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opus_raw / opus_raw.py

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	# 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.


	import datasets


	_DESCRIPTION = """\
	mono corpus from http://www.opensubtitles.org/. Please check http://www.opensubtitles.org/ for the available corpora and licenses.
	"""

	_HOMEPAGE_URL = "http://opus.nlpl.eu"

	_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)
	"""

	_BASE_URL = "https://object.pouta.csc.fi/OPUS-{}/{}/mono/{}.txt.gz"

	# Please note that only few pairs are shown here. You can use config to generate data for all language pairs
	_LANGUAGES = [
	("OpenSubtitles", "v2018", "en"),
	]


	class OpenSubtitlesConfig(datasets.BuilderConfig):
	def __init__(self, args, corpus=None, lang=None, *kwargs):
	corpus.strip()
	splits = corpus.split()
	corpus = splits[0]
	corpus_version = splits[1]

	super().__init__(
	*args,
	name=f"{corpus}-{corpus_version}-{lang}",
	**kwargs,
	)
	self.corpus = corpus
	self.corpus_version = corpus_version
	self.lang = lang


	class OpenSubtitles(datasets.GeneratorBasedBuilder):

	BUILDER_CONFIG_CLASS = OpenSubtitlesConfig

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"text": datasets.Value("string"),
	},
	),
	supervised_keys=None,
	homepage=_HOMEPAGE_URL,
	)

	def _split_generators(self, dl_manager):
	def _base_url(corpus, corpus_version, lang):
	return _BASE_URL.format(corpus, corpus_version, lang)

	download_url = _base_url(self.config.corpus, self.config.corpus_version, self.config.lang)
	path = dl_manager.download_and_extract(download_url)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"datapath": path},
	)
	]

	def _generate_examples(self, datapath):
	with open(datapath, encoding="utf-8") as f:
	for text_counter, line in enumerate(f):
	line = line.strip()

	result = (
	text_counter,
	{
	"id": str(text_counter),
	"text": line
	},
	)
	text_counter += 1
	yield result