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import json |
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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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""" |
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_DESCRIPTION = """\ |
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""" |
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_HOMEPAGE = "https://indicnlp.ai4bharat.org/" |
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_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License" |
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_URL = "https://huggingface.co/datasets/AnanthZeke/naamapadam/main/data/{}_IndicNER_v{}.zip" |
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_LANGUAGES = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"] |
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class Naamapadam(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), 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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"tokens": datasets.Sequence(datasets.Value("string")), |
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"tags": datasets.Sequence( |
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datasets.features.ClassLabel( |
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names=[ |
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"O", |
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"B-PER", |
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"I-PER", |
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"B-ORG", |
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"I-ORG", |
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"B-LOC", |
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"I-LOC", |
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] |
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) |
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), |
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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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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, lang + "_train.json"), |
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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, lang + "_test.json"), |
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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, lang + "_val.json"), |
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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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logger.info(f"generating examples from = {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_, {"tokens": data["words"], "tags": data["ner"]} |
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