mirror of
https://github.com/open-compass/opencompass.git
synced 2025-05-30 16:03:24 +08:00
46cc7894e1
* [Feature] Support import configs/models/summarizers from whl * Update LCBench configs * Update * Update * Update * Update * update * Update * Update * Update * Update * Update
60 lines
2.1 KiB
Python
60 lines
2.1 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
|
|
from opencompass.openicl.icl_retriever import ZeroRetriever
|
|
from opencompass.openicl.icl_inferencer import GenInferencer
|
|
from opencompass.datasets.NPHardEval import (
|
|
HardGCPDataset, HardGCPEvaluator,
|
|
Hard_TSP_Dataset, Hard_TSP_Evaluator,
|
|
Hard_MSP_Dataset, Hard_MSP_Evaluator,
|
|
CMP_GCP_D_Dataset, CMP_GCP_D_Evaluator,
|
|
CMP_TSP_D_Dataset, CMP_TSP_D_Evaluator,
|
|
CMP_KSP_Dataset, CMP_KSP_Evaluator,
|
|
P_BSP_Dataset, P_BSP_Evaluator,
|
|
P_EDP_Dataset, P_EDP_Evaluator,
|
|
P_SPP_Dataset, P_SPP_Evaluator,
|
|
)
|
|
|
|
NPHardEval_tasks = [
|
|
['hard_GCP', 'GCP', HardGCPDataset, HardGCPEvaluator],
|
|
['hard_TSP', 'TSP', Hard_TSP_Dataset, Hard_TSP_Evaluator],
|
|
['hard_MSP', 'MSP', Hard_MSP_Dataset, Hard_MSP_Evaluator],
|
|
['cmp_GCP_D', 'GCP_Decision', CMP_GCP_D_Dataset, CMP_GCP_D_Evaluator],
|
|
['cmp_TSP_D', 'TSP_Decision', CMP_TSP_D_Dataset, CMP_TSP_D_Evaluator],
|
|
['cmp_KSP', 'KSP', CMP_KSP_Dataset, CMP_KSP_Evaluator],
|
|
['p_BSP', 'BSP', P_BSP_Dataset, P_BSP_Evaluator],
|
|
['p_EDP', 'EDP', P_EDP_Dataset, P_EDP_Evaluator],
|
|
['p_SPP', 'SPP', P_SPP_Dataset, P_SPP_Evaluator],
|
|
]
|
|
|
|
NPHardEval_datasets = []
|
|
for name, path_name, dataset, evaluator in NPHardEval_tasks:
|
|
NPHardEval_reader_cfg = dict(input_columns=['prompt', 'level'], output_column='q')
|
|
|
|
NPHardEval_infer_cfg = dict(
|
|
ice_template=dict(
|
|
type=PromptTemplate,
|
|
template=dict(
|
|
begin='</E>',
|
|
round=[
|
|
dict(role='HUMAN', prompt='</E>{prompt}'),
|
|
dict(role='BOT', prompt=''),
|
|
],
|
|
),
|
|
ice_token='</E>',
|
|
),
|
|
retriever=dict(type=ZeroRetriever),
|
|
inferencer=dict(type=GenInferencer),
|
|
)
|
|
|
|
NPHardEval_eval_cfg = dict(evaluator=dict(type=evaluator), pred_role='BOT')
|
|
|
|
NPHardEval_datasets.append(
|
|
dict(
|
|
type=dataset,
|
|
abbr=name,
|
|
path=f'./data/NPHardEval/{path_name}/',
|
|
reader_cfg=NPHardEval_reader_cfg,
|
|
infer_cfg=NPHardEval_infer_cfg,
|
|
eval_cfg=NPHardEval_eval_cfg,
|
|
)
|
|
)
|