network.py 文件源码

def build_output(self):
        mean = Dense(self.output_size, activation=MeanAct, kernel_initializer=self.init,
                     kernel_regularizer=l1_l2(self.l1_coef, self.l2_coef),
                     name='mean')(self.decoder_output)

        # Plug in dispersion parameters via fake dispersion layer
        disp = ConstantDispersionLayer(name='dispersion')
        mean = disp(mean)

        output = ColWiseMultLayer(name='output')([mean, self.sf_layer])

        nb = NB(disp.theta_exp)
        self.loss = nb.loss
        self.extra_models['dispersion'] = lambda :K.function([], [nb.theta])([])[0].squeeze()
        self.extra_models['mean_norm'] = Model(inputs=self.input_layer, outputs=mean)
        self.extra_models['decoded'] = Model(inputs=self.input_layer, outputs=self.decoder_output)
        self.model = Model(inputs=[self.input_layer, self.sf_layer], outputs=output)

        if self.ae:
            self.encoder = self.get_encoder()