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527a80947b
* fix pip version * fix pip version * add writingbench * add writingbench * add writingbench * add writingbench
70 lines
2.1 KiB
Python
70 lines
2.1 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 WritingBenchDataset, writingbench_postprocess
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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'],
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output_column='judge',
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)
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subjective_all_sets = [
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'writingbench'
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]
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writingbench_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,),
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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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multi_eval=True,
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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begin=[
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dict(
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role='SYSTEM',
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fallback_role='HUMAN',
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prompt='You are an expert evaluator with extensive experience in evaluating response of given query.')
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],
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round=[
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dict(
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role='HUMAN',
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prompt = '{prediction}'
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),
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]),
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),
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dict_postprocessor=dict(type=writingbench_postprocess),
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),
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pred_role='BOT',
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)
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writingbench_datasets.append(
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dict(
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abbr=f'{_name}',
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type=WritingBenchDataset,
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path='./data/subjective/writingbench',
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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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mode='singlescore',
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))
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