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53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import PPLInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import CommonsenseQADataset_CN
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commonsenseqacn_reader_cfg = dict(
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input_columns=['question', 'A', 'B', 'C', 'D', 'E'],
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output_column='answerKey',
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test_split='validation',
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)
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_ice_template = dict(
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type=PromptTemplate,
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template={
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ans: dict(
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begin='</E>',
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round=[
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dict(role='HUMAN', prompt='问题: {question}\n答案: '),
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dict(role='BOT', prompt=ans_token),
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],
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)
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for ans, ans_token in [
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['A', '{A}'],
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['B', '{B}'],
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['C', '{C}'],
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['D', '{D}'],
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['E', '{E}'],
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]
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},
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ice_token='</E>',
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)
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commonsenseqacn_infer_cfg = dict(
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prompt_template=_ice_template,
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=PPLInferencer),
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)
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commonsenseqacn_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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commonsenseqacn_datasets = [
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dict(
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abbr='commonsenseqa_cn',
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type=CommonsenseQADataset_CN,
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path='./data/commonsenseqa_cn/validation.jsonl',
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reader_cfg=commonsenseqacn_reader_cfg,
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infer_cfg=commonsenseqacn_infer_cfg,
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eval_cfg=commonsenseqacn_eval_cfg,
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)
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]
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