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mbert-mrtydi-corpus

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mbert-mrtydi-corpus / mbert-mrtydi-corpus.py

Crystina Zhang

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	# 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 = '''
	@article{mrtydi,
	title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval},
	author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin},
	year={2021},
	journal={arXiv:2108.08787},
	}
	'''

	languages = [
	'arabic',
	'bengali',
	'english',
	'indonesian',
	'finnish',
	'korean',
	'russian',
	'swahili',
	'telugu',
	'thai',
	'japanese',
	]

	_DESCRIPTION = 'dataset load script for Mr. TyDi'

	_DATASET_URLS = {
	lang: {
	'train': f'https://huggingface.co/datasets/crystina-z/mbert-mrtydi-corpus/resolve/main/mr-tydi-v1.1-mbert-tokenize-{lang}/corpus.jsonl.gz',
	} for lang in languages
	}


	class MrTyDiCorpus(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	version=datasets.Version('1.1.0'),
	name=lang,
	description=f'Mr TyDi dataset in language {lang}.'
	) for lang in languages
	]

	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://github.com/castorini/mr.tydi',
	# 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={
	'filepath': downloaded_files['train'],
	},
	),
	]
	return splits

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