dcgan.py 文件源码

def discriminator_model():
    model = Sequential()
    model.add(
            Conv2D(64, (5, 5),
            padding='same',
            input_shape=(28, 28, 1))
            )
    model.add(Activation('tanh'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Conv2D(128, (5, 5)))
    model.add(Activation('tanh'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Flatten())
    model.add(Dense(1024))
    model.add(Activation('tanh'))
    model.add(Dense(1))
    model.add(Activation('sigmoid'))
    return model