dcgan.py 文件源码

def generator_model():
    model = Sequential()
    model.add(Dense(input_dim=100, output_dim=1024))
    model.add(Activation('tanh'))
    model.add(Dense(128*7*7))
    model.add(BatchNormalization())
    model.add(Activation('tanh'))
    model.add(Reshape((128,7,7), input_shape=(128*7*7,)))
    model.add(UpSampling2D(size=(2,2), dim_ordering="th"))
    model.add(Convolution2D(64,5,5, border_mode='same', dim_ordering="th"))
    model.add(Activation('tanh'))
    model.add(UpSampling2D(size=(2,2), dim_ordering="th"))
    model.add(Convolution2D(1,5,5, border_mode='same', dim_ordering="th"))
    model.add(Activation('tanh'))
    return model