net.py 文件源码

def lf(self, x):
        mu, ln_var = self.encode(x)
        batchsize = len(mu.data)
        # reconstruction loss
        rec_loss = 0
        for l in six.moves.range(self.k):
            z = F.gaussian(mu, ln_var)
            rec_loss += F.bernoulli_nll(x, self.decode(z, sigmoid=False)) \
                / (self.k * batchsize)
        self.rec_loss = rec_loss
        self.loss = self.rec_loss + \
            self.C * gaussian_kl_divergence(mu, ln_var) / batchsize
        return self.loss