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"""RuTextSegNews: Dataset for automatic text semantic segmentation of Russian news""" |
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import json |
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import os |
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import datasets |
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_CITATION = """ |
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In progress |
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""" |
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_DESCRIPTION = "Dataset for automatic text semantic segmentation of Russian news" |
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_URLS = { |
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"train": "train.jsonl", |
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"test": "test.jsonl" |
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} |
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class RuTextSegNewsDataset(datasets.GeneratorBasedBuilder): |
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"""RuTextSegNews Dataset""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="default", version=VERSION, description=""), |
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] |
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DEFAULT_CONFIG_NAME = "default" |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"sentences": [datasets.Value("string")], |
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"labels": [datasets.Value("int8")], |
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"method": datasets.Value("string") |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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downloaded_files = dl_manager.download_and_extract(_URLS) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), |
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] |
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def _generate_examples(self, filepath): |
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with open(filepath, encoding="utf-8") as f: |
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for id_, row in enumerate(f): |
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data = json.loads(row) |
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yield id_, data |