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| | import os |
| |
|
| | import datasets |
| |
|
| |
|
| | _DESCRIPTION = """\ |
| | This is a new collection of translated movie subtitles from http://www.opensubtitles.org/. |
| | |
| | IMPORTANT: If you use the OpenSubtitle corpus: Please, add a link to http://www.opensubtitles.org/ to your website and to your reports and publications produced with the data! |
| | |
| | This is a slightly cleaner version of the subtitle collection using improved sentence alignment and better language checking. |
| | |
| | 62 languages, 1,782 bitexts |
| | total number of files: 3,735,070 |
| | total number of tokens: 22.10G |
| | total number of sentence fragments: 3.35G |
| | """ |
| | _HOMEPAGE_URL = "http://opus.nlpl.eu/OpenSubtitles.php" |
| | _CITATION = """\ |
| | P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016) |
| | """ |
| |
|
| | _VERSION = "2018.0.0" |
| | _BASE_NAME = "OpenSubtitles.{}.{}" |
| | _BASE_URL = "https://object.pouta.csc.fi/OPUS-OpenSubtitles/v2018/moses/{}-{}.txt.zip" |
| |
|
| | |
| | _LANGUAGE_PAIRS = [ |
| | ("bs", "eo"), |
| | ("fr", "hy"), |
| | ("da", "ru"), |
| | ("en", "hi"), |
| | ("bn", "is"), |
| | ] |
| |
|
| |
|
| | class OpenSubtitlesConfig(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 OpenSubtitles(datasets.GeneratorBasedBuilder): |
| | BUILDER_CONFIGS = [ |
| | OpenSubtitlesConfig( |
| | 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 = OpenSubtitlesConfig |
| |
|
| | def _info(self): |
| | return datasets.DatasetInfo( |
| | description=_DESCRIPTION, |
| | features=datasets.Features( |
| | { |
| | "id": datasets.Value("string"), |
| | "meta": { |
| | "year": datasets.Value("uint32"), |
| | "imdbId": datasets.Value("uint32"), |
| | "subtitleId": { |
| | self.config.lang1: datasets.Value("uint32"), |
| | self.config.lang2: datasets.Value("uint32"), |
| | }, |
| | "sentenceIds": { |
| | self.config.lang1: datasets.Sequence(datasets.Value("uint32")), |
| | self.config.lang2: datasets.Sequence(datasets.Value("uint32")), |
| | }, |
| | }, |
| | "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}, |
| | ) |
| | ] |
| |
|
| | @classmethod |
| | def _extract_info(cls, sentence_id): |
| | |
| | |
| | |
| | parts = sentence_id[: -len(".xml.gz")].split("/") |
| | parts.pop(0) |
| |
|
| | |
| | return tuple(map(int, parts)) |
| |
|
| | 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) |
| | ids_file = _BASE_NAME.format(folder, "ids") |
| | l1_path = os.path.join(datapath, l1_file) |
| | l2_path = os.path.join(datapath, l2_file) |
| | ids_path = os.path.join(datapath, ids_file) |
| | with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2, open( |
| | ids_path, encoding="utf-8" |
| | ) as f3: |
| | for sentence_counter, (x, y, _id) in enumerate(zip(f1, f2, f3)): |
| | x = x.strip() |
| | y = y.strip() |
| | l1_id, l2_id, l1_sid, l2_sid = _id.split("\t") |
| | year, imdb_id, l1_subtitle_id = self._extract_info(l1_id) |
| | _, _, l2_subtitle_id = self._extract_info(l2_id) |
| | l1_sentence_ids = list(map(int, l1_sid.split(" "))) |
| | l2_sentence_ids = list(map(int, l2_sid.split(" "))) |
| |
|
| | result = ( |
| | sentence_counter, |
| | { |
| | "id": str(sentence_counter), |
| | "meta": { |
| | "year": year, |
| | "imdbId": imdb_id, |
| | "subtitleId": {l1: l1_subtitle_id, l2: l2_subtitle_id}, |
| | "sentenceIds": {l1: l1_sentence_ids, l2: l2_sentence_ids}, |
| | }, |
| | "translation": {l1: x, l2: y}, |
| | }, |
| | ) |
| | sentence_counter += 1 |
| | yield result |
| |
|