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import os |
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import json |
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import datasets |
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_DESCRIPTION = """datasets-for-simcse""" |
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_CITATION = '' |
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GITHUB_HOME = '' |
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class DatasetsForSimCSEConfig(datasets.BuilderConfig): |
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def __init__(self, features, data_url, citation, url, label_classes=(0, 1), **kwargs): |
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super().__init__(version=datasets.Version("1.0.0"), **kwargs) |
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self.features = features |
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self.label_classes = label_classes |
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self.data_url = data_url |
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self.citation = citation |
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self.url = url |
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class DatasetsForSimCSE(datasets.GeneratorBasedBuilder): |
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"""The Natural Language Inference Chinese(NLI_zh) Corpus.""" |
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BUILDER_CONFIGS = [ |
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DatasetsForSimCSEConfig( |
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name="nli_for_simcse", |
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description=_DESCRIPTION, |
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features=datasets.Features({"sent0": datasets.Value("string"), |
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"sent1": datasets.Value("string"), |
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"hard_neg": datasets.Value("string")}), |
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data_url='https://huggingface.co/datasets/princeton-nlp/datasets-for-simcse/resolve/main/nli_for_simcse.csv', |
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citation=_CITATION, |
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url=GITHUB_HOME, |
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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=self.config.description, |
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features=self.config.features, |
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homepage=self.config.url, |
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citation=self.config.citation, |
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) |
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def _split_generators(self, dl_manager): |
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filepath = dl_manager.download(self.config.data_url) |
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return [datasets.SplitGenerator( |
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name='nli_for_simcse', |
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gen_kwargs={ |
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"filepath": filepath, |
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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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with open(filepath, 'r', encoding="utf-8") as f: |
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f.readline() |
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for idx, row in enumerate(f.readlines()): |
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sent0, sent1, hard_neg = row.split(',') |
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context = {'sent0': sent0, 'sent1': sent1, 'hard_neg': hard_neg} |
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yield idx, context |
