dureader-retrieval-ranking / dureader-retrieval-ranking.py
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Update dureader-retrieval-ranking.py
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# coding=utf-8
# Lint as: python3
"""Dureader Retrieval dataset."""
import json
import datasets
_CITATION = """
@article{Qiu2022DuReader\_retrievalAL,
title={DuReader\_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine},
author={Yifu Qiu and Hongyu Li and Yingqi Qu and Ying Chen and Qiaoqiao She and Jing Liu and Hua Wu and Haifeng Wang},
journal={ArXiv},
year={2022},
volume={abs/2203.10232}
}
"""
_DESCRIPTION = "Dureader-Retrieval datas"
_DATASET_URLS = {
'train': "https://huggingface.co/datasets/zyznull/dureader-retrieval-ranking/resolve/main/train.jsonl.gz",
'dev': "https://huggingface.co/datasets/zyznull/dureader-retrieval-ranking/resolve/main/dev.jsonl.gz"
}
class DureaderRetrieval(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("0.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(version=VERSION,
description="Dureader Retrieval train/dev datasets"),
]
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')}
],
'negative_passages': [
{'docid': 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="",
# License for the dataset if available
license="",
# Citation for the dataset
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download_and_extract(_DATASET_URLS)
splits = [
datasets.SplitGenerator(
name=split,
gen_kwargs={
"files": [downloaded_files[split]] if isinstance(downloaded_files[split], str) else downloaded_files[split],
},
) for split in downloaded_files
]
return splits
def _generate_examples(self, files):
"""Yields examples."""
for filepath in files:
with open(filepath, encoding="utf-8") as f:
for line in f:
data = json.loads(line)
if data.get('negative_passages') is None:
data['negative_passages'] = []
if data.get('positive_passages') is None:
data['positive_passages'] = []
yield data['query_id'], data