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# 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 = """\
Parallel corpora from Web Crawls collected in the ParaCrawl project.
42 languages, 43 bitexts
total number of files: 59,996
total number of tokens: 56.11G
total number of sentence fragments: 3.13G
"""
_HOMEPAGE = "http://opus.nlpl.eu/ParaCrawl.php"
_CITATION = r"""\
@inproceedings{banon-etal-2020-paracrawl,
title = "{P}ara{C}rawl: Web-Scale Acquisition of Parallel Corpora",
author = "Ba{\~n}{\'o}n, Marta and
Chen, Pinzhen and
Haddow, Barry and
Heafield, Kenneth and
Hoang, Hieu and
Espl{\`a}-Gomis, Miquel and
Forcada, Mikel L. and
Kamran, Amir and
Kirefu, Faheem and
Koehn, Philipp and
Ortiz Rojas, Sergio and
Pla Sempere, Leopoldo and
Ram{\'\i}rez-S{\'a}nchez, Gema and
Sarr{\'\i}as, Elsa and
Strelec, Marek and
Thompson, Brian and
Waites, William and
Wiggins, Dion and
Zaragoza, Jaume",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.417",
doi = "10.18653/v1/2020.acl-main.417",
pages = "4555--4567",
}
@InProceedings{TIEDEMANN12.463,
author = {Jörg 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 Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
publisher = {European Language Resources Association (ELRA)},
isbn = {978-2-9517408-7-7},
language = {english}
}
"""
_VERSION = "9.0.0"
_BASE_NAME = "ParaCrawl.{}.{}"
_BASE_URL = "https://object.pouta.csc.fi/OPUS-ParaCrawl/v9/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 = [
("el", "en"),
("en", "km"),
("en", "so"),
("de", "pl"),
("fr", "nl"),
("en", "sw"),
("en", "tl"),
("es", "gl"),
]
class ParaCrawlConfig(datasets.BuilderConfig):
def __init__(self, *args, lang1=None, lang2=None, **kwargs):
super().__init__(
*args,
name=f"{lang1}-{lang2}",
**kwargs,
)
assert lang1 != lang2, "'language 1' & 'language 2' should be different from each other"
self.lang1 = lang1
self.lang2 = lang2
class OpusParaCrawl(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
ParaCrawlConfig(
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 = ParaCrawlConfig
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,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
download_url = _BASE_URL.format(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):
lang1, lang2 = self.config.lang1, self.config.lang2
folder = lang1 + "-" + lang2
lang1_filename = _BASE_NAME.format(folder, lang1)
lang2_filename = _BASE_NAME.format(folder, lang2)
lang1_path = os.path.join(datapath, lang1_filename)
lang2_path = os.path.join(datapath, lang2_filename)
with open(lang1_path, encoding="utf-8") as f1, open(lang2_path, encoding="utf-8") as f2:
for id_, (lang1_sentence, lang2_sentence) in enumerate(zip(f1, f2)):
lang1_sentence = lang1_sentence.strip()
lang2_sentence = lang2_sentence.strip()
yield id_, {
"id": str(id_),
"translation": {lang1: lang1_sentence, lang2: lang2_sentence},
}
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