Datasets:

larrylawl
/

opus

Tasks:

Multilinguality:

Language Creators:

expert-generated

Annotations Creators:

expert-generated

Tags:

parallel-corpus

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opus / opus.py

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	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the 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 json
	import os
	from typing import List
	import datasets
	import pandas as pd
	import opustools

	_DESCRIPTION = """\
	Downloads OPUS data using `opustools`.
	"""

	_VERSION = "1.0.0"
	_URL = "https://opus.nlpl.eu/"

	class OpusConfig(datasets.BuilderConfig):
	"""BuilderConfig for Opus Dataset."""

	def __init__(self, args, src=None, tgt=None, corpus=None, download_dir="data", *kwargs):
	""" BuilderConfig for Opus Dataset.
	The following args follows `opustools`: https://pypi.org/project/opustools/

	Args:
	src: str, source language
	tgt: str, target language
	corpus: str, corpus name. Leave as `None` to download all available corpus for the src-tgt pair.
	download_dir: str, dir to save downloaded files

	"""

	super(OpusConfig, self).__init__(
	*args,
	name=f"{src}-{tgt}",
	description=f"Translating {src} to {tgt} or vice versa",
	**kwargs)
	self.src = src
	self.tgt = tgt
	self.opus_get = opustools.OpusGet(source=src, target=tgt, list_resources=True, directory=corpus)
	self.download_dir = download_dir

	def get_corpora_data(self):
	""" Returns corpora, number of files, and total size. """
	return self.opus_get.get_corpora_data()


	class Opus(datasets.GeneratorBasedBuilder):
	""" Opus dataset.
	See: https://huggingface.co/docs/datasets/dataset_script#create-a-dataset-loading-script"""

	BUILDER_CONFIG_CLASS = OpusConfig

	def _info(self):
	features = {
	"src": datasets.Value("string"),
	"tgt": datasets.Value("string"),
	}

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(features),
	homepage=_URL,
	)

	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={}),
	]

	def _generate_examples(self):
	# read from specific corpus
	id_ = 0

	data = self.config.opus_get.get_corpora_data()
	self.config.opus_get.print_files(*data)

	for d in data[0]:
	opus_reader = opustools.OpusRead(
	directory=d["corpus"],
	source=self.config.src,
	target=self.config.tgt,
	write_mode="yield_tuple",
	leave_non_alignments_out=True,
	download_dir=self.config.download_dir,
	suppress_prompts=True,
	)
	gen = opus_reader.printPairs()
	for src, tgt in gen:
	yield id_, {"src": src, "tgt": tgt}
	id_ += 1