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import gzip |
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import json |
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import datasets |
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_URLS = { |
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"csl": "https://huggingface.co/datasets/neuclir/csl/resolve/main/data/csl.jsonl.gz", |
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"en_translation": "https://huggingface.co/datasets/neuclir/csl/resolve/main/data/csl.gt.063023.jsonl.gz", |
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} |
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class Csl(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.1.1") |
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def _info(self): |
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return datasets.DatasetInfo( |
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features=datasets.Features({ |
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"doc_id": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"abstract": datasets.Value("string"), |
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"keywords": datasets.Sequence(feature=datasets.Value("string"), length=-1), |
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"category": datasets.Value("string"), |
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"category_eng": datasets.Value("string"), |
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"discipline": datasets.Value("string"), |
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"discipline_eng": datasets.Value("string"), |
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}), |
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) |
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def _split_generators(self, dl_manager): |
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paths = dl_manager.download(_URLS) |
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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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"filepath": paths[split], |
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}) |
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for split in _URLS |
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] |
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def _generate_examples(self, filepath): |
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with gzip.open(filepath) as f: |
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for key, row in enumerate(f): |
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data = json.loads(row) |
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if "category_eng" not in data: |
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data["category_eng"] = "" |
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data["discipline_eng"] = "" |
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yield key, data |
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