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import os |
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import datasets |
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import pandas as pd |
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class semiTextcConfig(datasets.BuilderConfig): |
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def __init__(self, features, data_url, **kwargs): |
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super(semiTextcConfig, self).__init__(**kwargs) |
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self.features = features |
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self.data_url = data_url |
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class semiTextc(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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semiTextcConfig( |
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name="pairs", |
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features={ |
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"ltable_id": datasets.Value("string"), |
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"rtable_id": datasets.Value("string"), |
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"label": datasets.Value("string"), |
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}, |
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data_url="https://huggingface.co/datasets/matchbench/semi-Textc/resolve/main/", |
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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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features=datasets.Features(self.config.features) |
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) |
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def _split_generators(self, dl_manager): |
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if self.config.name == "pairs": |
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return [ |
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datasets.SplitGenerator( |
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name=split, |
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gen_kwargs={ |
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"path_file": dl_manager.download_and_extract( |
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os.path.join(self.config.data_url, f"{split}.csv")), |
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"split": split, |
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} |
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) |
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for split in ["train", "valid", "test"] |
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] |
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def _generate_examples(self, path_file, split): |
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file = pd.read_csv(path_file) |
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for i, row in file.iterrows(): |
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if split in ['train', 'valid','test']: |
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yield i, { |
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"ltable_id": row["ltable_id"], |
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"rtable_id": row["rtable_id"], |
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"label": row["label"], |
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} |
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