Datasets:
open_subtitles

	# 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