Datasets:

miracl
/

miracl-corpus

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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 datasets
	from dataclasses import dataclass

	_CITATION = '''
	'''

	languages2filesize = {
	'ar': 5,
	'bn': 1,
	'en': 66 ,
	'es': 21,
	'fa': 5,
	'fi': 4,
	'fr': 30,
	'hi': 2,
	'id': 3,
	'ja': 14,
	'ko': 3,
	'ru': 20,
	'sw': 1,
	'te': 2,
	'th': 2,
	'zh': 10,
	'de': 32,
	'yo': 1,
	}

	_DESCRIPTION = 'dataset load script for MIRACL'

	_DATASET_URLS = {
	lang: {
	'train': [
	f'https://huggingface.co/datasets/miracl/miracl-corpus/resolve/main/miracl-corpus-v1.0-{lang}/docs-{i}.jsonl.gz' for i in range(n)
	]
	} for lang, n in languages2filesize.items()
	}


	class MIRACLCorpus(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	version=datasets.Version('1.0.0'),
	name=lang,
	description=f'MIRACL dataset in language {lang}.'
	) for lang in languages2filesize
	]

	def _info(self):
	features = datasets.Features({
	'docid': datasets.Value('string'),
	'title': datasets.Value('string'),
	'text': datasets.Value('string'),
	})

	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage='https://project-miracl.github.io',
	# License for the dataset if available
	license='',
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	lang = self.config.name
	downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[lang])

	splits = [
	datasets.SplitGenerator(
	name='train',
	gen_kwargs={
	'filepaths': downloaded_files['train'],
	},
	),
	]
	return splits

	def _generate_examples(self, filepaths):
	for filepath in sorted(filepaths):
	with open(filepath, encoding="utf-8") as f:
	for line in f:
	data = json.loads(line)
	yield data['docid'], data