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Browse files- casum.py +0 -86
- test.jsonl +0 -3
- train.jsonl +0 -3
- valid.jsonl +0 -3
casum.py
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# Loading script for the CaSum dataset.
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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}
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test.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:a89ab6ba4a414c5eeb3bb12984930a8c1572fb9a45a3180635215503f96732fe
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size 22414860
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train.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:f2f41efa8ea790d57e3aa4dbaf786aba5589435e8fc8491d7511df975c5ca01e
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size 442268535
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valid.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb210735172c0d09e6321c6fa5cab9dc12fd5ffa2b254c5916c70b287b8c9e03
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size 22387837
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