2023-12-11 22:22:11 +08:00
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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 LMEvaluator
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from opencompass.datasets import Creationv01Dataset
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from mmengine.config import read_base
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subjective_reader_cfg = dict(
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input_columns=['question', 'prefix', 'suffix'],
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output_column='judge',
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)
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subjective_all_sets = [
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"creation_v0.1",
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]
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subjective_datasets = []
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for _name in subjective_all_sets:
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subjective_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="{question}"
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),
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]),
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),
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retriever=dict(type=ZeroRetriever),
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2023-12-20 00:00:28 +08:00
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inferencer=dict(type=GenInferencer, max_out_len=1024),
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2023-12-11 22:22:11 +08:00
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)
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subjective_eval_cfg = dict(
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evaluator=dict(
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type=LMEvaluator,
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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 = "{prefix}问题: <问题开始> {question} <问题结束>\n\n回答: <回答开始> {prediction} <回答结束>\n\n{suffix}"
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),
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]),
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),
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),
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pred_role="BOT",
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)
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subjective_datasets.append(
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dict(
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abbr=f"{_name}",
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type=Creationv01Dataset,
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path="./data/subjective/",
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name=_name,
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reader_cfg=subjective_reader_cfg,
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infer_cfg=subjective_infer_cfg,
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eval_cfg=subjective_eval_cfg
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))
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