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39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import FixKRetriever
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from opencompass.openicl.icl_inferencer import LLInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import winograndeDataset_V3
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winogrande_reader_cfg = dict(
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input_columns=['opt1', 'opt2'],
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output_column='answer',
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train_split="train_xs",
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test_split="dev",
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)
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question_and_options = "Which of the following is a good sentence:\nA. {opt1}\nB. {opt2}"
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winogrande_infer_cfg = dict(
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ice_template=dict(
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type=PromptTemplate,
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template={answer: f"{question_and_options}\nAnswer: {answer}\n" for answer in ["A", "B"]},
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),
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prompt_template=dict(
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type=PromptTemplate,
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template={answer: f"</E>{question_and_options}\nAnswer: {answer}" for answer in ["A", "B"]},
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ice_token="</E>",
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),
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retriever=dict(type=FixKRetriever, fix_id_list=[0, 2, 4, 6, 8]),
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inferencer=dict(type=LLInferencer),
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)
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winogrande_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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winogrande_datasets = [
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dict(
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abbr='winogrande',
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type=winograndeDataset_V3,
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path='./data/winogrande',
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reader_cfg=winogrande_reader_cfg,
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infer_cfg=winogrande_infer_cfg,
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eval_cfg=winogrande_eval_cfg)
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]
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