f3ed294875549679cb8d365e6604a4d4545de31b,gpytorch/mlls/variational_elbo.py,VariationalELBOEmpirical,forward,#VariationalELBOEmpirical#Any#Any#,74

Before Change

        kl_divergence = kl_divergence.div(self.num_data)

        res = log_likelihood - kl_divergence
        for _, param, prior in self.named_parameter_priors():
            res.add_(prior.log_prob(param).sum().div(self.num_data))
        for _, params, transform, prior in self.named_derived_priors():
            res.add_(prior.log_prob(transform(*params)).sum().div(self.num_data))
        return res

After Change

        res = log_likelihood - kl_divergence
        for _, prior, params, tf in self.named_priors():
            lp_arg = params[0] if tf is None else tf(*params)
            res.add_(prior.log_prob(lp_arg).sum().div(self.num_data))
        return res

Instances