GAN_Example_2.py

def generator():
    """ Declare generator """

    model = Sequential()
    model.add(Dense(256, input_shape=(10,)))
    model.add(LeakyReLU(alpha=0.2))  # 使用 LeakyReLU 激活函數
    model.add(BatchNormalization(momentum=0.8))  # 使用 BatchNormalization 優化
    model.add(Dense(512))
    model.add(LeakyReLU(alpha=0.2))
    model.add(BatchNormalization(momentum=0.8))
    model.add(Dense(1024))
    model.add(LeakyReLU(alpha=0.2))
    model.add(BatchNormalization(momentum=0.8))
    model.add(Dense(width  * height * channels, activation='tanh'))
    model.add(Reshape((width, height, channels)))
    model.summary()

    return model