Datasets:
xquad

	"""TODO(xquad): Add a description here."""


	import json

	import datasets
	from datasets.tasks import QuestionAnsweringExtractive


	_CITATION = """\
	@article{Artetxe:etal:2019,
	author = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
	title = {On the cross-lingual transferability of monolingual representations},
	journal = {CoRR},
	volume = {abs/1910.11856},
	year = {2019},
	archivePrefix = {arXiv},
	eprint = {1910.11856}
	}
	"""

	_DESCRIPTION = """\
	XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering
	performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set
	of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German,
	Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, Hindi and Romanian. Consequently, the dataset is entirely parallel
	across 12 languages.
	"""

	_URL = "https://github.com/deepmind/xquad/raw/master/"
	_LANG = ["ar", "de", "zh", "vi", "en", "es", "hi", "el", "th", "tr", "ru", "ro"]


	class XquadConfig(datasets.BuilderConfig):

	"""BuilderConfig for Xquad"""

	def __init__(self, lang, **kwargs):
	"""

	Args:
	lang: string, language for the input text
	**kwargs: keyword arguments forwarded to super.
	"""
	super(XquadConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
	self.lang = lang


	class Xquad(datasets.GeneratorBasedBuilder):
	"""TODO(xquad): Short description of my dataset."""

	# TODO(xquad): Set up version.
	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIGS = [XquadConfig(name=f"xquad.{lang}", description=_DESCRIPTION, lang=lang) for lang in _LANG]

	def _info(self):
	# TODO(xquad): 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(
	{
	"id": datasets.Value("string"),
	"context": datasets.Value("string"),
	"question": datasets.Value("string"),
	"answers": datasets.features.Sequence(
	{
	"text": datasets.Value("string"),
	"answer_start": datasets.Value("int32"),
	}
	),
	# These are the features of your dataset like images, labels ...
	}
	),
	# 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/deepmind/xquad",
	citation=_CITATION,
	task_templates=[
	QuestionAnsweringExtractive(
	question_column="question", context_column="context", answers_column="answers"
	)
	],
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# TODO(xquad): Downloads the data and defines the splits
	# dl_manager is a datasets.download.DownloadManager that can be used to
	# download and extract URLs
	urls_to_download = {lang: _URL + f"xquad.{lang}.json" for lang in _LANG}
	downloaded_files = dl_manager.download_and_extract(urls_to_download)

	return [
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": downloaded_files[self.config.lang]},
	),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	# TODO(xquad): Yields (key, example) tuples from the dataset
	with open(filepath, encoding="utf-8") as f:
	xquad = json.load(f)
	id_ = 0
	for article in xquad["data"]:
	for paragraph in article["paragraphs"]:
	context = paragraph["context"].strip()
	for qa in paragraph["qas"]:
	question = qa["question"].strip()
	answer_starts = [answer["answer_start"] for answer in qa["answers"]]
	answers = [answer["text"].strip() for answer in qa["answers"]]

	# Features currently used are "context", "question", and "answers".
	# Others are extracted here for the ease of future expansions.
	yield id_, {
	"context": context,
	"question": question,
	"id": qa["id"],
	"answers": {
	"answer_start": answer_starts,
	"text": answers,
	},
	}
	id_ += 1