from opencompass.openicl.icl_prompt_template import PromptTemplate from opencompass.openicl.icl_retriever import ZeroRetriever from opencompass.openicl.icl_inferencer import GenInferencer from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.datasets import MedBenchDataset, MedBenchEvaluator, MedBenchEvaluator_Cloze, MedBenchEvaluator_CMeEE, MedBenchEvaluator_CMeIE, MedBenchEvaluator_CHIP_CDEE, MedBenchEvaluator_CHIP_CDN, MedBenchEvaluator_CHIP_CTC, MedBenchEvaluator_NLG, MedBenchEvaluator_TF, MedBenchEvaluator_DBMHG, MedBenchEvaluator_SMDoc, MedBenchEvaluator_IMCS_V2_MRG from opencompass.utils.text_postprocessors import first_capital_postprocess medbench_reader_cfg = dict( input_columns=['problem_input'], output_column='label') medbench_multiple_choices_sets = ['Med-Exam', 'DDx-basic', 'DDx-advanced', 'MedSafety'] # 选择题,用acc判断 medbench_qa_sets = ['MedHC', 'MedMC', 'MedDG', 'MedSpeQA', 'MedTreat', 'CMB-Clin'] # 开放式QA,有标答 medbench_cloze_sets = ['MedHG'] # 限定域QA,有标答 medbench_single_choice_sets = ['DrugCA'] # 正确与否判断,有标答 medbench_ie_sets = ['DBMHG', 'CMeEE', 'CMeIE', 'CHIP-CDEE', 'CHIP-CDN', 'CHIP-CTC', 'SMDoc', 'IMCS-V2-MRG'] # 判断识别的实体是否一致,用F1评价 medbench_datasets = [] for name in medbench_single_choice_sets + medbench_multiple_choices_sets: medbench_infer_cfg = dict( prompt_template=dict( type=PromptTemplate, template=dict( round=[dict(role="HUMAN", prompt='{problem_input}')])), retriever=dict(type=ZeroRetriever ), # retriver 不起作用,以输入参数为准 (zero-shot / few-shot) inferencer=dict(type=GenInferencer)) medbench_eval_cfg = dict( evaluator=dict(type=MedBenchEvaluator), pred_role="BOT") medbench_datasets.append( dict( type=MedBenchDataset, path='./data/MedBench/' + name, name=name, abbr='medbench-' + name, setting_name='zero-shot', reader_cfg=medbench_reader_cfg, infer_cfg=medbench_infer_cfg.copy(), eval_cfg=medbench_eval_cfg.copy())) for name in medbench_qa_sets: medbench_infer_cfg = dict( prompt_template=dict( type=PromptTemplate, template=dict( round=[dict(role="HUMAN", prompt='{problem_input}')])), retriever=dict(type=ZeroRetriever ), # retriver 不起作用,以输入参数为准 (zero-shot / few-shot) inferencer=dict(type=GenInferencer)) medbench_eval_cfg = dict( evaluator=dict(type=MedBenchEvaluator_NLG), pred_role="BOT") medbench_datasets.append( dict( type=MedBenchDataset, path='./data/MedBench/' + name, name=name, abbr='medbench-' + name, setting_name='zero-shot', reader_cfg=medbench_reader_cfg, infer_cfg=medbench_infer_cfg.copy(), eval_cfg=medbench_eval_cfg.copy())) for name in medbench_cloze_sets: medbench_infer_cfg = dict( prompt_template=dict( type=PromptTemplate, template=dict( round=[dict(role="HUMAN", prompt='{problem_input}')])), retriever=dict(type=ZeroRetriever ), # retriver 不起作用,以输入参数为准 (zero-shot / few-shot) inferencer=dict(type=GenInferencer)) medbench_eval_cfg = dict( evaluator=dict(type=MedBenchEvaluator_Cloze), pred_role="BOT") medbench_datasets.append( dict( type=MedBenchDataset, path='./data/MedBench/' + name, name=name, abbr='medbench-' + name, setting_name='zero-shot', reader_cfg=medbench_reader_cfg, infer_cfg=medbench_infer_cfg.copy(), eval_cfg=medbench_eval_cfg.copy())) for name in medbench_ie_sets: medbench_infer_cfg = dict( prompt_template=dict( type=PromptTemplate, template=dict( round=[dict(role="HUMAN", prompt='{problem_input}')])), retriever=dict(type=ZeroRetriever ), # retriver 不起作用,以输入参数为准 (zero-shot / few-shot) inferencer=dict(type=GenInferencer)) medbench_eval_cfg = dict( evaluator=dict(type=eval('MedBenchEvaluator_'+name.replace('-', '_'))), pred_role="BOT") medbench_datasets.append( dict( type=MedBenchDataset, path='./data/MedBench/' + name, name=name, abbr='medbench-' + name, setting_name='zero-shot', reader_cfg=medbench_reader_cfg, infer_cfg=medbench_infer_cfg.copy(), eval_cfg=medbench_eval_cfg.copy())) del name, medbench_infer_cfg, medbench_eval_cfg