aegans_recon.py 文件源码

def discriminator_model(self):
        model = Sequential()
        model.add(Convolution2D(
            8, 10, 10,
            border_mode='same',
            input_shape=(1, 144, 144)))
        model.add(Activation('tanh'))
        model.add(MaxPooling2D(pool_size=(4, 4)))
        model.add(Convolution2D(16, 10, 10))
        model.add(Activation('tanh'))
        model.add(MaxPooling2D(pool_size=(4, 4)))
        model.add(Flatten())
        model.add(Dense(128))
        model.add(Activation('tanh'))
        model.add(Dense(1))
        model.add(Activation('sigmoid'))
        return model