import datasets _CITATION = """\ """ _DESCRIPTION = """\ This is a test dataset. """ _URLS = { "train": "https://huggingface.co/datasets/changxin/test_pq/blob/main/another_text.txt", # absolute "dev": "some_text.txt", # relative "TEST1":"chuishui.txt" } class Test(datasets.GeneratorBasedBuilder): """SQUAD: The Stanford Question Answering Dataset. Version 1.1.""" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "text": datasets.Value("string"), } ), supervised_keys=None, homepage="https://huggingface.co/datasets/changxin/test_pq", citation=_CITATION, ) def _split_generators(self, dl_manager): downloaded_files = dl_manager.download_and_extract(_URLS) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["TEST1"]}), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" for _id, line in enumerate(open(filepath, encoding="utf-8")): yield _id, {"text": line.rstrip()}