Datasets:
europa_ecdc_tm

	# 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.
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	#
	# 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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	"""European Center for Disease Prevention and Control Translation Memory dataset"""


	import os
	from xml.etree import ElementTree

	import datasets


	logger = datasets.logging.get_logger(__name__)


	_CITATION = """\
	@Article{Steinberger2014,
	author={Steinberger, Ralf
	and Ebrahim, Mohamed
	and Poulis, Alexandros
	and Carrasco-Benitez, Manuel
	and Schl{\"u}ter, Patrick
	and Przybyszewski, Marek
	and Gilbro, Signe},
	title={An overview of the European Union's highly multilingual parallel corpora},
	journal={Language Resources and Evaluation},
	year={2014},
	month={Dec},
	day={01},
	volume={48},
	number={4},
	pages={679-707},
	issn={1574-0218},
	doi={10.1007/s10579-014-9277-0},
	url={https://doi.org/10.1007/s10579-014-9277-0}
	}
	"""

	_DESCRIPTION = """\
	In October 2012, the European Union (EU) agency 'European Centre for Disease Prevention and Control' (ECDC) released \
	a translation memory (TM), i.e. a collection of sentences and their professionally produced translations, in \
	twenty-five languages. This resource bears the name EAC Translation Memory, short EAC-TM.
	ECDC-TM covers 25 languages: the 23 official languages of the EU plus Norwegian (Norsk) and Icelandic. ECDC-TM was \
	created by translating from English into the following 24 languages: Bulgarian, Czech, Danish, Dutch, English, \
	Estonian, Gaelige (Irish), German, Greek, Finnish, French, Hungarian, Icelandic, Italian, Latvian, Lithuanian, \
	Maltese, Norwegian (NOrsk), Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish and Swedish.
	All documents and sentences were thus originally written in English. They were then translated into the other \
	languages by professional translators from the Translation Centre CdT in Luxembourg."""

	_HOMEPAGE = "https://ec.europa.eu/jrc/en/language-technologies/ecdc-translation-memory"

	_LICENSE = "\
	Creative Commons Attribution 4.0 International(CC BY 4.0) licence \
	Copyright © EU/ECDC, 1995-2020"

	_VERSION = "1.0.0"

	_DATA_URL = "http://optima.jrc.it/Resources/ECDC-TM/ECDC-TM.zip"

	_AVAILABLE_LANGUAGES = (
	"bg",
	"cs",
	"da",
	"de",
	"el",
	"es",
	"en",
	"et",
	"fi",
	"fr",
	"ga",
	"hu",
	"is",
	"it",
	"lt",
	"lv",
	"mt",
	"nl",
	"no",
	"pl",
	"pt",
	"ro",
	"sk",
	"sl",
	"sv",
	)


	def _find_sentence(translation, language):
	"""Util that returns the sentence in the given language from translation, or None if it is not found

	Args:
	translation: `xml.etree.ElementTree.Element`, xml tree element extracted from the translation memory files.
	language: `str`, language of interest e.g. 'en'

	Returns: `str` or `None`, can be `None` if the language of interest is not found in the translation
	"""
	# Retrieve the first <tuv> children of translation having xml:lang tag equal to language
	namespaces = {"xml": "http://www.w3.org/XML/1998/namespace"}
	seg_tag = translation.find(path=f".//tuv[@xml:lang='{language.upper()}']/seg", namespaces=namespaces)
	if seg_tag is not None:
	return seg_tag.text
	return None


	class EuropaEcdcTMConfig(datasets.BuilderConfig):
	"""BuilderConfig for EuropaEcdcTM"""

	def __init__(self, args, language_pair=(None, None), *kwargs):
	"""BuilderConfig for EuropaEcdcTM
	Args:
	language_pair: pair of languages that will be used for translation. Should
	contain 2-letter coded strings. First will be used at source and second
	as target in supervised mode. For example: ("se", "en").
	**kwargs: keyword arguments forwarded to super.
	"""
	name = f"{language_pair[0]}2{language_pair[1]}"
	description = f"Translation dataset from {language_pair[0]} to {language_pair[1]}"
	super(EuropaEcdcTMConfig, self).__init__(
	*args,
	name=name,
	description=description,
	**kwargs,
	)
	source, target = language_pair
	assert source != target, "Source and target languages must be different}"
	assert (source in _AVAILABLE_LANGUAGES) and (
	target in _AVAILABLE_LANGUAGES
	), f"Either source language {source} or target language {target} is not supported. Both must be one of : {_AVAILABLE_LANGUAGES}"
	self.language_pair = language_pair


	# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
	class EuropaEcdcTM(datasets.GeneratorBasedBuilder):
	"""European Center for Disease Control and Prevention Translation Memory"""

	BUILDER_CONFIGS = [
	EuropaEcdcTMConfig(language_pair=("en", target), version=_VERSION) for target in ["bg", "fr", "sl"]
	]
	BUILDER_CONFIG_CLASS = EuropaEcdcTMConfig

	def _info(self):
	source, target = self.config.language_pair
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"translation": datasets.features.Translation(languages=self.config.language_pair),
	}
	),
	supervised_keys=(source, target),
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	dl_dir = dl_manager.download_and_extract(_DATA_URL)
	filepath = os.path.join(dl_dir, "ECDC-TM", "ECDC.tmx")
	source, target = self.config.language_pair
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": filepath,
	"source_language": source,
	"target_language": target,
	},
	),
	]

	def _generate_examples(
	self,
	filepath,
	source_language,
	target_language,
	):
	logger.info(f"⏳ Generating examples from = {filepath}")
	xml_element_tree = ElementTree.parse(filepath)
	xml_body_tag = xml_element_tree.getroot().find("body")
	assert xml_body_tag is not None, f"Invalid data: <body></body> tag not found in {filepath}"

	# Translations are stored in <tu>...</tu> tags
	translation_units = xml_body_tag.iter("tu")

	# _ids may not be contiguous
	for _id, translation in enumerate(translation_units):
	source_sentence = _find_sentence(translation=translation, language=source_language)
	target_sentence = _find_sentence(translation=translation, language=target_language)
	if source_sentence is None or target_sentence is None:
	continue

	yield _id, {
	"translation": {source_language: source_sentence, target_language: target_sentence},
	}