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31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
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from mmengine.config import read_base
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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.datasets import MATHDataset, MATHEvaluator, math_postprocess_v2
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with read_base():
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from .math_4shot_example_from_google_research import prompt
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math_reader_cfg = dict(input_columns=['problem'], output_column='solution')
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math_infer_cfg = dict(
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prompt_template=dict(type=PromptTemplate, template=prompt + '\n\nProblem:\n{problem}\nSolution:'),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=1024, stopping_criteria=['Problem']))
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# postprocess v2
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math_eval_cfg = dict(
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evaluator=dict(type=MATHEvaluator, version='v2'),
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pred_postprocessor=dict(type=math_postprocess_v2))
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math_datasets = [
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dict(
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type=MATHDataset,
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abbr='math',
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path='./data/math/math.json',
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reader_cfg=math_reader_cfg,
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infer_cfg=math_infer_cfg,
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eval_cfg=math_eval_cfg)
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]
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