Datasets:

Helsinki-NLP
/

news_commentary

	# coding=utf-8
	# Copyright 2020 HuggingFace Datasets Authors.
	#
	# 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.

	# Lint as: python3
	import os

	import datasets


	_DESCRIPTION = """\
	A parallel corpus of News Commentaries provided by WMT for training SMT. The source is taken from CASMACAT: http://www.casmacat.eu/corpus/news-commentary.html

	12 languages, 63 bitexts
	total number of files: 61,928
	total number of tokens: 49.66M
	total number of sentence fragments: 1.93M
	"""
	_HOMEPAGE_URL = "https://opus.nlpl.eu/News-Commentary/corpus/version/News-Commentary"
	_CITATION = """\
	@inproceedings{tiedemann-2012-parallel,
	title = "Parallel Data, Tools and Interfaces in {OPUS}",
	author = {Tiedemann, J{\\"o}rg},
	editor = "Calzolari, Nicoletta and
	Choukri, Khalid and
	Declerck, Thierry and
	Do{\\u{g}}an, Mehmet U{\\u{g}}ur and
	Maegaard, Bente and
	Mariani, Joseph and
	Moreno, Asuncion and
	Odijk, Jan and
	Piperidis, Stelios",
	booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
	month = may,
	year = "2012",
	address = "Istanbul, Turkey",
	publisher = "European Language Resources Association (ELRA)",
	url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/463_Paper.pdf",
	pages = "2214--2218",
	}
	"""

	_VERSION = "11.0.0"
	_BASE_NAME = "News-Commentary.{}.{}"
	_BASE_URL = "https://object.pouta.csc.fi/OPUS-News-Commentary/v11/moses/{}-{}.txt.zip"

	_LANGUAGE_PAIRS = [
	("ar", "cs"),
	("ar", "de"),
	("cs", "de"),
	("ar", "en"),
	("cs", "en"),
	("de", "en"),
	("ar", "es"),
	("cs", "es"),
	("de", "es"),
	("en", "es"),
	("ar", "fr"),
	("cs", "fr"),
	("de", "fr"),
	("en", "fr"),
	("es", "fr"),
	("ar", "it"),
	("cs", "it"),
	("de", "it"),
	("en", "it"),
	("es", "it"),
	("fr", "it"),
	("ar", "ja"),
	("cs", "ja"),
	("de", "ja"),
	("en", "ja"),
	("es", "ja"),
	("fr", "ja"),
	("ar", "nl"),
	("cs", "nl"),
	("de", "nl"),
	("en", "nl"),
	("es", "nl"),
	("fr", "nl"),
	("it", "nl"),
	("ar", "pt"),
	("cs", "pt"),
	("de", "pt"),
	("en", "pt"),
	("es", "pt"),
	("fr", "pt"),
	("it", "pt"),
	("nl", "pt"),
	("ar", "ru"),
	("cs", "ru"),
	("de", "ru"),
	("en", "ru"),
	("es", "ru"),
	("fr", "ru"),
	("it", "ru"),
	("ja", "ru"),
	("nl", "ru"),
	("pt", "ru"),
	("ar", "zh"),
	("cs", "zh"),
	("de", "zh"),
	("en", "zh"),
	("es", "zh"),
	("fr", "zh"),
	("it", "zh"),
	("ja", "zh"),
	("nl", "zh"),
	("pt", "zh"),
	("ru", "zh"),
	]


	class NewsCommentaryConfig(datasets.BuilderConfig):
	def __init__(self, args, lang1=None, lang2=None, *kwargs):
	super().__init__(
	*args,
	name=f"{lang1}-{lang2}",
	**kwargs,
	)
	self.lang1 = lang1
	self.lang2 = lang2


	class NewsCommentary(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	NewsCommentaryConfig(
	lang1=lang1,
	lang2=lang2,
	description=f"Translating {lang1} to {lang2} or vice versa",
	version=datasets.Version(_VERSION),
	)
	for lang1, lang2 in _LANGUAGE_PAIRS
	]
	BUILDER_CONFIG_CLASS = NewsCommentaryConfig

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
	},
	),
	supervised_keys=None,
	homepage=_HOMEPAGE_URL,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	def _base_url(lang1, lang2):
	return _BASE_URL.format(lang1, lang2)

	download_url = _base_url(self.config.lang1, self.config.lang2)
	path = dl_manager.download_and_extract(download_url)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"datapath": path},
	)
	]

	def _generate_examples(self, datapath):
	l1, l2 = self.config.lang1, self.config.lang2
	folder = l1 + "-" + l2
	l1_file = _BASE_NAME.format(folder, l1)
	l2_file = _BASE_NAME.format(folder, l2)
	l1_path = os.path.join(datapath, l1_file)
	l2_path = os.path.join(datapath, l2_file)
	with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2:
	for sentence_counter, (x, y) in enumerate(zip(f1, f2)):
	x = x.strip()
	y = y.strip()
	result = (
	sentence_counter,
	{
	"id": str(sentence_counter),
	"translation": {l1: x, l2: y},
	},
	)
	yield result