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46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import MDLRetriever
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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
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_ice_template = dict(
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type=PromptTemplate,
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template={
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'A': "</E>Answer the following question:\n{question}\nAnswer: {A}",
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'B': "</E>Answer the following question:\n{question}\nAnswer: {B}",
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'C': "</E>Answer the following question:\n{question}\nAnswer: {C}",
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'D': "</E>Answer the following question:\n{question}\nAnswer: {D}",
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'E': "</E>Answer the following question:\n{question}\nAnswer: {E}",
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},
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ice_token='</E>')
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commonsenseqa_infer_cfg = dict(
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ice_template=_ice_template,
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retriever=dict(
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type=MDLRetriever,
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ice_num=8,
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candidate_num=30,
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select_time=10,
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seed=1,
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batch_size=12,
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ice_template=_ice_template),
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inferencer=dict(type=PPLInferencer))
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commonsenseqa_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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commonsenseqa_datasets = [
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dict(
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type=commonsenseqaDataset,
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path='commonsense_qa',
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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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infer_cfg=commonsenseqa_infer_cfg,
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eval_cfg=commonsenseqa_eval_cfg)
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]
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del _ice_template
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