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62 lines
1.6 KiB
Python
62 lines
1.6 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 GenInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import commonsenseqaDataset
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from opencompass.utils.text_postprocessors import first_capital_postprocess
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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=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=
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"{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\nE. {E}\nAnswer:",
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),
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dict(
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role="BOT",
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prompt="{answerKey}",
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),
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],
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),
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ice_token="</E>",
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)
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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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),
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inferencer=dict(type=GenInferencer),
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)
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commonsenseqa_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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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=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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]
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del _ice_template
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