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# -*- coding: utf-8 -*-
"""
@author:XuMing([email protected])
@description:
"""
"""Natural Language Inference (NLI) Chinese Corpus.(nli_zh)"""
import os
import json
import datasets
_DESCRIPTION = """SimCLUE：3000000+中文语义理解与匹配数据集"""
GITHUB_HOME = "https://github.com/CLUEbenchmark/SimCLUE"
_CITATION = "https://github.com/CLUEbenchmark/SimCLUE"
_DATA_URL = "https://storage.googleapis.com/cluebenchmark/tasks/simclue_public.zip"
class SimCLUEConfig(datasets.BuilderConfig):
def __init__(self, features, data_url, citation, url, label_classes=(0, 1), **kwargs):
super().__init__(version=datasets.Version("1.0.0"), **kwargs)
self.features = features
self.label_classes = label_classes
self.data_url = data_url
self.citation = citation
self.url = url
class SimCLUE(datasets.GeneratorBasedBuilder):
"""The Natural Language Inference Chinese(NLI_zh) Corpus."""
part_file = {'train_rank': 'train_rank.json',
'train_pair': 'train_pair.json',
'corpus': 'corpus.txt',
'train_pair_postive': 'train_pair_postive.json',
'dev': 'dev.json',
'test_public': 'test_public.json'}
BUILDER_CONFIGS = [
SimCLUEConfig(
name="train_rank",
description=_DESCRIPTION,
features=datasets.Features({"query": datasets.Value("string"),
"title": datasets.Value("string"),
"neg_title": datasets.Value("string")}),
data_url=_DATA_URL,
citation=_CITATION,
url=GITHUB_HOME,
),
SimCLUEConfig(
name="train_pair",
description=_DESCRIPTION,
features=datasets.Features({"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"label": datasets.Value("int32")}),
data_url=_DATA_URL,
citation=_CITATION,
url=GITHUB_HOME,
),
SimCLUEConfig(
name="corpus",
description=_DESCRIPTION,
features=datasets.Features({"sentence1": datasets.Value("string")}),
data_url=_DATA_URL,
citation=_CITATION,
url=GITHUB_HOME,
),
SimCLUEConfig(
name="train_pair_postive",
description=_DESCRIPTION,
features=datasets.Features({"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"label": datasets.Value("int32")}),
data_url=_DATA_URL,
citation=_CITATION,
url=GITHUB_HOME,
),
SimCLUEConfig(
name="dev",
description=_DESCRIPTION,
features=datasets.Features({"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"label": datasets.Value("int32")}),
data_url=_DATA_URL,
citation=_CITATION,
url=GITHUB_HOME,
),
SimCLUEConfig(
name="test_public",
description=_DESCRIPTION,
features=datasets.Features({"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"label": datasets.Value("int32")}),
data_url=_DATA_URL,
citation=_CITATION,
url=GITHUB_HOME,
),
]
def _info(self):
return datasets.DatasetInfo(
description=self.config.description,
features=self.config.features,
homepage=self.config.url,
citation=self.config.citation,
)
def _split_generators(self, dl_manager):
dl_dir = dl_manager.download_and_extract(self.config.data_url)
return [datasets.SplitGenerator(
name=self.config.name,
gen_kwargs={
"filepath": os.path.join(dl_dir, self.part_file[self.config.name]),
})]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
with open(filepath, 'r', encoding="utf-8") as f:
for idx, row in enumerate(f):
yield idx, json.loads(row)
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