re_index

[Chris33Edwards]

Hi, nice work! But I have a question.

        unseen_query_samples = [self.dataset.train_seen[ids] for ids in unseen_query]
        unseen_querys_x, unseen_querys_len, unseen_querys_y = get_samples(unseen_query_samples, self.device, self.config['encoder_type'])
        seen_query_samples = [self.dataset.train_seen[ids] for ids in seen_query]
        seen_querys_x, seen_querys_len, seen_querys_y = get_samples(seen_query_samples, self.device, self.config['encoder_type'])

        re_index = torch.sort(torch.cat([seen_class_idxs, unseen_class_idxs], 0).to(self.device))[1]
        unseen_querys_y = re_index[unseen_querys_y]
        seen_querys_y = re_index[seen_querys_y]

        # if epoch >= 15:
        # novel_querys = self.model(novel_querys_x, novel_querys_len, memory_protos, novel_protos,
        #                                      after_memory_protos, after_novel_protos, v, 'adapt')
        # memory_querys = self.model(memory_querys_x, memory_querys_len, memory_protos, novel_protos,
        #                                       after_memory_protos, after_novel_protos, v, 'adapt')

        unseen_querys = self.model(unseen_querys_x, unseen_querys_len, protos, semantic_components, n_seen,
                                   'sample_adapt')
        seen_querys = self.model(seen_querys_x, seen_querys_len, protos, semantic_components, n_seen, 'sample_adapt')


        loss_unseen, output_unseen = self.loss_fn(protos, unseen_querys, unseen_querys_y, self.model.tau)
        loss_seen, output_seen = self.loss_fn(protos, seen_querys, seen_querys_y, self.model.tau)

Why do re_index seen_querys_y and unseen_querys_y?