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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