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"""Samanantar dataset.""" |
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from pathlib import Path |
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import datasets |
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_CITATION = """\ |
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@misc{ramesh2021samanantar, |
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title={Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages}, |
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author={Gowtham Ramesh and Sumanth Doddapaneni and Aravinth Bheemaraj and Mayank Jobanputra and Raghavan AK and Ajitesh Sharma and Sujit Sahoo and Harshita Diddee and Mahalakshmi J and Divyanshu Kakwani and Navneet Kumar and Aswin Pradeep and Srihari Nagaraj and Kumar Deepak and Vivek Raghavan and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra}, |
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year={2021}, |
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eprint={2104.05596}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Samanantar is the largest publicly available parallel corpora collection for Indic languages: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu. The corpus has 49.6M sentence pairs between English to Indian Languages. |
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""" |
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_HOMEPAGE = "https://indicnlp.ai4bharat.org/samanantar/" |
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_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International" |
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_URLS = { |
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"0.3.0": "https://objectstore.e2enetworks.net/ai4b-public-nlu-nlg/samanantar_paper_version.zip", |
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} |
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_LANGUAGES = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"] |
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class SamanantarConfig(datasets.BuilderConfig): |
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VERSION = datasets.Version("0.3.0") |
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def __init__(self, language=None, version=VERSION, **kwargs): |
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super().__init__(name=language, version=version, **kwargs) |
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self.language = language |
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class Samanantar(datasets.GeneratorBasedBuilder): |
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"""Samanantar dataset.""" |
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BUILDER_CONFIG_CLASS = SamanantarConfig |
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BUILDER_CONFIGS = [SamanantarConfig(language=language) for language in _LANGUAGES] |
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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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"idx": datasets.Value("int64"), |
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"src": datasets.Value("string"), |
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"tgt": 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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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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urls = _URLS[str(self.config.version)] |
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data_dir = dl_manager.download_and_extract(urls) |
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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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"data_dir": (Path(data_dir) / "samanantar_paper_version" / f"en-{self.config.language}"), |
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}, |
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), |
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] |
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def _generate_examples(self, data_dir): |
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src_path = data_dir / "train.en" |
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tgt_path = data_dir / f"train.{self.config.language}" |
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with src_path.open(encoding="utf-8") as src_file, tgt_path.open(encoding="utf-8") as tgt_file: |
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for idx, (src_line, tgt_line) in enumerate(zip(src_file, tgt_file)): |
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yield idx, {"idx": idx, "src": src_line.strip(), "tgt": tgt_line.strip()} |
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