import json import datasets logger = datasets.logging.get_logger(__name__) _URL = "https://huggingface.co/datasets/sagnikrayc/snli-bt/resolve/main" _URLS = { "train": f"{_URL}/train.jsonl", "validation": f"{_URL}/validation.jsonl", "test": f"{_URL}/test.jsonl", } class SnliBTConfig(datasets.BuilderConfig): def __init__(self, **kwargs): super(SnliBTConfig, self).__init__(**kwargs) class SnliBT(datasets.GeneratorBasedBuilder): """SQUAD: The Stanford Question Answering Dataset. Version 1.1.""" BUILDER_CONFIGS = [ SnliBTConfig( name="plain_text", version=datasets.Version("1.0.0", ""), description="Plain text", ), ] def _info(self): return datasets.DatasetInfo( description="NA", features=datasets.Features( { "idx": datasets.Value("string"), "premise": datasets.Value("string"), "hypothesis": datasets.Value("string"), "label": datasets.Value("string"), "_type": datasets.Value("string"), } ), # No default supervised_keys (as we have to pass both question # and context as input). supervised_keys=None ) 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["validation"]} ), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" logger.info("generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as rf: for idx, line in enumerate(rf): if line: _line = json.loads(line) yield idx, { "premise": _line["premise"], "hypothesis": _line["hypothesis"], "idx": _line["idx"], "_type": _line["_type"], "label": _line["label"] }