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49 lines
1.5 KiB
Python
49 lines
1.5 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 eprstmtDataset_V2
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eprstmt_reader_cfg = dict(
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input_columns=["sentence"], output_column="label", test_split="train")
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eprstmt_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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'内容： "{sentence}"。请对上述内容进行情绪分类。\nA. 积极\nB. 消极\n请从”A“，”B“中进行选择。\n答：'
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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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eprstmt_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"),
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)
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eprstmt_datasets = [
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dict(
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abbr="eprstmt-dev",
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type=eprstmtDataset_V2,
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path="./data/FewCLUE/eprstmt/dev_few_all.json",
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reader_cfg=eprstmt_reader_cfg,
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infer_cfg=eprstmt_infer_cfg,
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eval_cfg=eprstmt_eval_cfg,
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),
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dict(
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abbr="eprstmt-test",
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type=eprstmtDataset_V2,
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path="./data/FewCLUE/eprstmt/test_public.json",
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reader_cfg=eprstmt_reader_cfg,
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infer_cfg=eprstmt_infer_cfg,
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eval_cfg=eprstmt_eval_cfg,
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),
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]
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