vae_m1.py 文件源码

def log_pz(self, z, mean, ln_var):
        if self.type_pz == "gaussianmarg":
            # \int q(z)logp(z)dz = -(J/2)*log2pi - (1/2)*sum_{j=1}^{J} (mu^2 + var)
            # See Appendix B [Auto-Encoding Variational Bayes](http://arxiv.org/abs/1312.6114)
            # See https://github.com/dpkingma/nips14-ssl/blob/master/anglepy/models/VAE_YZ_X.py line 106
            log_pz = -0.5 * (math.log(2.0 * math.pi) + mean * mean + F.exp(ln_var))
        elif self.type_pz == "gaussian":
            log_pz = -0.5 * math.log(2.0 * math.pi) - 0.5 * z ** 2
        return F.sum(log_pz, axis=1)

    # this will not be used for bernoulli decoder