import os import datasets import json _CITATION = """\ """ _DESCRIPTION = """\ OlympicArena """ _HOMEPAGE = "" _URL = "" subject_list = ["Math", "Physics", "Chemistry", "Biology", "Geography", "Astronomy", "CS"] class OlympicArenaConfig(datasets.BuilderConfig): """BuilderConfig""" def __init__(self, **kwargs): """BuilderConfig Args: **kwargs: keyword arguments forwarded to super. """ super(OlympicArenaConfig, self).__init__(**kwargs) class OlympicArena(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ OlympicArenaConfig(name=subject) for subject in subject_list ] def _info(self): features = datasets.Features( { "id": datasets.Value("string"), "problem": datasets.Value("string"), "prompt": datasets.Value("string"), "figure_urls": datasets.Sequence(datasets.Value("string")), "answer": datasets.Sequence(datasets.Value("string")), "solution": datasets.Value("string"), "answer_type": datasets.Value("string"), "unit": datasets.Sequence(datasets.Value("string")), "answer_sequence": datasets.Sequence(datasets.Value("string")), "type_sequence": datasets.Sequence(datasets.Value("string")), "test_cases": datasets.Sequence( { "input": datasets.Value("string"), "output": datasets.Value("string") } ), "subject": datasets.Value("string"), "language": datasets.Value("string"), "modality": datasets.Value("string") } ) return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, citation=_CITATION, ) def _split_generators(self, dl_manager): subject = self.config.name return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "filepath": dl_manager.download(os.path.join("test", subject+".json")), }, ), datasets.SplitGenerator( name=datasets.Split("val"), gen_kwargs={ "filepath": dl_manager.download(os.path.join("val", subject+".json")), }, ), ] def _generate_examples(self, filepath): with open(filepath, "r") as f: data = json.load(f) for i, instance in enumerate(data): yield i, instance