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[Bug] 不支持flores200数据集评测
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) 4.8.5 20150623 (Red Hat 4.8.5-44)', 'GPU 0,1,2,3': 'NVIDIA GeForce RTX 3090', 'MMEngine': '0.10.3', 'MUSA available': False, 'NVCC': 'Cuda compilation tools, release 11.0, V11.0.194', 'OpenCV': '4.9.0', 'PyTorch': '2.0.0+cu117', 'PyTorch compiling details': 'PyTorch built with:\n' ' - GCC 9.3\n' ' - C++ Version: 201703\n' ' - Intel(R) oneAPI Math Kernel Library Version ' '2021.4-Product Build 20210904 for Intel(R) 64 ' 'architecture applications\n' ' - Intel(R) MKL-DNN v2.7.3 (Git Hash ' '6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)\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: AVX2\n' ' - CUDA Runtime 11.7\n' ' - NVCC architecture flags: ' '-gencode;arch=compute_37,code=sm_37;-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\n' ' - CuDNN 8.5\n' ' - Magma 2.6.1\n' ' - Build settings: BLAS_INFO=mkl, ' 'BUILD_TYPE=Release, CUDA_VERSION=11.7, ' 'CUDNN_VERSION=8.5.0, ' 'CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, ' 'CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 ' '-fabi-version=11 -Wno-deprecated ' '-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 -Wunused-local-typedefs ' '-Wno-unused-parameter -Wno-unused-function ' '-Wno-unused-result -Wno-strict-overflow ' '-Wno-strict-aliasing ' '-Wno-error=deprecated-declarations ' '-Wno-stringop-overflow -Wno-psabi ' '-Wno-error=pedantic -Wno-error=redundant-decls ' '-Wno-error=old-style-cast ' '-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=2.0.0, 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': '3.8.18 | packaged by conda-forge | (default, Dec 23 2023, ' '17:21:28) [GCC 12.3.0]', 'numpy_random_seed': 2147483648, 'opencompass': '0.2.4+004ed79', 'sys.platform': 'linux'}
重现问题 - 代码/配置示例
python tools/list_configs.py llama3 flores
重现问题 - 命令或脚本
查看当前服务器opencompass支持的llama3 flores200的模型和数据集
重现问题 - 错误信息
其他信息
opencompass的完整数据集里面有flores200数据集,服务器环境已经配置好,但是使用python tools/list_configs.py llama3 flores无法查看支持的flores200数据集
Please try flores_gen_806ede
请尝试
flores_gen_806ede
First of all, thank you for your reply. What are the differences between the following three flores data sets:
flores_gen lores_gen_806ede flores_gen_aad4fd
请尝试
flores_gen_806ede
请问为什么我使用flores200测评,也就是您说的flores_gen_806ede
数据集,为什么在测评的过程中显示的是flores100,如图所示
Apologies for the confusion. We are currently utilizing the flores200
dataset; however, the configuration flores_gen_806ede
mistakenly employs the prompt for flores100
. We will address and rectify this issue promptly.