xnli_bn.py

"""XNLI Bengali dataset"""
import json
import os

import datasets


_CITATION = """\
@misc{bhattacharjee2021banglabert,
      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding},
      author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},
      year={2021},
      eprint={2101.00204},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
"""
_DESCRIPTION = """\
This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of
MNLI data used in XNLI and state-of-the-art English to Bengali translation model.
"""
_HOMEPAGE = "https://github.com/csebuetnlp/banglabert"
_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"
_URL = "https://huggingface.co/datasets/csebuetnlp/xnli_bn/resolve/main/data/xnli_bn.tar.bz2"
_VERSION = datasets.Version("0.0.1")


class XnliBn(datasets.GeneratorBasedBuilder):
    """XNLI Bengali dataset"""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name="xnli_bn",
            version=_VERSION,
            description=_DESCRIPTION,
        )
    ]

    def _info(self):
        features = datasets.Features(
            {
                "sentence1": datasets.Value("string"),
                "sentence2": datasets.Value("string"),
                "label": datasets.features.ClassLabel(names=["contradiction", "entailment", "neutral"]),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
            version=_VERSION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        data_dir = os.path.join(dl_manager.download_and_extract(_URL), "xnli_bn")
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, "train.jsonl"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, "test.jsonl"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, "validation.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_, {"sentence1": data["sentence1"], "sentence2": data["sentence2"], "label": data["label"]}