How to use the lineflow.core.ZipDataset function in lineflow

def setUp(self):
        self.n = 5
        self.base = range(100)
        self.data = ZipDataset(*[self.base for _ in range(5)])

def test_returns_zip_dataset(self):
        self.assertIsInstance(self.data, ZipDataset)

def test_zips_multiple_files(self):
        fp = self.fp
        lines = self.lines

        data = TextDataset([fp.name, fp.name], mode='zip')
        for x, y in zip(data, lines):
            self.assertTupleEqual(x, (y, y))
        for j, y in enumerate(lines):
            self.assertTupleEqual(data[j], (y, y))
        self.assertEqual(len(data), len(lines))
        self.assertEqual(data._length, len(lines))
        self.assertIsInstance(data._dataset, lineflow.core.ZipDataset)
        self.assertIsInstance(data.map(lambda x: x)._dataset, TextDataset)

with io.open(path, 'wb') as f:
            pickle.dump(dataset, f)
        return dataset

    def loader(path):
        with io.open(path, 'rb') as f:
            return pickle.load(f)

    pkl_path = os.path.join(root, 'cnndm.pkl')
    return download.cache_or_load_file(pkl_path, creator, loader)


cached_get_wmt14 = lru_cache()(get_wmt14)


class Wmt14(ZipDataset):
    def __init__(self, split: str = 'train') -> None:
        if split not in {'train', 'dev', 'test'}:
            raise ValueError(f"only 'train', 'dev' and 'test' are valid for 'split', but '{split}' is given.")

        raw = cached_get_wmt14()
        super(Wmt14, self).__init__(*raw[split])

def lineflow_zip(*datasets: List[DatasetMixin]) -> ZipDataset:
    return ZipDataset(*datasets)

with io.open(path, 'wb') as f:
            pickle.dump(dataset, f)
        return dataset

    def loader(path):
        with io.open(path, 'rb') as f:
            return pickle.load(f)

    pkl_path = os.path.join(root, 'cnndm.pkl')
    return download.cache_or_load_file(pkl_path, creator, loader)


cached_get_cnn_dailymail = lru_cache()(get_cnn_dailymail)


class CnnDailymail(ZipDataset):
    def __init__(self, split: str = 'train') -> None:
        if split not in {'train', 'dev', 'test'}:
            raise ValueError(f"only 'train', 'dev' and 'test' are valid for 'split', but '{split}' is given.")

        raw = cached_get_cnn_dailymail()
        super(CnnDailymail, self).__init__(*raw[split])

def __init__(self,
                 paths: Union[str, List[str]],
                 encoding: str = 'utf-8',
                 mode: str = 'zip') -> None:
        if isinstance(paths, str):
            dataset = easyfile.TextFile(paths, encoding)
        elif isinstance(paths, list):
            if mode == 'zip':
                dataset = ZipDataset(*[easyfile.TextFile(p, encoding) for p in paths])
            elif mode == 'concat':
                dataset = ConcatDataset(*[easyfile.TextFile(p, encoding) for p in paths])
            else:
                raise ValueError(f"only 'zip' and 'concat' are valid for 'mode', but '{mode}' is given.")

        super().__init__(dataset)