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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{Kumar2022IndicNLGSM,
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title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages},
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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},
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year={2022},
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url = "https://arxiv.org/abs/2203.05437"
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}
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"""
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_DESCRIPTION = """\
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This is the Question Generation dataset released as part of IndicNLG Suite. Each
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example has five fields: id, squad_id, answer, context and question. We create this dataset in eleven
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languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. This is a translated data. The examples in each language are exactly similar but in different languages.
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The number of examples in each language is 98,027.
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"""
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_HOMEPAGE = "https://indicnlp.ai4bharat.org/indicnlg-suite"
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_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"
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_URL = "https://huggingface.co/datasets/ai4bharat/IndicQuestionGeneration/resolve/main/data/{}_IndicQuestionGeneration_v{}.tar.bz2"
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_LANGUAGES = [
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"as",
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"bn",
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"gu",
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"hi",
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"kn",
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"ml",
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"mr",
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"or",
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"pa",
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"ta",
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"te"
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]
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class WikiBio(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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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("1.0.0")
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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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"squad_id": datasets.Value("string"),
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"answer": datasets.Value("string"),
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"context": datasets.Value("string"),
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"question": 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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"squad_id": data["squad_id"],
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"answer": data["answer"],
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"context": data["context"],
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"question": data["question"]
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}
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