
    encoded = MaxPooling2D((2, 2))(h)
    h = Conv2D(4, 3, 3, activation='relu', border_mode='same')(encoded)
    h = UpSampling2D((2, 2))(h)
    outputs = Conv2D(1, 3, 3, activation='relu', border_mode='same')(h)

    model = Model(input=inputs, output=outputs)
    model.compile(optimizer='adam', loss='mse')
    model.fit(X, X, batch_size=64, nb_epoch=5)

    return model, Model(input=inputs, output=encoded)