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""" |
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from datasets import load_dataset |
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data = load_dataset(".") |
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""" |
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import json |
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import datasets |
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|
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """ Named-entities Relation Ranking. """ |
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_NAME = "relentless" |
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_VERSION = "0.2.4" |
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_CITATION = """TBA""" |
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_HOME_PAGE = "https://huggingface.co/datasets/cardiffnlp/relentless" |
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_URL = f'https://huggingface.co/datasets/cardiffnlp/{_NAME}/raw/main' |
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_URLS = { |
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str(datasets.Split.VALIDATION): [f'{_URL}/data/data_processed.new.validation.jsonl'], |
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str(datasets.Split.TEST): [f'{_URL}/data/data_processed.new.test.jsonl'] |
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} |
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class RelentlessConfig(datasets.BuilderConfig): |
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"""BuilderConfig""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(RelentlessConfig, self).__init__(**kwargs) |
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class Relentless(datasets.GeneratorBasedBuilder): |
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"""Dataset.""" |
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BUILDER_CONFIGS = [RelentlessConfig(version=datasets.Version(_VERSION), description=_DESCRIPTION)] |
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|
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def _split_generators(self, dl_manager): |
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downloaded_file = dl_manager.download_and_extract(_URLS) |
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return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]}) |
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for i in [datasets.Split.VALIDATION, datasets.Split.TEST]] |
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|
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def _generate_examples(self, filepaths): |
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_key = 0 |
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for filepath in filepaths: |
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logger.info(f"generating examples from = {filepath}") |
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with open(filepath, encoding="utf-8") as f: |
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_list = [i for i in f.read().split('\n') if len(i) > 0] |
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for i in _list: |
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data = json.loads(i) |
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yield _key, data |
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_key += 1 |
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|
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"pairs": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), |
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"scores_all": datasets.Sequence(datasets.Sequence(datasets.Value('int32'))), |
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"scores_mean": datasets.Sequence(datasets.Value("float32")), |
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"relation_type": datasets.Value("string"), |
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"prototypical_examples": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), |
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"ranks": datasets.Sequence(datasets.Value('int32')) |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOME_PAGE, |
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citation=_CITATION, |
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) |
