42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
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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 AccEvaluator
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from opencompass.datasets import WSCDataset
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WSC_reader_cfg = dict(
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input_columns=["span1", "span2", "text", "new_text"],
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output_column="answer",
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)
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WSC_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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0: dict(round=[
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dict(role="HUMAN", prompt="{text}"),
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]),
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1: dict(round=[
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dict(role="HUMAN", prompt="{new_text}"),
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]),
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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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)
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WSC_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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WSC_datasets = [
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dict(
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type=WSCDataset,
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path="json",
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abbr="WSC",
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data_files="./data/SuperGLUE/WSC/val.jsonl",
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split="train",
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reader_cfg=WSC_reader_cfg,
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infer_cfg=WSC_infer_cfg,
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eval_cfg=WSC_eval_cfg,
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)
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]
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