OpenCompass/configs/datasets/MedBench/medbench_gen_0b4fff.py

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_IE, MedBenchEvaluator_mcq, 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', 'SafetyBench'] # 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_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_TF), 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_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