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# -*- coding: utf-8 -*-
"""
@author:XuMing(xuming624@qq.com)
@description:
2021搜狐校园文本匹配算法大赛数据集
upload： https://github.com/shibing624
"""
import csv
import os
import json
import datasets
_CITATION = """https://github.com/shibing624/text2vec"""
_DESCRIPTION = """\
2021搜狐校园文本匹配算法大赛数据集
"""
_DATA_URL = "https://huggingface.co/datasets/shibing624/sts-sohu2021/resolve/main"
class Sohu(datasets.GeneratorBasedBuilder):
"""The Chinese Natural Language Inference (sts-sohu) Corpus."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="dda",
version=datasets.Version("1.0.0", ""),
description="Plain text import of sts-sohu2021",
),
datasets.BuilderConfig(
name="ddb",
version=datasets.Version("1.0.0", ""),
description="Plain text import of sts-sohu2021",
),
datasets.BuilderConfig(
name="dca",
version=datasets.Version("1.0.0", ""),
description="Plain text import of sts-sohu2021",
),
datasets.BuilderConfig(
name="dcb",
version=datasets.Version("1.0.0", ""),
description="Plain text import of sts-sohu2021",
),
datasets.BuilderConfig(
name="cca",
version=datasets.Version("1.0.0", ""),
description="Plain text import of sts-sohu2021",
),
datasets.BuilderConfig(
name="ccb",
version=datasets.Version("1.0.0", ""),
description="Plain text import of sts-sohu2021",
),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"label": datasets.Value("int32"),
}
),
supervised_keys=None,
homepage="https://github.com/shibing624/text2vec",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
# https://huggingface.co/datasets/shibing624/sts-sohu2021/resolve/main/dda.jsonl
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": dl_manager.download_and_extract(f"{_DATA_URL}/{self.config.name}-train.jsonl")
}
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": dl_manager.download_and_extract(f"{_DATA_URL}/{self.config.name}-test.jsonl")
}
),
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (jsonl) form."""
id = 0
if isinstance(filepath, str):
filepath = [filepath]
for file in filepath:
with open(file, encoding="utf-8") as f:
for key, row in enumerate(f):
if row and len(row) > 1:
data = json.loads(row)
yield id, {
"sentence1": data["sentence1"],
"sentence2": data["sentence2"],
"label": int(data["label"])
}
id += 1 |