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51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
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 GenInferencer
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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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from opencompass.utils.text_postprocessors import first_capital_postprocess
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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=dict(
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begin='</E>',
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round=[
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dict(
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role='HUMAN',
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prompt='{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\nE. {E}\n答案：',
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),
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dict(role='BOT', prompt='{answerKey}'),
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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=GenInferencer),
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)
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commonsenseqacn_eval_cfg = dict(
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evaluator=dict(type=AccEvaluator),
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pred_postprocessor=dict(type=first_capital_postprocess),
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)
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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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