OpenCompass/examples/eval_math_llm_judge_internal.py
Linchen Xiao a6193b4c02
[Refactor] Code refactoarization (#1831)
* Update

* fix lint

* update

* fix lint
2025-01-20 19:17:38 +08:00

44 lines
1.6 KiB
Python

from mmengine.config import read_base
with read_base():
from opencompass.configs.datasets.math.math_0shot_llm_judge_v2_gen_31d777 import \
math_datasets
# 选择一个感兴趣的模型
from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_72b_instruct import \
models as qwen2_5_72b_instruct_model
eval_model_name = 'eval_model_name'
postprocessor_model_name = 'postprocessor_model_name'
eval_model_urls = ['http://0.0.0.0:23333/v1']
postprocessor_model_urls = ['http://0.0.0.0:23333/v1']
datasets = sum([v for k, v in locals().items() if k.endswith('_datasets')], [])
models = sum([v for k, v in locals().items() if k.endswith('_model')], [])
for dataset in datasets:
dataset['eval_cfg']['evaluator']['model_name'] = eval_model_name
dataset['eval_cfg']['evaluator']['url'] = eval_model_urls
dataset['eval_cfg']['evaluator']['post_url'] = postprocessor_model_urls
dataset['eval_cfg']['evaluator'][
'post_model_name'] = postprocessor_model_name
# -------------Inferen Stage ----------------------------------------
from opencompass.partitioners import NaivePartitioner, NumWorkerPartitioner
from opencompass.runners import LocalRunner
from opencompass.tasks import OpenICLEvalTask, OpenICLInferTask
infer = dict(
partitioner=dict(type=NumWorkerPartitioner, num_worker=8),
runner=dict(type=LocalRunner,
max_num_workers=8,
task=dict(type=OpenICLInferTask)),
)
eval = dict(
partitioner=dict(type=NaivePartitioner, n=10),
runner=dict(type=LocalRunner,
max_num_workers=256,
task=dict(type=OpenICLEvalTask)),
)