def load_dataset(self, split, epoch=1, combine=False, **kwargs):
        """Load a given dataset split.

        Args:
            split (str): name of the split (e.g., train, valid, test)
        """
        dataset_map = OrderedDict()

        for lang in self.langs2id.keys():
            # Datasets are expected to be in "split.lang" format (Eg: train.en)
            language_split = "{}.{}".format(split, lang)

            block_dataset, sizes = self._load_single_lang_dataset(
                split=language_split, epoch=epoch
            )

            dataset_map[lang] = MaskedLMDataset(
                dataset=block_dataset,
                sizes=sizes,
                vocab=self.dictionary,
                pad_idx=self.dictionary.pad(),
                mask_idx=self.dictionary.mask(),
                classif_token_idx=self.dictionary.eos(),
                sep_token_idx=self.dictionary.eos(),
                shuffle=getattr(self.args, "shuffle", False),
                has_pairs=False,
                segment_id=self.langs2id[lang],
                seed=self.seed,
            )

        self.datasets[split] = MultiCorpusSampledDataset(dataset_map)
        logger.info(
            "{} {} {} examples".format(
                utils.split_paths(self.args.data)[epoch - 1],
                split,
                len(self.datasets[split]),
            )
        )
Load a given dataset split.

        Args:
            split (str): name of the split (e.g., train, valid, test)
        
structured_prompting/fairseq-version/fairseq/fairseq/tasks/cross_lingual_lm.py