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""" |
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RF is a tiny parallel corpus of the Declarations of the Swedish Government and its translations. |
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5 languages, 10 bitexts |
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total number of files: 11 |
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total number of tokens: 19.74k |
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total number of sentence fragments: 0.86k |
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""" |
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import os |
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import datasets |
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_CITATION = """\ |
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@InProceedings{TIEDEMANN12.463, |
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author = {J{\"o}rg Tiedemann}, |
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title = {Parallel Data, Tools and Interfaces in OPUS}, |
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booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, |
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year = {2012}, |
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month = {may}, |
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date = {23-25}, |
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address = {Istanbul, Turkey}, |
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editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis}, |
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publisher = {European Language Resources Association (ELRA)}, |
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isbn = {978-2-9517408-7-7}, |
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language = {english} |
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} |
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""" |
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_DESCRIPTION = """\ |
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RF is a tiny parallel corpus of the Declarations of the Swedish Government and its translations. |
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""" |
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_HOMEPAGE = "http://opus.nlpl.eu/RF.php" |
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_VERSION = "1.0.0" |
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_BASE_NAME = "RF.{}.{}" |
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_BASE_URL = "https://object.pouta.csc.fi/OPUS-RF/v1/moses/{}-{}.txt.zip" |
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_LANGUAGE_PAIRS = [ |
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("de", "en"), |
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("de", "es"), |
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("de", "fr"), |
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("de", "sv"), |
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("en", "es"), |
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("en", "fr"), |
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("en", "sv"), |
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("es", "fr"), |
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("es", "sv"), |
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("fr", "sv"), |
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] |
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class OpusRFTranslationsConfig(datasets.BuilderConfig): |
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def __init__(self, *args, lang1=None, lang2=None, **kwargs): |
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super().__init__( |
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*args, |
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name=f"{lang1}-{lang2}", |
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**kwargs, |
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) |
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self.lang1 = lang1 |
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self.lang2 = lang2 |
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class OpusRF(datasets.GeneratorBasedBuilder): |
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"""RF is a tiny parallel corpus of the Declarations of the Swedish Government and its translations.""" |
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BUILDER_CONFIGS = [ |
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OpusRFTranslationsConfig( |
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lang1=lang1, |
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lang2=lang2, |
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description=f"Translating {lang1} to {lang2} or vice versa", |
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version=datasets.Version(_VERSION), |
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) |
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for lang1, lang2 in _LANGUAGE_PAIRS |
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] |
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BUILDER_CONFIG_CLASS = OpusRFTranslationsConfig |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)), |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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download_url = _BASE_URL.format(self.config.lang1, self.config.lang2) |
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path = dl_manager.download_and_extract(download_url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"datapath": path}, |
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) |
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] |
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def _generate_examples(self, datapath): |
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"""Yields examples.""" |
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l1, l2 = self.config.lang1, self.config.lang2 |
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folder = l1 + "-" + l2 |
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l1_file = _BASE_NAME.format(folder, l1) |
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l2_file = _BASE_NAME.format(folder, l2) |
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l1_path = os.path.join(datapath, l1_file) |
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l2_path = os.path.join(datapath, l2_file) |
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with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2: |
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for sentence_counter, (x, y) in enumerate(zip(f1, f2)): |
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x = x.strip() |
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y = y.strip() |
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result = ( |
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sentence_counter, |
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{ |
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"id": str(sentence_counter), |
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"translation": {l1: x, l2: y}, |
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}, |
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) |
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yield result |
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