| | import json |
| | import os |
| |
|
| | import datasets |
| |
|
| | _CITATION = """\ |
| | @inproceedings{Kumar2022IndicNLGSM, |
| | title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages}, |
| | author={Aman Kumar and Himani Shrotriya and Prachi Sahu and Raj Dabre and Ratish Puduppully and Anoop Kunchukuttan and Amogh Mishra and Mitesh M. Khapra and Pratyush Kumar}, |
| | year={2022}, |
| | url = "https://arxiv.org/abs/2203.05437" |
| | } |
| | """ |
| |
|
| | _DESCRIPTION = """\ |
| | This is the WikiBio dataset released as part of IndicNLG Suite. Each |
| | example has four fields: id, infobox, serialized infobox and summary. We create this dataset in nine |
| | languages including as, bn, hi, kn, ml, or, pa, ta, te. The total |
| | size of the dataset is 57,426. |
| | """ |
| | _HOMEPAGE = "https://indicnlp.ai4bharat.org/indicnlg-suite" |
| |
|
| | _LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License" |
| |
|
| | _URL = "https://huggingface.co/datasets/ai4bharat/IndicWikiBio/resolve/main/data/{}_WikiBio_v{}.zip" |
| |
|
| |
|
| | _LANGUAGES = [ |
| | "as", |
| | "bn", |
| | "hi", |
| | "kn", |
| | "ml", |
| | "or", |
| | "pa", |
| | "ta", |
| | "te" |
| | ] |
| | |
| |
|
| | class WikiBio(datasets.GeneratorBasedBuilder): |
| | VERSION = datasets.Version("1.0.0") |
| | |
| | BUILDER_CONFIGS = [ |
| | datasets.BuilderConfig( |
| | name="{}".format(lang), |
| | version=datasets.Version("1.0.0") |
| | ) |
| | for lang in _LANGUAGES |
| | ] |
| |
|
| | def _info(self): |
| | return datasets.DatasetInfo( |
| | description=_DESCRIPTION, |
| | features=datasets.Features( |
| | { |
| | "id": datasets.Value("string"), |
| | "infobox": datasets.Value("string"), |
| | "serialized_infobox": datasets.Value("string"), |
| | "summary": datasets.Value("string") |
| | } |
| | ), |
| | supervised_keys=None, |
| | homepage=_HOMEPAGE, |
| | citation=_CITATION, |
| | license=_LICENSE, |
| | version=self.VERSION, |
| | ) |
| |
|
| | def _split_generators(self, dl_manager): |
| | """Returns SplitGenerators.""" |
| | lang = str(self.config.name) |
| | url = _URL.format(lang, self.VERSION.version_str[:-2]) |
| |
|
| | data_dir = dl_manager.download_and_extract(url) |
| | return [ |
| | datasets.SplitGenerator( |
| | name=datasets.Split.TRAIN, |
| | gen_kwargs={ |
| | "filepath": os.path.join(data_dir, lang + "_train" + ".jsonl"), |
| | }, |
| | ), |
| | datasets.SplitGenerator( |
| | name=datasets.Split.TEST, |
| | gen_kwargs={ |
| | "filepath": os.path.join(data_dir, lang + "_test" + ".jsonl"), |
| | }, |
| | ), |
| | datasets.SplitGenerator( |
| | name=datasets.Split.VALIDATION, |
| | gen_kwargs={ |
| | "filepath": os.path.join(data_dir, lang + "_val" + ".jsonl"), |
| | }, |
| | ), |
| | ] |
| |
|
| | def _generate_examples(self, filepath): |
| | """Yields examples as (key, example) tuples.""" |
| | with open(filepath, encoding="utf-8") as f: |
| | for idx_, row in enumerate(f): |
| | data = json.loads(row) |
| | yield idx_, { |
| | "id": data["id"], |
| | "infobox": data["infobox"], |
| | "serialized_infobox": data["serialized_infobox"], |
| | "summary": data["summary"] |
| | |
| | } |
| |
|