code: def _slice_split_info_to_instruction_dicts(self, list_sliced_split_info):
      
      instruction_dicts = []
      for sliced_split_info in list_sliced_split_info:
        mask = splits_lib.slice_to_percent_mask(sliced_split_info.slice_value)
  
        # Compute filenames from the given split
        filepaths = list(sorted(self._build_split_filenames(
            split_info_list=[sliced_split_info.split_info],
        )))
  
        # Compute the offsets
        if sliced_split_info.split_info.num_examples:
          shard_id2num_examples = splits_lib.get_shard_id2num_examples(
              sliced_split_info.split_info.num_shards,
              sliced_split_info.split_info.num_examples,
          )
          mask_offsets = splits_lib.compute_mask_offsets(shard_id2num_examples)
        else:
          logging.warning(
              "Statistics not present in the dataset. TFDS is not able to load "
              "the total number of examples, so using the subsplit API may not "
              "provide precise subsplits."
          )
          mask_offsets = [0] * len(filepaths)
  
        for filepath, mask_offset in zip(filepaths, mask_offsets):
          instruction_dicts.append({
              "filepath": filepath,
              "mask": mask,
              "mask_offset": mask_offset,
          })
      return instruction_dicts
docs: Return the list of files and reading mask of the files to read.