How to use the lineflow.download.cached_download function in lineflow

def test_fails_to_make_directory(self, f):
        f.side_effect = OSError()
        with self.assertRaises(OSError):
            download.cached_download('https://example.com')

def test_cache_exists(self, f):
        f.return_value = True
        url = 'https://example.com'
        path = download.cached_download(url)
        self.assertEqual(path, f'{self.temp_dir}/_dl_cache/{hashlib.md5(url.encode("utf-8")).hexdigest()}')

def creator(path):
        archive_path = download.cached_download(url)
        with tarfile.open(archive_path, 'r') as archive:
            print(f'Extracting to {root}...')
            archive.extractall(root)

        extracted_path = os.path.join(root, 'aclImdb')

        dataset = {}
        for split in ('train', 'test'):
            pos_path = os.path.join(extracted_path, split, 'pos')
            neg_path = os.path.join(extracted_path, split, 'neg')
            dataset[split] = [x.path for x in os.scandir(pos_path)
                              if x.is_file() and x.name.endswith('.txt')] + \
                             [x.path for x in os.scandir(neg_path)
                              if x.is_file() and x.name.endswith('.txt')]

        with io.open(path, 'wb') as f:

def creator(path):
        archive_path = download.cached_download(url)
        target_path = os.path.join(root, 'raw')
        with tarfile.open(archive_path, 'r') as archive:
            print(f'Extracting to {target_path}')
            archive.extractall(target_path)

        dataset = {}
        for split in ('train', 'dev', 'test'):
            src_path = f'{split if split != "dev" else "val"}.txt.src'
            tgt_path = f'{split if split != "dev" else "val"}.txt.tgt.tagged'
            dataset[split] = (
                easyfile.TextFile(os.path.join(target_path, src_path)),
                easyfile.TextFile(os.path.join(target_path, tgt_path))
            )

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

def creator(path):
        dataset = {}
        fieldnames = ('quality', 'id1', 'id2', 'string1', 'string2')
        for split in ('train', 'test'):
            data_path = download.cached_download(url.format(split))
            with io.open(data_path, 'r', encoding='utf-8') as f:
                f.readline()  # skip header
                reader = csv.DictReader(f, delimiter='\t', fieldnames=fieldnames)
                dataset[split] = [dict(row) for row in reader]

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

def list_creator(path):
        archive_path = download.cached_download(url)
        with zipfile.ZipFile(archive_path, 'r') as archive:
            dataset = {}
            path2key = {f'{name}/wiki.train.tokens': 'train',
                        f'{name}/wiki.valid.tokens': 'dev',
                        f'{name}/wiki.test.tokens': 'test'}
            for p, key in path2key.items():
                print(f'Extracting {p}...')
                with archive.open(p) as f:
                    lines = [line.decode('utf-8').rstrip(os.linesep) for line in f]
                dataset[key] = lines

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

def creator(path):
        dataset = {}
        for split in ('train', 'dev', 'test'):
            en_path = download.cached_download(en_url.format(split))
            ja_path = download.cached_download(ja_url.format(split))
            with io.open(en_path, 'rt') as en, io.open(ja_path, 'rt') as ja:
                dataset[split] = [(x.rstrip(os.linesep), y.rstrip(os.linesep))
                                  for x, y in zip(en, ja)]

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

def creator(path):
        train_path = download.cached_download(train_url)
        dev_path = download.cached_download(dev_url)
        test_path = download.cached_download(test_url)

        dataset = {}
        for split in ("train", "dev", "test"):
            data_path = {"train": train_path, "dev": dev_path, "test": test_path}[split]
            with io.open(data_path, "rt", encoding="utf-8") as f:
                data = [json.loads(line) for line in f.readlines()]
            temp = []
            for x in data:
                answer_key = x["answerKey"] if split != "test" else ""
                options = {choice["label"]: choice["text"] for choice in x["question"]["choices"]}
                stem = x["question"]["stem"]
                temp.append({
                    "id": x["id"],
                    "answer_key": answer_key,
                    "options": options,