from datasets.utils import version """TODO(squad_es): Add a description here.""" import json import datasets # TODO(squad_es): BibTeX citation _CITATION = """\ @article{2016arXiv160605250R, author = {Casimiro Pio , Carrino and Marta R. , Costa-jussa and Jose A. R. , Fonollosa}, title = "{Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering}", journal = {arXiv e-prints}, year = 2019, eid = {arXiv:1912.05200v1}, pages = {arXiv:1912.05200v1}, archivePrefix = {arXiv}, eprint = {1912.05200v2}, } """ # TODO(squad_es_v1): _DESCRIPTION = """\ automatic translation of the Stanford Question Answering Dataset (SQuAD) v2 into Spanish """ _URL = "https://raw.githubusercontent.com/EvelynQuevedo/becas/main/" print(_URL) _URLS_V1 = { "train": _URL + "datos/train3.json", "validation": _URL + "datos/validation3.json", } print(_URLS_V1) #_URLS_V2 = { # "train": _URL + "SQuAD-es-v2.0/train-v2.0-es.json", #"dev": _URL + "SQuAD-es-v2.0/dev-v2.0-es.json", #} class SquadEsConfig(datasets.BuilderConfig): """BuilderConfig for SQUADEsV2.""" def __init__(self, **kwargs): """BuilderConfig for SQUADEsV2. Args: **kwargs: keyword arguments forwarded to super. """ super(SquadEsConfig, self).__init__(**kwargs) class SquadEs(datasets.GeneratorBasedBuilder): """TODO(squad_es): Short description of my dataset.""" # TODO(squad_es): Set up version. VERSION = datasets.Version("0.1.0") BUILDER_CONFIGS = [ SquadEsConfig( name="v1.1.0", version=datasets.Version("1.1.0", ""), description="Plain text Spanish squad version 1", ), #SquadEsConfig( # name="v2.0.0", # version=datasets.Version("2.0.0", ""), # description="Plain text Spanish squad version 2", #), ] def _info(self): # TODO(squad_es): Specifies the datasets.DatasetInfo object return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # datasets.features.FeatureConnectors features=datasets.Features( { # These are the features of your dataset like images, labels ... "id": datasets.Value("string"), "title": datasets.Value("string"), "context": datasets.Value("string"), "question": datasets.Value("string"), "answers": datasets.features.Sequence( { "text": datasets.Value("string"), "answer_start": datasets.Value("int32"), } ), } ), # If there's a common (input, target) tuple from the features, # specify them here. They'll be used if as_supervised=True in # builder.as_dataset. supervised_keys=None, # Homepage of the dataset for documentation homepage="https://github.com/EvelynQuevedo/becas", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" # TODO(squad_es): Downloads the data and defines the splits # dl_manager is a datasets.download.DownloadManager that can be used to # download and extract URLs if self.config.name == "v1.1.0": dl_dir = dl_manager.download_and_extract(_URLS_V1) print(dl_dir) # elif self.config.name == "v2.0.0": # dl_dir = dl_manager.download_and_extract(_URLS_V2) else: raise Exception("version does not match any existing one") return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={"filepath": dl_dir["train"]}, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, # These kwargs will be passed to _generate_examples gen_kwargs={"filepath": dl_dir["validation"]}, ), ] def _generate_examples(self, filepath): """Yields examples.""" # TODO(squad_es): Yields (key, example) tuples from the dataset with open(filepath, encoding="utf-8") as f: data = json.load(f) for example in data["data"]: title = example.get("title", "").strip() for paragraph in example["paragraphs"]: context = paragraph["context"].strip() for qa in paragraph["qas"]: question = qa["question"].strip() id_ = qa["id"] answer_starts = [answer["answer_start"] for answer in qa["answers"]] answers = [answer["text"].strip() for answer in qa["answers"]] yield id_, { "title": title, "context": context, "question": question, "id": id_, "answers": { "answer_start": answer_starts, "text": answers, }, }