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import csv |
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from typing import List |
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import datasets |
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LANGUAGES = ["ar", "de", "es", "fr", "hi", "it", "ja", "ko", "pl", "pt", "ta", "zh"] |
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DATA_PATH = "test.csv" |
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class XPQAConfig(datasets.BuilderConfig): |
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def __init__(self, language, **kwargs): |
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super().__init__(**kwargs) |
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self.language = language |
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class XPQA(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIG_CLASS = XPQAConfig |
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BUILDER_CONFIGS = [ |
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XPQAConfig(name=language, language=language) for language 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="xPQA is a large-scale annotated cross-lingual Product QA dataset.", |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"answer": datasets.Value("string"), |
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} |
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), |
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homepage="https://github.com/amazon-science/contextual-product-qa/tree/main?tab=readme-ov-file#xpqa", |
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citation="https://arxiv.org/abs/2305.09249", |
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) |
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def _split_generators( |
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self, dl_manager: datasets.DownloadManager |
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) -> List[datasets.SplitGenerator]: |
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downloaded_file = dl_manager.download_and_extract(DATA_PATH) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": downloaded_file} |
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), |
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] |
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def _generate_examples(self, filepath): |
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id_ = 0 |
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with open(filepath, newline="") as csvfile: |
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csvreader = csv.reader(csvfile, delimiter=",") |
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header = next(csvreader) |
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lang_pos = header.index("lang") |
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answer_pos = header.index("answer") |
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question_pos = header.index("question") |
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label_pos = header.index("label") |
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for row in csvreader: |
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if row[lang_pos] == self.config.language and row[label_pos] == "2": |
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answer = row[answer_pos] |
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question = row[question_pos] |
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if not answer or not question: |
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continue |
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yield id_, {"id": id_, "question": question, "answer": answer} |
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id_ += 1 |
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