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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 = """\
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
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