from opencompass.openicl.icl_prompt_template import PromptTemplate from opencompass.openicl.icl_retriever import FixKRetriever from opencompass.openicl.icl_inferencer import PPLInferencer from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.datasets import CMMLUDataset from opencompass.utils.text_postprocessors import first_capital_postprocess cmmlu_subject_mapping = { 'agronomy': '农学', 'anatomy': '解剖学', 'ancient_chinese': '古汉语', 'arts': '艺术学', 'astronomy': '天文学', 'business_ethics': '商业伦理', 'chinese_civil_service_exam': '中国公务员考试', 'chinese_driving_rule': '中国驾驶规则', 'chinese_food_culture': '中国饮食文化', 'chinese_foreign_policy': '中国外交政策', 'chinese_history': '中国历史', 'chinese_literature': '中国文学', 'chinese_teacher_qualification': '中国教师资格', 'clinical_knowledge': '临床知识', 'college_actuarial_science': '大学精算学', 'college_education': '大学教育学', 'college_engineering_hydrology': '大学工程水文学', 'college_law': '大学法律', 'college_mathematics': '大学数学', 'college_medical_statistics': '大学医学统计', 'college_medicine': '大学医学', 'computer_science': '计算机科学', 'computer_security': '计算机安全', 'conceptual_physics': '概念物理学', 'construction_project_management': '建设工程管理', 'economics': '经济学', 'education': '教育学', 'electrical_engineering': '电气工程', 'elementary_chinese': '小学语文', 'elementary_commonsense': '小学常识', 'elementary_information_and_technology': '小学信息技术', 'elementary_mathematics': '初等数学', 'ethnology': '民族学', 'food_science': '食品科学', 'genetics': '遗传学', 'global_facts': '全球事实', 'high_school_biology': '高中生物', 'high_school_chemistry': '高中化学', 'high_school_geography': '高中地理', 'high_school_mathematics': '高中数学', 'high_school_physics': '高中物理学', 'high_school_politics': '高中政治', 'human_sexuality': '人类性行为', 'international_law': '国际法学', 'journalism': '新闻学', 'jurisprudence': '法理学', 'legal_and_moral_basis': '法律与道德基础', 'logical': '逻辑学', 'machine_learning': '机器学习', 'management': '管理学', 'marketing': '市场营销', 'marxist_theory': '马克思主义理论', 'modern_chinese': '现代汉语', 'nutrition': '营养学', 'philosophy': '哲学', 'professional_accounting': '专业会计', 'professional_law': '专业法学', 'professional_medicine': '专业医学', 'professional_psychology': '专业心理学', 'public_relations': '公共关系', 'security_study': '安全研究', 'sociology': '社会学', 'sports_science': '体育学', 'traditional_chinese_medicine': '中医中药', 'virology': '病毒学', 'world_history': '世界历史', 'world_religions': '世界宗教' } cmmlu_all_sets = list(cmmlu_subject_mapping.keys()) cmmlu_datasets = [] for _name in cmmlu_all_sets: _ch_name = cmmlu_subject_mapping[_name] cmmlu_infer_cfg = dict( ice_template=dict( type=PromptTemplate, template={ answer: dict( begin="", round=[ dict( role="HUMAN", prompt=f"以下是关于{_ch_name}的单项选择题,请直接给出正确答案的选项。\n题目:{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}" ), dict(role="BOT", prompt=f'答案是: {answer}'), ]) for answer in ["A", "B", "C", "D"] }, ice_token="", ), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), inferencer=dict(type=PPLInferencer), ) cmmlu_eval_cfg = dict(evaluator=dict(type=AccEvaluator)) cmmlu_datasets.append( dict( type=CMMLUDataset, path="./data/cmmlu/", name=_name, abbr=f"cmmlu-{_name}", reader_cfg=dict( input_columns=["question", "A", "B", "C", "D"], output_column="answer", train_split="dev", test_split='test'), infer_cfg=cmmlu_infer_cfg, eval_cfg=cmmlu_eval_cfg, )) del _name, _ch_name