File size: 4,205 Bytes
63fba53 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 | 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 |