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