dcgan.py 文件源码

def discriminator_model():
    model = Sequential()
    model.add(Convolution2D(64,5,5,
                            border_mode='same',
                            input_shape=(1,28,28),
                            dim_ordering="th"))
    model.add(Activation('tanh'))
    model.add(MaxPooling2D(pool_size=(2,2), dim_ordering="th"))
    model.add(Convolution2D(128,5,5, border_mode='same', dim_ordering="th"))
    model.add(Activation('tanh'))
    model.add(MaxPooling2D(pool_size=(2,2), dim_ordering="th"))
    model.add(Flatten())
    model.add(Dense(1024))
    model.add(Activation('tanh'))
    model.add(Dense(1))
    model.add(Activation('sigmoid'))
    return model