0f2f31b4fef8bbc4fb18e52bc3c376a725f13939,infcomp/modules.py,Artifact,loss,#Artifact#Any#,344

Before Change

                        logpdf += log_one_minus_probabilities[b]
            elif isinstance(proposal, DiscreteProposal):
                util.log_error("Unimplemented")
            elif isinstance(proposal, CategoricalProposal):
                util.log_error("Unimplemented")
            else:
                util.log_error("Unsupported proposal distribution: " + proposal_type)

After Change

                log_weights = torch.log(proposal_output + util.epsilon)
                for b in range(sub_batch_size):
                    value = sub_batch[b].samples[time_step].value[0]
                    logpdf += log_weights[b, int(value)]
            elif isinstance(distribution, Categorical):
                util.log_error("Unimplemented")
            else:
                util.log_error("Unsupported distribution: " + distribution.name())

Instances