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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 paraphrasing dataset released as part of IndicNLG Suite. Each |
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input is paired with up to 5 references. We create this dataset in eleven |
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languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total |
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size of the dataset is 5.57M. |
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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/IndicParaphrase/resolve/main/data/{}_IndicParaphrase_v{}.zip" |
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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 IndicParaphrase(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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"pivot": datasets.Value("string"), |
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"input": datasets.Value("string"), |
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"target": datasets.Value("string"), |
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"references": [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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if lang == 'as' : |
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return [ |
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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, "test_" + lang + ".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, "dev_" + lang + ".jsonl"), |
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}, |
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), |
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] |
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else : |
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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, "train_" + lang + ".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, "test_" + lang + ".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, "dev_" + lang + ".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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"pivot": data["pivot"], |
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"input": data["input"], |
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"target": data["target"], |
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"references": data["references"] |
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} |
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