# 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 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" # Please note that only few pairs are shown here. You can use config to generate data for all language pairs _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): # see https://github.com/huggingface/datasets/issues/1844 # sentence ids have the following format: en/2017/7006210/7050201.xml.gz # lang/year/imdb_id/opensubtitles_id.xml.gz parts = sentence_id[: -len(".xml.gz")].split("/") parts.pop(0) # remove lang, we do not need it # returns year, imdb_id, opensubtitles_id 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