44 lines
1.2 KiB
Python
44 lines
1.2 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 GenInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import WSCDataset_V2
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from opencompass.utils.text_postprocessors import first_capital_postprocess
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WSC_reader_cfg = dict(
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input_columns=["span1", "span2", "text"],
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output_column="label",
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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=dict(round=[
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dict(
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role="HUMAN",
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prompt=
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"{text}\nIs '{span1}' and '{span2}' refers to the same entity in the above sentence?\nA. Yes\nB. No\nAnseer:"
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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=GenInferencer),
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)
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WSC_eval_cfg = dict(
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evaluator=dict(type=AccEvaluator),
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pred_role="BOT",
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pred_postprocessor=dict(type=first_capital_postprocess),
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)
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WSC_datasets = [
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dict(
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abbr="WSC",
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type=WSCDataset_V2,
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path="./data/SuperGLUE/WSC/val.jsonl",
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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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