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46cc7894e1
* [Feature] Support import configs/models/summarizers from whl * Update LCBench configs * Update * Update * Update * Update * update * Update * Update * Update * Update * Update
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
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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commonsenseqa_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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_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=[
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dict(
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role='SYSTEM',
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fallback_role='HUMAN',
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prompt=f'Answer the following question:'), '</E>'
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],
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round=[
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dict(role='HUMAN', prompt='{question}'),
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dict(role='BOT', prompt=ans_token),
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])
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for ans, ans_token in [['A', '{A}'], ['B', '{B}'],
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['C', '{C}'], ['D', '{D}'],
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['E', '{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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abbr='commonsense_qa',
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type=commonsenseqaDataset,
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path='opencompass/commonsense_qa',
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reader_cfg=commonsenseqa_reader_cfg,
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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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