运行评测结果为空[Bug]

[badmic]

先决条件

• [X] 我已经搜索过 问题 和 讨论 但未得到预期的帮助。
• [X] 错误在 最新版本 中尚未被修复。

问题类型

我修改了代码（配置不视为代码），或者我正在处理我自己的任务/模型/数据集。

环境

{'CUDA available': True, 'CUDA_HOME': '/usr/local/cuda', 'GCC': 'gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0', 'GPU 0,1,2,3,4,5,6,7': 'NVIDIA A800-SXM4-80GB', 'MMEngine': '0.10.4', 'MUSA available': False, 'NVCC': 'Cuda compilation tools, release 11.8, V11.8.89', 'OpenCV': '4.9.0', 'PyTorch': '2.1.2+cu118', 'PyTorch compiling details': 'PyTorch built with:\n' ' - GCC 9.3\n' ' - C++ Version: 201703\n' ' - Intel(R) oneAPI Math Kernel Library Version ' '2022.2-Product Build 20220804 for Intel(R) 64 ' 'architecture applications\n' ' - Intel(R) MKL-DNN v3.1.1 (Git Hash ' '64f6bcbcbab628e96f33a62c3e975f8535a7bde4)\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 11.8\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_37,code=sm_37;-gencode;arch=compute_90,code=sm_90\n' ' - CuDNN 8.9.6\n' ' - Built with CuDNN 8.7\n' ' - Magma 2.6.1\n' ' - Build settings: BLAS_INFO=mkl, ' 'BUILD_TYPE=Release, CUDA_VERSION=11.8, ' 'CUDNN_VERSION=8.7.0, ' '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 -DUSE_FBGEMM ' '-DUSE_QNNPACK -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-unused-function -Wno-unused-result ' '-Wno-strict-overflow -Wno-strict-aliasing ' '-Wno-stringop-overflow -Wno-psabi ' '-Wno-error=pedantic -Wno-error=old-style-cast ' '-Wno-invalid-partial-specialization ' '-Wno-unused-private-field ' '-Wno-aligned-allocation-unavailable ' '-Wno-missing-braces -fdiagnostics-color=always ' '-faligned-new -Wno-unused-but-set-variable ' '-Wno-maybe-uninitialized -fno-math-errno ' '-fno-trapping-math -Werror=format ' '-Werror=cast-function-type ' '-Wno-stringop-overflow, LAPACK_INFO=mkl, ' 'PERF_WITH_AVX=1, PERF_WITH_AVX2=1, ' 'PERF_WITH_AVX512=1, ' 'TORCH_DISABLE_GPU_ASSERTS=ON, ' 'TORCH_VERSION=2.1.2, USE_CUDA=ON, USE_CUDNN=ON, ' 'USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, ' 'USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, ' 'USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, ' 'USE_OPENMP=ON, USE_ROCM=OFF, \n', 'Python': '3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]', 'TorchVision': '0.16.2+cu118', 'numpy_random_seed': 2147483648, 'opencompass': '0.2.4+94eb905', 'sys.platform': 'linux'}

重现问题 - 代码/配置示例

运行python run.py --models csg-wukong-code-1B-cpt --datasets medbench 出现错误，报错文档为：

配置文件为：

最后跑出来的结果为空：

重现问题 - 命令或脚本

如上

重现问题 - 错误信息

如上

其他信息

No response

[yaolu-zjut]

我也遇到了同样的问题，请问你解决了吗，我就跑了官方源代码：python run.py --datasets ceval_ppl mmlu_ppl --hf-type base --hf-path /public/MountData/yaolu/LLM_pretrained/LLAMA2_7B，只是把路径换成了本地的llama

[goosey-geo]

使用最新版本的 open-compass ，并在官方命令行后添加 --debug 参数，会在 ./tmp/ 路径下生成 *_debug.log 文件。 我的报错是 Error: mkl-service + Intel(R) MKL: MKL_THREADING_LAYER=INTEL is incompatible with libgomp.so.1 library. Try to import numpy first or set the threading layer accordingly. Set MKL_SERVICE_FORCE_INTEL to force it. 下面是对应的解决方法 https://github.com/pytorch/pytorch/issues/37377 即 export MKL_THREADING_LAYER=GNU 另外，此 bug 似乎是 import 顺序导致的。官方可以解决一下吗？

[ppalantir]

export MKL_THREADING_LAYER=GNU

Hi @goosey-geo Thanks for sharing the information. I try to use export MKL_THREADING_LAYER=GNU, but I get stucked in waiting" 0%| | 0/1 [00:00<?, ?it/s]". Have you solved the issues?

[goosey-geo]

Hello there @ppalantir I do not have this problem, here is my advise, wait for a little longer, use the --debug param to see log file or check out the 'outputs/predictions' file to see if there has a predict result.