Datasets:
squad_es

	"""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/ccasimiro88/TranslateAlignRetrieve/master/"
	_URLS_V1 = {
	"train": _URL + "SQuAD-es-v1.1/train-v1.1-es.json",
	"dev": _URL + "SQuAD-es-v1.1/dev-v1.1-es.json",
	}
	_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/ccasimiro88/TranslateAlignRetrieve",
	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)
	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["dev"]},
	),
	]

	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,
	},
	}