def METHOD_NAME(self):
    self.data, self.slices, sizes = read_tu_data(self.raw_dir, self.name)
    if self.pre_filter is not None or self.pre_transform is not None:
        data_list = [self.get(idx) for idx in range(len(self))]
        if self.pre_filter is not None:
            data_list = [d for d in data_list if self.pre_filter(d)]
        if self.pre_transform is not None:
            data_list = [self.pre_transform(d) for d in data_list]
        self.data, self.slices = self.collate(data_list)
        self._data_list = None  # Reset cache.
    torch.save((self._data.to_dict(), self.slices, sizes),
               self.processed_paths[0])