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| import os |
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| import datasets |
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| _DESCRIPTION = """\ |
| This is a collection of Quran translations compiled by the Tanzil project |
| The translations provided at this page are for non-commercial purposes only. If used otherwise, you need to obtain necessary permission from the translator or the publisher. |
| |
| If you are using more than three of the following translations in a website or application, we require you to put a link back to this page to make sure that subsequent users have access to the latest updates. |
| |
| 42 languages, 878 bitexts |
| total number of files: 105 |
| total number of tokens: 22.33M |
| total number of sentence fragments: 1.01M |
| """ |
| _HOMEPAGE_URL = "http://opus.nlpl.eu/Tanzil.php" |
| _CITATION = """\ |
| J. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012) |
| """ |
|
|
| _VERSION = "1.0.0" |
| _BASE_NAME = "Tanzil.{}.{}" |
| _BASE_URL = "https://object.pouta.csc.fi/OPUS-Tanzil/v1/moses/{}-{}.txt.zip" |
|
|
| |
| _LANGUAGE_PAIRS = [ |
| ("bg", "en"), |
| ("bn", "hi"), |
| ("fa", "sv"), |
| ("ru", "zh"), |
| ("en", "tr"), |
| ] |
|
|
|
|
| class TanzilConfig(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 Tanzil(datasets.GeneratorBasedBuilder): |
| BUILDER_CONFIGS = [ |
| TanzilConfig( |
| 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 = TanzilConfig |
|
|
| 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 |
|
|