vae_m2.py 文件源码

def __init__(self, conf, name="vae"):
        conf.check()
        self.encoder_xy_z, self.encoder_x_y, self.decoder = self.build(conf)
        self.name = name

        self.optimizer_encoder_xy_z = optimizers.Adam(alpha=conf.learning_rate, beta1=conf.gradient_momentum)
        self.optimizer_encoder_xy_z.setup(self.encoder_xy_z)
        # self.optimizer_encoder_xy_z.add_hook(optimizer.WeightDecay(0.00001))
        self.optimizer_encoder_xy_z.add_hook(GradientClipping(conf.gradient_clipping))

        self.optimizer_encoder_x_y = optimizers.Adam(alpha=conf.learning_rate, beta1=conf.gradient_momentum)
        self.optimizer_encoder_x_y.setup(self.encoder_x_y)
        # self.optimizer_encoder_x_y.add_hook(optimizer.WeightDecay(0.00001))
        self.optimizer_encoder_x_y.add_hook(GradientClipping(conf.gradient_clipping))

        self.optimizer_decoder = optimizers.Adam(alpha=conf.learning_rate, beta1=conf.gradient_momentum)
        self.optimizer_decoder.setup(self.decoder)
        # self.optimizer_decoder.add_hook(optimizer.WeightDecay(0.00001))
        self.optimizer_decoder.add_hook(GradientClipping(conf.gradient_clipping))

        self.type_pz = conf.type_pz
        self.type_qz = conf.type_qz