Description
先决条件
问题类型
我正在使用官方支持的任务/模型/数据集进行评估。
环境
{'CUDA available': True,
'CUDA_HOME': '/usr/local/cuda',
'GCC': 'gcc (GCC) 11.4.1 20231218 (Red Hat 11.4.1-3)',
'GPU 0': 'NVIDIA A100 80GB PCIe',
'MMEngine': '0.10.7',
'MUSA available': False,
'NVCC': 'Cuda compilation tools, release 12.6, V12.6.77',
'OpenCV': '4.11.0',
'PyTorch': '2.6.0+cu124',
'PyTorch compiling details': 'PyTorch built with:\n'
' - GCC 9.3\n'
' - C++ Version: 201703\n'
' - Intel(R) oneAPI Math Kernel Library Version '
'2024.2-Product Build 20240605 for Intel(R) 64 '
'architecture applications\n'
' - Intel(R) MKL-DNN v3.5.3 (Git Hash '
'66f0cb9eb66affd2da3bf5f8d897376f04aae6af)\n'
' - OpenMP 201511 (a.k.a. OpenMP 4.5)\n'
' - LAPACK is enabled (usually provided by '
'MKL)\n'
' - NNPACK is enabled\n'
' - CPU capability usage: AVX512\n'
' - CUDA Runtime 12.4\n'
' - NVCC architecture flags: '
'-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90\n'
' - CuDNN 90.1\n'
' - Magma 2.6.1\n'
' - Build settings: BLAS_INFO=mkl, '
'BUILD_TYPE=Release, '
'COMMIT_SHA=2236df1770800ffea5697b11b0bb0d910b2e59e1, '
'CUDA_VERSION=12.4, CUDNN_VERSION=9.1.0, '
'CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, '
'CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 '
'-fabi-version=11 -fvisibility-inlines-hidden '
'-DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO '
'-DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON '
'-DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK '
'-DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE '
'-O2 -fPIC -Wall -Wextra -Werror=return-type '
'-Werror=non-virtual-dtor -Werror=bool-operation '
'-Wnarrowing -Wno-missing-field-initializers '
'-Wno-type-limits -Wno-array-bounds '
'-Wno-unknown-pragmas -Wno-unused-parameter '
'-Wno-strict-overflow -Wno-strict-aliasing '
'-Wno-stringop-overflow -Wsuggest-override '
'-Wno-psabi -Wno-error=old-style-cast '
'-Wno-missing-braces -fdiagnostics-color=always '
'-faligned-new -Wno-unused-but-set-variable '
'-Wno-maybe-uninitialized -fno-math-errno '
'-fno-trapping-math -Werror=format '
'-Wno-stringop-overflow, LAPACK_INFO=mkl, '
'PERF_WITH_AVX=1, PERF_WITH_AVX2=1, '
'TORCH_VERSION=2.6.0, USE_CUDA=ON, USE_CUDNN=ON, '
'USE_CUSPARSELT=1, USE_EXCEPTION_PTR=1, '
'USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, '
'USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, '
'USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, '
'USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, \n',
'Python': '3.10.16 (main, Dec 11 2024, 16:24:50) [GCC 11.2.0]',
'lmdeploy': "not installed:No module named 'lmdeploy'",
'numpy_random_seed': 2147483648,
'opencompass': '0.4.1+0f46c35',
'sys.platform': 'linux',
'transformers': '4.50.3'}
重现问题 - 代码/配置示例
python run.py --datasets aime2024_0shot_nocot_gen_2b9dc2 --hf-type chat --hf-path /home/kaiyu/cheers/LLMs/qwen2.5-1.5b-instruct --max-out-len 2048 --generation-kwargs do_sample=True temperature=0.7 top_p=0.95
重现问题 - 命令或脚本
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 import Aime2024Dataset, MATHEvaluator, math_postprocess_v2
aime2024_reader_cfg = dict(
input_columns=['question'],
output_column='answer'
)
aime2024_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(role='HUMAN', prompt='{question}\nRemember to put your final answer within \boxed{}.'),
],
)
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=2048)
)
aime2024_eval_cfg = dict(
evaluator=dict(type=MATHEvaluator, version='v2'), pred_postprocessor=dict(type=math_postprocess_v2)
)
aime2024_datasets = [
dict(
abbr='aime2024',
type=Aime2024Dataset,
path='opencompass/aime2024',
k=[1, 4, 8],
n=32,
reader_cfg=aime2024_reader_cfg,
infer_cfg=aime2024_infer_cfg,
eval_cfg=aime2024_eval_cfg
)
]
重现问题 - 错误信息
Traceback (most recent call last):
File "/home/kaiyu/cheers/opencompass/opencompass/tasks/openicl_eval.py", line 481, in
inferencer.run()
File "/home/kaiyu/cheers/opencompass/opencompass/tasks/openicl_eval.py", line 86, in run
self._score()
File "/home/kaiyu/cheers/opencompass/opencompass/tasks/openicl_eval.py", line 245, in _score
result = icl_evaluator.evaluate(k, n, copy.deepcopy(test_set),
File "/home/kaiyu/cheers/opencompass/opencompass/openicl/icl_evaluator/icl_base_evaluator.py", line 161, in evaluate
if can_calculate and n > 1 and k > 1:
TypeError: '>' not supported between instances of 'list' and 'int'
其他信息
我想测试在生成32条回答里，Pass@1，Pass@4，Pass@8的结果，但是这里出现报错。