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* [Feature] Support import configs/models/summarizers from whl * Update LCBench configs * Update * Update * Update * Update * update * Update * Update * Update * Update * Update
45 lines
1.7 KiB
Python
45 lines
1.7 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 AttackInferencer
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from opencompass.datasets import MATHDataset, MATHEvaluator, math_postprocess
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math_reader_cfg = dict(input_columns=['problem'], output_column='solution')
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original_prompt_list = [
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'Solve the following math question about',
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'Determine the solution to this mathematical problem related to',
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'Calculate the answer to the following math query about',
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'Find the solution for this mathematical challenge with',
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'Compute the result of this math task concerning',
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'Resolve the following mathematical question associated with',
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'Work out the answer to this math problem featuring',
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'Figure out the solution for the following mathematical task with',
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'Obtain the result for this math question regarding',
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'Evaluate the following mathematical problem that includes',
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]
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math_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='{adv_prompt} {problem}:'),
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]),
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=AttackInferencer, original_prompt_list=original_prompt_list,max_out_len=512, adv_key='adv_prompt'))
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math_eval_cfg = dict(
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evaluator=dict(type=MATHEvaluator), pred_postprocessor=dict(type=math_postprocess))
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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='opencompass/math',
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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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