Datasets:
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Parent(s):
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Create sts-sohu2021.py
Browse files- sts-sohu2021.py +102 -0
sts-sohu2021.py
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# -*- coding: utf-8 -*-
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"""
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@author:XuMing(xuming624@qq.com)
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@description:
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2021搜狐校园文本匹配算法大赛数据集
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upload: https://github.com/shibing624
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"""
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import csv
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import os
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import json
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import datasets
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_CITATION = """https://github.com/shibing624/text2vec"""
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_DESCRIPTION = """\
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2021搜狐校园文本匹配算法大赛数据集
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"""
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_DATA_URL = "https://huggingface.co/datasets/shibing624/sts-sohu2021/resolve/main/"
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class Sohu(datasets.GeneratorBasedBuilder):
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"""The Chinese Natural Language Inference (sts-sohu) Corpus."""
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="dda",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of sts-sohu2021",
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),
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datasets.BuilderConfig(
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name="ddb",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of sts-sohu2021",
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),
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datasets.BuilderConfig(
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name="dca",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of sts-sohu2021",
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),
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datasets.BuilderConfig(
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name="dcb",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of sts-sohu2021",
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),
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datasets.BuilderConfig(
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name="cca",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of sts-sohu2021",
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),
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datasets.BuilderConfig(
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name="ccb",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of sts-sohu2021",
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),
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"sentence1": datasets.Value("string"),
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"sentence2": datasets.Value("string"),
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"label": datasets.Value("int32"),
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}
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),
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supervised_keys=None,
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homepage="https://github.com/shibing624/text2vec",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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dl_dir = dl_manager.download_and_extract(_DATA_URL)
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dl_file = f"{dl_dir}/{self.config.name}.jsonl"
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_file}
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),
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]
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def _generate_examples(self, filepath):
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"""This function returns the examples in the raw (text) form."""
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id = 0
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if isinstance(filepath, str):
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filepath = [filepath]
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for file in filepath:
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with open(file, encoding="utf-8") as f:
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for key, row in enumerate(f):
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data = json.loads(row)
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yield id, {
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"sentence1": data["sentence1"],
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"sentence2": data["sentence2"],
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"label": int(data["label"])
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}
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id += 1
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