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import datasets |
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_LANGUAGE_PAIRS = { |
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"en_de": "data/en_de.parquet", |
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"en_es": "data/en_es.parquet", |
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"en_fr": "data/en_fr.parquet", |
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"en_it": "data/en_it.parquet", |
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"en_ko": "data/en_ko.parquet", |
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"en_nl": "data/en_nl.parquet", |
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"en_pt": "data/en_pt.parquet", |
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"en_ru": "data/en_ru.parquet", |
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"en_zh": "data/en_zh.parquet", |
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} |
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VERSION = datasets.Version("1.0.0") |
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class Spite(datasets.GeneratorBasedBuilder): |
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VERSION = VERSION |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name=lang_pair, |
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version=VERSION, |
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description=f"Training data for language pair: {lang_pair}", |
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) |
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for lang_pair in _LANGUAGE_PAIRS |
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] |
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DEFAULT_CONFIG_NAME = "en_de" |
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def _info(self): |
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return datasets.DatasetInfo( |
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description="Pseudolabeled speech translation dataset", |
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features=datasets.Features({ |
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"src": datasets.Value("string"), |
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"mt": datasets.Value("string"), |
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'cometqe_22': datasets.Value("float64"), |
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'xcomet_xl': datasets.Value("float64"), |
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'blaser2_src': datasets.Value("float64"), |
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'audio_length': datasets.Value("float64"), |
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"example_id": datasets.Value("string"), |
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"index": datasets.Value("int64") |
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}), |
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supervised_keys=None, |
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) |
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def _split_generators(self, dl_manager): |
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parquet_path = dl_manager.download(_LANGUAGE_PAIRS[self.config.name]) |
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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={"filepath": parquet_path}, |
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) |
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] |
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def _generate_examples(self, filepath): |
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import pyarrow.parquet as pq |
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table = pq.read_table(filepath) |
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for idx, row in enumerate(table.to_pylist()): |
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yield idx, row |
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