Datasets:
wiki_lingua

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	"""WikiLingua."""


	import json

	import datasets


	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\
	@inproceedings{ladhak-etal-2020-wikilingua,
	title = "{W}iki{L}ingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization",
	author = "Ladhak, Faisal and
	Durmus, Esin and
	Cardie, Claire and
	McKeown, Kathleen",
	booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
	month = nov,
	year = "2020",
	address = "Online",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2020.findings-emnlp.360",
	doi = "10.18653/v1/2020.findings-emnlp.360",
	pages = "4034--4048",
	}
	"""

	_DESCRIPTION = """\
	WikiLingua is a large-scale multilingual dataset for the evaluation of
	cross-lingual abstractive summarization systems. The dataset includes ~770k
	article and summary pairs in 18 languages from WikiHow. The gold-standard
	article-summary alignments across languages was done by aligning the images
	that are used to describe each how-to step in an article.
	"""

	_HOMEPAGE = "https://github.com/esdurmus/Wikilingua"

	_LICENSE = "CC BY-NC-SA 3.0"

	# Download link
	_URL = "data/{language}.jsonl.gz"
	_LANGUAGES = [
	"arabic",
	"chinese",
	"czech",
	"dutch",
	"english",
	"french",
	"german",
	"hindi",
	"indonesian",
	"italian",
	"japanese",
	"korean",
	"portuguese",
	"russian",
	"spanish",
	"thai",
	"turkish",
	"vietnamese",
	]


	class WikiLingua(datasets.GeneratorBasedBuilder):
	"""WikiLingua dataset."""

	VERSION = datasets.Version("1.1.1")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name=lang,
	version=datasets.Version("1.1.1"),
	description=f"A subset of article-summary in {lang.capitalize()}",
	)
	for lang in _LANGUAGES
	]

	DEFAULT_CONFIG_NAME = "english"

	def _info(self):
	if self.config.name == "english":
	features = datasets.Features(
	{
	"url": datasets.Value("string"),
	"article": datasets.Sequence(
	{
	"section_name": datasets.Value("string"),
	"document": datasets.Value("string"),
	"summary": datasets.Value("string"),
	}
	),
	}
	)
	else:
	features = datasets.Features(
	{
	"url": datasets.Value("string"),
	"article": datasets.Sequence(
	{
	"section_name": datasets.Value("string"),
	"document": datasets.Value("string"),
	"summary": datasets.Value("string"),
	"english_url": datasets.Value("string"),
	"english_section_name": datasets.Value("string"),
	}
	),
	}
	)

	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	# Homepage of the dataset for documentation
	homepage=_HOMEPAGE,
	# License for the dataset if available
	license=_LICENSE,
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	filepath = dl_manager.download_and_extract(_URL.format(language=self.config.name))
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": filepath,
	},
	),
	]

	def _process_article(self, article):
	"""Parse the article and convert into list of dict"""
	processed_article = []
	for key, value in article.items():
	row = {"section_name": key, "document": value["document"], "summary": value["summary"]}

	if self.config.name != "english":
	row["english_url"] = value["english_url"]
	row["english_section_name"] = value["english_section_name"]
	processed_article.append(row)

	return processed_article

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, "rb") as f:
	for id_, line in enumerate(f):
	row = json.loads(line)
	yield id_, {"url": row["url"], "article": self._process_article(row["article"])}