# 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