IndicHeadlineGeneration.py

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 new headline generation dataset released as part of IndicNLG Suite. Each 
input document is paired an output title. We create this dataset in eleven 
languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total
size of the dataset is 1.43M.
"""
_HOMEPAGE = "https://indicnlp.ai4bharat.org/indicnlg-suite"

_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"

_URL = "https://huggingface.co/datasets/ai4bharat/IndicHeadlineGeneration/resolve/main/data/{}_IndicHeadlineGeneration_v{}.zip"


_LANGUAGES = [
    "as",
    "bn",
    "gu",
    "hi",
    "kn",
    "ml",
    "mr",
    "or",
    "pa",
    "ta",
    "te"
]
    

class IndicHeadlineGeneration(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"),
                    "input": datasets.Value("string"),
                    "target": datasets.Value("string"),
                    "url":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 + "_dev.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"],
                    "input": data["Document"],
                    "target": data["Title"],
                    "url":data["URL"]
                   
                }