dbae22f30a6c49b4cdc90b5403436555fb3ad4fa,pixyz/distributions/mixture_distributions.py,MixtureModel,log_likelihood,#MixtureModel#Any#,120

Before Change

        return torch.stack(log_likelihood_all, dim=0)

    def log_likelihood(self, x_dict):
        visible_dict = get_dict_values(x_dict, self._visible_var, return_dict=True)
        loglike_all_hidden = self.log_likelihood_all_hidden(visible_dict)

        hidden_sample_idx = get_dict_values(x_dict, self._hidden_var, return_dict=False)[0].argmax(dim=-1)
        loglike = loglike_all_hidden[hidden_sample_idx, torch.arange(len(hidden_sample_idx))]

        return loglike

After Change

    def log_likelihood(self, x_dict):
        // log p(x)
        loglike = self.log_likelihood_all_hidden(x_dict)
        return torch.logsumexp(loglike, 0)

    def _log_likelihood_given_hidden(self, x_dict):
        // log p(x, z)
        visible_dict = get_dict_values(x_dict, self._var, return_dict=True)

Instances