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61 lines
1.8 KiB
Python
61 lines
1.8 KiB
Python
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 CreationBenchDataset
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subjective_reader_cfg = dict(
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input_columns=['question', 'capability', 'score_with_ref_prefix', 'score_with_ref_suffix'],
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output_column='judge',
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)
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subjective_all_sets = [
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'creationv2_zh',
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]
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data_path ='data/subjective/'
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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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inferencer=dict(type=GenInferencer, max_seq_len=4096, max_out_len=2048),
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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 = '{score_with_ref_prefix}{prediction}{score_with_ref_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=CreationBenchDataset,
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multi_dimension=True,
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path=data_path,
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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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