# 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.
import os
import xml.etree.ElementTree as ET
import datasets
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@inproceedings{koehn-2005-europarl,
title = "{E}uroparl: A Parallel Corpus for Statistical Machine Translation",
author = "Koehn, Philipp",
booktitle = "Proceedings of Machine Translation Summit X: Papers",
month = sep # " 13-15",
year = "2005",
address = "Phuket, Thailand",
url = "https://aclanthology.org/2005.mtsummit-papers.11",
pages = "79--86",
}
@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",
}"""
# You can copy an official description
_DESCRIPTION = """\
A parallel corpus extracted from the European Parliament web site by Philipp Koehn (University of Edinburgh). The main intended use is to aid statistical machine translation research.
"""
# Add a link to an official homepage for the dataset here
_HOMEPAGE = "https://opus.nlpl.eu/Europarl/corpus/version/Europarl"
# Add the licence for the dataset here if you can find it
_LICENSE = """\
The data set comes with the same license
as the original sources.
Please, check the information about the source
that is given on
https://opus.nlpl.eu/Europarl/corpus/version/Europarl
"""
# The HuggingFace dataset library don't host the datasets but only point to the original files
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
LANGUAGES = [
"bg",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fi",
"fr",
"hu",
"it",
"lt",
"lv",
"nl",
"pl",
"pt",
"ro",
"sk",
"sl",
"sv",
]
ALL_PAIRS = []
for i in range(len(LANGUAGES)):
for j in range(i + 1, len(LANGUAGES)):
ALL_PAIRS.append((LANGUAGES[i], LANGUAGES[j]))
_VERSION = "8.0.0"
_BASE_URL_DATASET = "https://object.pouta.csc.fi/OPUS-Europarl/v8/raw/{}.zip"
_BASE_URL_RELATIONS = "https://object.pouta.csc.fi/OPUS-Europarl/v8/xml/{}-{}.xml.gz"
class EuroparlBilingualConfig(datasets.BuilderConfig):
"""Slightly custom config to require source and target languages."""
def __init__(self, *args, lang1=None, lang2=None, **kwargs):
super().__init__(
*args,
name=f"{lang1}-{lang2}",
**kwargs,
)
self.lang1 = lang1
self.lang2 = lang2
def _lang_pair(self):
return (self.lang1, self.lang2)
def _is_valid(self):
return self._lang_pair() in ALL_PAIRS
class EuroparlBilingual(datasets.GeneratorBasedBuilder):
"""Europarl contains aligned sentences in multiple west language pairs."""
VERSION = datasets.Version(_VERSION)
BUILDER_CONFIG_CLASS = EuroparlBilingualConfig
BUILDER_CONFIGS = [
EuroparlBilingualConfig(lang1=lang1, lang2=lang2, version=datasets.Version(_VERSION))
for lang1, lang2 in ALL_PAIRS[:5]
]
def _info(self):
"""This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset."""
features = datasets.Features(
{
"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
if not self.config._is_valid():
raise ValueError(f"{self.config._lang_pair()} is not a supported language pair. Choose among: {ALL_PAIRS}")
# download data files
path_datafile_1 = dl_manager.download_and_extract(_BASE_URL_DATASET.format(self.config.lang1))
path_datafile_2 = dl_manager.download_and_extract(_BASE_URL_DATASET.format(self.config.lang2))
# download relations file
path_relation_file = dl_manager.download_and_extract(
_BASE_URL_RELATIONS.format(self.config.lang1, self.config.lang2)
)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"path_datafiles": (path_datafile_1, path_datafile_2),
"path_relation_file": path_relation_file,
},
)
]
@staticmethod
def _parse_xml_datafile(filepath):
"""
Parse and return a Dict[sentence_id, text] representing data with the following structure:
"""
document = ET.parse(filepath).getroot()
return {tag.attrib["id"]: tag.text for tag in document.iter("s")}
def _generate_examples(self, path_datafiles, path_relation_file):
"""Yields examples.
In parenthesis the useful attributes
Lang files XML
- document
- CHAPTER ('ID')
- P ('id')
- s ('id')
Relation file XML
- cesAlign
- linkGrp ('fromDoc', 'toDoc')
- link ('xtargets': '1;1')
"""
# my counter
_id = 0
relations_root = ET.parse(path_relation_file).getroot()
for linkGroup in relations_root:
# retrieve files and remove .gz extension because 'datasets' library already decompress them
from_doc_dict = EuroparlBilingual._parse_xml_datafile(
os.path.splitext(os.path.join(path_datafiles[0], "Europarl", "raw", linkGroup.attrib["fromDoc"]))[0]
)
to_doc_dict = EuroparlBilingual._parse_xml_datafile(
os.path.splitext(os.path.join(path_datafiles[1], "Europarl", "raw", linkGroup.attrib["toDoc"]))[0]
)
for link in linkGroup:
from_sentence_ids, to_sentence_ids = link.attrib["xtargets"].split(";")
from_sentence_ids = [i for i in from_sentence_ids.split(" ") if i]
to_sentence_ids = [i for i in to_sentence_ids.split(" ") if i]
if not len(from_sentence_ids) or not len(to_sentence_ids):
continue
# in rare cases, there is not entry for some key pairs
sentence_lang1 = " ".join(from_doc_dict[i] for i in from_sentence_ids if i in from_doc_dict)
sentence_lang2 = " ".join(to_doc_dict[i] for i in to_sentence_ids if i in to_doc_dict)
yield _id, {"translation": {self.config.lang1: sentence_lang1, self.config.lang2: sentence_lang2}}
_id += 1