Datasets:
tatoeba

	# 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
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	# distributed under the License is distributed on an "AS IS" BASIS,
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	# Lint as: python3
	import os

	import datasets


	_DESCRIPTION = """\
	This is a collection of translated sentences from Tatoeba
	359 languages, 3,403 bitexts
	total number of files: 750
	total number of tokens: 65.54M
	total number of sentence fragments: 8.96M
	"""
	_HOMEPAGE_URL = "http://opus.nlpl.eu/Tatoeba.php"
	_CITATION = """\
	@InProceedings{TIEDEMANN12.463,
	author = {J{\"o}rg}rg Tiedemann},
	title = {Parallel Data, Tools and Interfaces in OPUS},
	booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
	year = {2012},
	month = {may},
	date = {23-25},
	address = {Istanbul, Turkey},
	editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
	publisher = {European Language Resources Association (ELRA)},
	isbn = {978-2-9517408-7-7},
	language = {english}
	}
	"""

	_VERSION = "2021.7.22"
	_DATE = "v" + "-".join(s.zfill(2) for s in _VERSION.split("."))
	_BASE_NAME = "Tatoeba.{}.{}"
	_BASE_URL = "https://object.pouta.csc.fi/OPUS-Tatoeba/{}/moses/{}-{}.txt.zip"

	# Please note that only few pairs are shown here. You can use config to generate data for all language pairs
	_LANGUAGE_PAIRS = [
	("en", "mr"),
	("eo", "nl"),
	("es", "pt"),
	("fr", "ru"),
	("es", "gl"),
	]


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


	class Tatoeba(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	TatoebaConfig(
	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 = TatoebaConfig

	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, date):
	return _BASE_URL.format(date, lang1, lang2)

	download_url = _base_url(self.config.lang1, self.config.lang2, self.config.date)
	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