model_gan.py 文件源码

def __call__(self):
        model = Sequential()

        model.add(Dense(1024, kernel_initializer=self.initializer, \
            kernel_regularizer=self.regularizer, input_shape=(self.z_dim,)))
        model.add(BatchNormalization())
        model.add(Activation('relu'))

        model.add(Dense(7 * 7 * 128, kernel_initializer=self.initializer, \
            kernel_regularizer=self.regularizer))
        model.add(Reshape((7, 7, 128)))

        model.add(BatchNormalization())
        model.add(Activation('relu'))

        # Convolution transpose layer
        model.add(Conv2DTranspose(64, kernel_size=(4, 4), strides=(2, 2), padding='same',\
            kernel_initializer=self.initializer, kernel_regularizer=self.regularizer))
        model.add(BatchNormalization())
        model.add(Activation('relu'))

        model.add(Conv2DTranspose(1, kernel_size=(4, 4), strides=(2, 2), padding='same',\
            kernel_initializer=self.initializer, kernel_regularizer=self.regularizer))
        model.add(Activation('sigmoid'))
        model.add(Reshape((784,)))

        return model