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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 = """\
This is a multilingual parallel corpus created from translations of the Bible compiled by Christos Christodoulopoulos and Mark Steedman.
102 languages, 5,148 bitexts
total number of files: 107
total number of tokens: 56.43M
total number of sentence fragments: 2.84M
"""
_HOMEPAGE_URL = "http://opus.nlpl.eu/bible-uedin.php"
_CITATION = """\
OPUS and A massively parallel corpus: the Bible in 100 languages, Christos Christodoulopoulos and Mark Steedman, *Language Resources and Evaluation*, 49 (2)
"""
_VERSION = "1.0.0"
_BASE_NAME = "bible-uedin.{}.{}"
_BASE_URL = "https://object.pouta.csc.fi/OPUS-bible-uedin/v1/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 = [
("de", "en"),
("en", "fr"),
("en", "es"),
("en", "fi"),
("en", "no"),
("en", "hi"),
]
class BibleParaConfig(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 BiblePara(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
BibleParaConfig(
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 = BibleParaConfig
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},
},
)
sentence_counter += 1
yield result
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