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55 lines
1.8 KiB
Python
55 lines
1.8 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 PPLInferencer
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from opencompass.openicl.icl_evaluator import AccContaminationEvaluator
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from opencompass.datasets import ARCDatasetClean as ARCDataset
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ARC_c_reader_cfg = dict(
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input_columns=['question', 'textA', 'textB', 'textC', 'textD'],
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output_column='answerKey')
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ARC_c_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template={
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'A':
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dict(
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round=[
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dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
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dict(role='BOT', prompt='{textA}')
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], ),
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'B':
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dict(
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round=[
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dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
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dict(role='BOT', prompt='{textB}')
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], ),
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'C':
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dict(
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round=[
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dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
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dict(role='BOT', prompt='{textC}')
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], ),
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'D':
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dict(
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round=[
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dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
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dict(role='BOT', prompt='{textD}')
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], ),
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}),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=PPLInferencer))
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ARC_c_eval_cfg = dict(evaluator=dict(type=AccContaminationEvaluator),
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analyze_contamination=True)
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ARC_c_datasets = [
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dict(
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type=ARCDataset,
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abbr='ARC-c-test',
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path='./data/ARC/ARC-c/ARC-Challenge-Test.jsonl',
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reader_cfg=ARC_c_reader_cfg,
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infer_cfg=ARC_c_infer_cfg,
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eval_cfg=ARC_c_eval_cfg)
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]
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