45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
|
|
from opencompass.openicl.icl_retriever import ZeroRetriever
|
|
from opencompass.openicl.icl_inferencer import AttackInferencer
|
|
from opencompass.datasets import MATHDataset, MATHEvaluator, math_postprocess
|
|
|
|
math_reader_cfg = dict(input_columns=['problem'], output_column='solution')
|
|
|
|
original_prompt_list = [
|
|
"Solve the following math question about",
|
|
"Determine the solution to this mathematical problem related to",
|
|
"Calculate the answer to the following math query about",
|
|
"Find the solution for this mathematical challenge with",
|
|
"Compute the result of this math task concerning",
|
|
"Resolve the following mathematical question associated with",
|
|
"Work out the answer to this math problem featuring",
|
|
"Figure out the solution for the following mathematical task with",
|
|
"Obtain the result for this math question regarding",
|
|
"Evaluate the following mathematical problem that includes",
|
|
]
|
|
|
|
math_infer_cfg = dict(
|
|
prompt_template=dict(
|
|
type=PromptTemplate,
|
|
template=dict(round=[
|
|
dict(
|
|
role="HUMAN",
|
|
prompt="{adv_prompt} {problem}:"),
|
|
]),
|
|
),
|
|
retriever=dict(type=ZeroRetriever),
|
|
inferencer=dict(type=AttackInferencer, original_prompt_list=original_prompt_list,max_out_len=512, adv_key='adv_prompt'))
|
|
|
|
math_eval_cfg = dict(
|
|
evaluator=dict(type=MATHEvaluator), pred_postprocessor=dict(type=math_postprocess))
|
|
|
|
math_datasets = [
|
|
dict(
|
|
type=MATHDataset,
|
|
abbr='math',
|
|
path='./data/math/math.json',
|
|
reader_cfg=math_reader_cfg,
|
|
infer_cfg=math_infer_cfg,
|
|
eval_cfg=math_eval_cfg)
|
|
]
|