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"""STS Benchmark Multilingual dataset""" |
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import json |
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import os |
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import gzip |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """\ |
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STS Benchmark Multilingual dataset by deepl and google (only ar) |
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""" |
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_LANGUAGES = ["de", "en", "es", "fr", "it", "nl", "pl", "pt", "ru", "zh"] |
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_NEW_LANGUAGES = ['ar', 'id'] |
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class STSBMultilingual(datasets.GeneratorBasedBuilder): |
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"""STS Benchmark Multilingual""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name=name, |
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version=datasets.Version("1.0.0"), |
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description=f"The STS Benchmark for {name} language{'' if name == 'en' else ' by deepl'}.", |
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) |
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for name in _LANGUAGES |
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] + [ |
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datasets.BuilderConfig( |
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name='id', |
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version=datasets.Version("1.0.0"), |
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description=f"The STS Benchmark for id language by deepl.", |
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), |
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datasets.BuilderConfig( |
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name='ar', |
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version=datasets.Version("1.0.0"), |
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description=f"The STS Benchmark for id language by google translate.", |
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) |
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] |
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DEFAULT_CONFIG_NAME = 'en' |
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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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"sentence1": datasets.Value("string"), |
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"sentence2": datasets.Value("string"), |
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"score": datasets.Value("float32"), |
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}, |
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), |
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supervised_keys=None, |
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homepage="https://github.com/PhilipMay/stsb-multi-mt", |
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) |
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def _split_generators(self, dl_manager): |
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if self.config.name == 'ar': |
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path_or_ds = dl_manager.download('test_ar_google.jsonl') |
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elif self.config.name == 'id': |
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path_or_ds = dl_manager.download('test_id_deepl.jsonl') |
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else: |
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path_or_ds = datasets.load_dataset("stsb_multi_mt", self.config.name, split="test") |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, gen_kwargs={"path_or_ds": path_or_ds}, |
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), |
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] |
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def _generate_examples(self, path_or_ds): |
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"""Yields examples.""" |
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if isinstance(path_or_ds, datasets.Dataset): |
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for i, ins in enumerate(path_or_ds): |
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yield i, {'sentence1': ins['sentence1'], 'sentence2': ins['sentence2'], 'score': ins['similarity_score']} |
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else: |
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with open(path_or_ds) as f: |
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for i, line in enumerate(f): |
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yield i, json.loads(line) |
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