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"""XL-Sum abstractive summarization dataset.""" |
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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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@inproceedings{hasan-etal-2021-xl, |
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title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages", |
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author = "Hasan, Tahmid and |
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Bhattacharjee, Abhik and |
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Islam, Md. Saiful and |
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Mubasshir, Kazi and |
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Li, Yuan-Fang and |
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Kang, Yong-Bin and |
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Rahman, M. Sohel and |
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Shahriyar, Rifat", |
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booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021", |
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month = aug, |
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year = "2021", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2021.findings-acl.413", |
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pages = "4693--4703", |
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} |
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""" |
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_DESCRIPTION = """\ |
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We present XLSum, a comprehensive and diverse dataset comprising 1.35 million professionally |
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annotated article-summary pairs from BBC, extracted using a set of carefully designed heuristics. |
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The dataset covers 45 languages ranging from low to high-resource, for many of which no |
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public dataset is currently available. XL-Sum is highly abstractive, concise, |
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and of high quality, as indicated by human and intrinsic evaluation. |
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""" |
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_HOMEPAGE = "https://github.com/csebuetnlp/xl-sum" |
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_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)" |
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_URL = "https://huggingface.co/datasets/csebuetnlp/xlsum/resolve/main/data/{}_XLSum_v{}.tar.bz2" |
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_LANGUAGES = [ |
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"oromo", |
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"french", |
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"amharic", |
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"arabic", |
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"azerbaijani", |
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"bengali", |
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"burmese", |
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"chinese_simplified", |
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"chinese_traditional", |
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"welsh", |
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"english", |
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"kirundi", |
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"gujarati", |
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"hausa", |
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"hindi", |
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"igbo", |
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"indonesian", |
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"japanese", |
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"korean", |
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"kyrgyz", |
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"marathi", |
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"spanish", |
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"scottish_gaelic", |
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"nepali", |
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"pashto", |
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"persian", |
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"pidgin", |
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"portuguese", |
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"punjabi", |
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"russian", |
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"serbian_cyrillic", |
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"serbian_latin", |
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"sinhala", |
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"somali", |
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"swahili", |
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"tamil", |
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"telugu", |
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"thai", |
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"tigrinya", |
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"turkish", |
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"ukrainian", |
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"urdu", |
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"uzbek", |
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"vietnamese", |
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"yoruba", |
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] |
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class Xlsum(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("2.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="{}".format(lang), |
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version=datasets.Version("2.0.0") |
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) |
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for lang in _LANGUAGES |
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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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"id": datasets.Value("string"), |
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"url": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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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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license=_LICENSE, |
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version=self.VERSION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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lang = str(self.config.name) |
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url = _URL.format(lang, self.VERSION.version_str[:-2]) |
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data_dir = dl_manager.download_and_extract(url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": os.path.join(data_dir, lang + "_train.jsonl"), |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepath": os.path.join(data_dir, lang + "_test.jsonl"), |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepath": os.path.join(data_dir, lang + "_val.jsonl"), |
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}, |
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), |
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] |
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def _generate_examples(self, filepath): |
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"""Yields examples as (key, example) tuples.""" |
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with open(filepath, encoding="utf-8") as f: |
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for idx_, row in enumerate(f): |
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data = json.loads(row) |
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yield idx_, { |
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"id": data["id"], |
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"url": data["url"], |
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"title": data["title"], |
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"summary": data["summary"], |
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"text": data["text"], |
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} |
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