Datasets:
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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',
'combined',
]
_DESCRIPTION = 'dataset load script for Mr. TyDi'
_DATASET_URLS = {
lang: {
'train': f'https://huggingface.co/datasets/castorini/mr-tydi/resolve/main/mrtydi-v1.1-{lang}/train.jsonl.gz',
'dev': f'https://huggingface.co/datasets/castorini/mr-tydi/resolve/main/mrtydi-v1.1-{lang}/dev.jsonl.gz',
'test': f'https://huggingface.co/datasets/castorini/mr-tydi/resolve/main/mrtydi-v1.1-{lang}/test.jsonl.gz',
} for lang in languages
}
_DATASET_URLS['combined'] = {
'train': "https://huggingface.co/datasets/castorini/mr-tydi/resolve/main/mrtydi-v1.1-combined/train.jsonl.gz"
}
class MrTyDi(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({
'query_id': datasets.Value('string'),
'query': datasets.Value('string'),
'positive_passages': [{
'docid': datasets.Value('string'),
'text': datasets.Value('string'), 'title': datasets.Value('string')
}],
'negative_passages': [{
'docid': datasets.Value('string'),
'text': datasets.Value('string'), 'title': 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])
if lang != "combined":
splits = [
datasets.SplitGenerator(
name='train',
gen_kwargs={
'filepath': downloaded_files['train'],
},
),
datasets.SplitGenerator(
name='dev',
gen_kwargs={
'filepath': downloaded_files['dev'],
},
),
datasets.SplitGenerator(
name='test',
gen_kwargs={
'filepath': downloaded_files['test'],
},
),
]
else:
splits = [
datasets.SplitGenerator(
name='train',
gen_kwargs={
'filepath': downloaded_files['train'],
},
),
]
return splits
def _generate_examples(self, filepath):
with open(filepath) as f:
for i, line in enumerate(f):
data = json.loads(line)
for feature in ['negative_passages', 'positive_passages']:
if data.get(feature) is None:
data[feature] = []
yield data['query_id'], data
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