| 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 |
|
|