from utils import ( Medbullets_op4, Medbullets_op5, MedXpertQA, MMMU, OmniMedVQA, PATH_VQA, PMC_VQA, SLAKE, SuperGPQA, VQA_RAD, HealthBench, PubMedQA, MedMCQA, MedQA_USMLE, MMLU, CMB, CMExam, MedQA_MCMLE, CMMLU, IU_XRAY, CheXpert_Plus, MIMIC_CXR, MedFrameQA, Radrestruct, ) #eval_MedQA_USMLE def prepare_benchmark(model,eval_dataset,eval_dataset_path,eval_output_path): # Hallu,Geometry3k supported_dataset = ["MMMU-Medical-test","MMMU-Medical-val","PATH_VQA","PMC_VQA","VQA_RAD","SLAKE","MedQA_USMLE","MedMCQA","PubMedQA","OmniMedVQA","Medbullets_op4","Medbullets_op5","MedXpertQA-Text","MedXpertQA-MM","SuperGPQA""HealthBench","IU_XRAY","CheXpert_Plus","MIMIC_CXR","CMB","CMExam","CMMLU","MedQA_MCMLE","MedFrameQA"] if eval_dataset in ["MMMU-Medical-test", "MMMU-Medical-val"]: if eval_dataset_path: eval_dataset_path = eval_dataset_path.replace(eval_dataset,"MMMU") _ , subset , split = eval_dataset.split("-") dataset = MMMU(model,eval_dataset_path,eval_output_path,split,subset) elif eval_dataset == "PATH_VQA": dataset = PATH_VQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "PMC_VQA": dataset = PMC_VQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "VQA_RAD": dataset = VQA_RAD(model,eval_dataset_path,eval_output_path) elif eval_dataset == "SLAKE": dataset = SLAKE(model,eval_dataset_path,eval_output_path) elif eval_dataset == "OmniMedVQA": dataset = OmniMedVQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "Medbullets_op4": dataset = Medbullets_op4(model,eval_dataset_path,eval_output_path) elif eval_dataset == "Medbullets_op5": dataset = Medbullets_op5(model,eval_dataset_path,eval_output_path) elif eval_dataset in ["MedXpertQA-Text","MedXpertQA-MM"]: if eval_dataset_path: eval_dataset_path = eval_dataset_path.replace(eval_dataset,"MedXpertQA") _,split = eval_dataset.split("-") dataset = MedXpertQA(model,eval_dataset_path,eval_output_path,split) elif eval_dataset == "SuperGPQA": dataset = SuperGPQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "HealthBench": dataset =HealthBench(model,eval_dataset_path,eval_output_path) elif eval_dataset == "PubMedQA": dataset = PubMedQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "MedMCQA": dataset = MedMCQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "MedQA_USMLE": dataset = MedQA_USMLE(model,eval_dataset_path,eval_output_path) elif eval_dataset in ["MMLU-medical","MMLU-all"]: if eval_dataset_path: eval_dataset_path = eval_dataset_path.replace(eval_dataset,"MMLU") _,subject = eval_dataset.split("-") dataset = MMLU(model,eval_dataset_path,eval_output_path,subject) elif eval_dataset == "CMB": dataset = CMB(model,eval_dataset_path,eval_output_path) elif eval_dataset == "CMExam": dataset = CMExam(model,eval_dataset_path,eval_output_path) elif eval_dataset == "MedQA_MCMLE": dataset = MedQA_MCMLE(model,eval_dataset_path,eval_output_path) elif eval_dataset == "CMMLU": dataset = CMMLU(model,eval_dataset_path,eval_output_path) elif eval_dataset == "IU_XRAY": dataset = IU_XRAY(model,eval_dataset_path,eval_output_path) elif eval_dataset == "CheXpert_Plus": dataset = CheXpert_Plus(model,eval_dataset_path,eval_output_path) elif eval_dataset == "MIMIC_CXR": dataset = MIMIC_CXR(model,eval_dataset_path,eval_output_path) elif eval_dataset == "MedFrameQA": dataset = MedFrameQA(model,eval_dataset_path,eval_output_path) elif eval_dataset == "Radrestruct": dataset = Radrestruct(model,eval_dataset_path,eval_output_path) else: print(f"unknown eval dataset {eval_dataset}, we only support {supported_dataset}") dataset = None return dataset if __name__ == '__main__': pass