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import json |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """@misc{degibert2022sequencetosequence, |
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title={Sequence-to-Sequence Resources for Catalan}, |
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author={Ona de Gibert and Ksenia Kharitonova and Blanca Calvo Figueras and Jordi Armengol-Estapé and Maite Melero}, |
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year={2022}, |
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eprint={2202.06871}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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}""" |
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_DESCRIPTION = """CaSum is a summarization dataset. It is extracted from a newswire corpus crawled from the Catalan News Agency. The corpus consists of 217,735 instances that are composed by the headline and the body. |
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""" |
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_HOMEPAGE = """https://github.com/TeMU-BSC/seq-to-seq-catalan""" |
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_URL = "https://huggingface.co/datasets/projecte-aina/casum/resolve/main/" |
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_TRAIN_FILE = "train.jsonl" |
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_VALID_FILE = "valid.jsonl" |
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_TEST_FILE = "test.jsonl" |
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class CaSumConfig(datasets.BuilderConfig): |
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""" Builder config for the CaSum dataset """ |
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def __init__(self, **kwargs): |
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"""BuilderConfig for CaSum. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(CaSumConfig, self).__init__(**kwargs) |
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class CaSum(datasets.GeneratorBasedBuilder): |
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"""CaSum Dataset.""" |
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BUILDER_CONFIGS = [ |
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CaSumConfig( |
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name="CaSum", |
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version=datasets.Version("1.0.0"), |
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description="CaSum dataset" |
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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=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"summary": datasets.Value("string"), |
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"text": datasets.Value("string") |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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urls_to_download = { |
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"train": f"{_URL}{_TRAIN_FILE}", |
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"valid": f"{_URL}{_VALID_FILE}", |
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"test": f"{_URL}{_TEST_FILE}" |
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} |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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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.VALIDATION, gen_kwargs={"filepath": downloaded_files["valid"]}), |
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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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"""This function returns the examples in the raw (text) form.""" |
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logger.info("generating examples from = %s", filepath) |
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with open(filepath) as f: |
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for id_, row in enumerate(f): |
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article = json.loads(row) |
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text = article['text'] |
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summary = article['summary'] |
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yield id_, { "summary": summary,"text": text} |
