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prajdabre
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KreolMorisienMT

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KreolMorisienMT
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import json
import os

import datasets

_CITATION = """\
Not Yet
"""

_DESCRIPTION = """\
This is the MorisienMT dataset for Muritian Creole Machine translation, English-Creole and French-Creole machine translation to be specific. See readme/datacard for details.
"""
_HOMEPAGE = "https://huggingface.co/datasets/prajdabre/MorisienMT"

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

_URL = "https://huggingface.co/datasets/prajdabre/MorisienMT/resolve/main/data/{}.zip"


_LANGUAGE_PAIRS = [
    "en-cr",
    "fr-cr",
    "cr"
]
    

class MorisienMT(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")
    
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name="{}".format(lang),
            version=datasets.Version("1.0.0")
        )
        for lang in _LANGUAGE_PAIRS
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "input": datasets.Value("string"),
                    "target": 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)

        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_, {
                    "input": data["input"],
                    "target": data["target"],
                    
                }