[Bug] ds1000数据集eval阶段报错

先决条件

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

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 (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0',
'GPU 0,1,2,3,4,5,6,7': 'Tesla V100-PCIE-32GB',
'MMEngine': '0.10.4',
'MUSA available': False,
'NVCC': 'Cuda compilation tools, release 12.1, V12.1.66',
'OpenCV': '4.10.0',
'PyTorch': '2.3.1+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 v3.3.6 (Git Hash '
'86e6af5974177e513fd3fee58425e1063e7f1361)\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 8.7\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 -Wsuggest-override '
'-Wno-psabi -Wno-error=pedantic '
'-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, '
'PERF_WITH_AVX512=1, TORCH_VERSION=2.3.1, '
'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': '3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0]',
'TorchVision': '0.18.1+cu118',
'numpy_random_seed': 2147483648,
'opencompass': '0.2.6+bb0a37d',
'sys.platform': 'linux'}

重现问题 - 代码/配置示例

CUDA_VISIBLE_DEVICES=3 python run.py --datasets ds1000_gen_cbc84f
--hf-type base
--hf-path path_to_Qwen1.5-0.5B
--tokenizer-path path_to_Qwen1.5-0.5B
--tokenizer-kwargs padding_side='left' truncation='left' trust_remote_code=True
--model-kwargs device_map='auto'
--max-seq-len 2048
--max-out-len 100
--min-out-len 100
--batch-size 4
--hf-num-gpus 1

重现问题 - 命令或脚本

CUDA_VISIBLE_DEVICES=3 python run.py --datasets ds1000_gen_cbc84f
--hf-type base
--hf-path path_to_Qwen1.5-0.5B
--tokenizer-path path_to_Qwen1.5-0.5B
--tokenizer-kwargs padding_side='left' truncation='left' trust_remote_code=True
--model-kwargs device_map='auto'
--max-seq-len 2048
--max-out-len 100
--min-out-len 100
--batch-size 4
--hf-num-gpus 1

重现问题 - 错误信息

concurrent.futures.process._RemoteTraceback:
"""
Traceback (most recent call last):
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/process.py", line 246, in _process_worker
r = call_item.fn(*call_item.args, **call_item.kwargs)
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/process.py", line 205, in _process_chunk
return [fn(*args) for args in chunk]
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/process.py", line 205, in
return [fn(*args) for args in chunk]
File "/home/baymax/opencompass/opencompass/datasets/ds1000.py", line 234, in score_single
test_module = import_source_file(tempdir_name / 'test_code.py',
File "/home/baymax/opencompass/opencompass/datasets/ds1000.py", line 342, in import_source_file
spec.loader.exec_module(module)
File "", line 883, in exec_module
File "", line 241, in _call_with_frames_removed
File "/tmp/tmp66d5d5xt/test_code.py", line 3, in
ModuleNotFoundError: No module named 'parser'
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "/home/baymax/opencompass/opencompass/tasks/openicl_eval.py", line 368, in
inferencer.run()
File "/home/baymax/opencompass/opencompass/tasks/openicl_eval.py", line 112, in run
self._score()
File "/home/baymax/opencompass/opencompass/tasks/openicl_eval.py", line 223, in _score
result = icl_evaluator.score(**preds)
File "/home/baymax/opencompass/opencompass/datasets/ds1000.py", line 273, in score
list(executor.map(self.score_single, predictions, references)))
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/process.py", line 575, in _chain_from_iterable_of_lists
for element in iterable:
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/_base.py", line 621, in result_iterator
yield _result_or_cancel(fs.pop())
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/_base.py", line 319, in _result_or_cancel
return fut.result(timeout)
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/_base.py", line 451, in result
return self.__get_result()
File "/root/anaconda3/envs/opencompass/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
raise self._exception
ModuleNotFoundError: No module named 'parser'

其他信息

1. 使用pip install -e .来安装的环境

2. launch OpenICLInfer[Qwen1.5-0.5B_hf/ds1000_Pandas,Qwen1.5-0.5B_hf/ds1000_Numpy,Qwen1.5-0.5B_hf/ds1000_Tensorflow,Qwen1.5-0.5B_hf/ds1000_Scipy,Qwen1.5-0.5B_hf/ds1000_Sklearn,Qwen1.5-0.5B_hf/ds1000_Pytorch,Qwen1.5-0.5B_hf/ds1000_Matplotlib] on GPU 3 阶段是正常的

3. launch OpenICLEval[Qwen1.5-0.5B_hf/ds1000_Matplotlib] on CPU 的时候报错

4. ds1000_Pandas、ds1000_Numpy、ds1000_Scipy、ds1000_Sklearn 都是同样的错误，其他的几个是没有问题的
   dataset version metric mode Qwen1.5-0.5B_hf
   ds1000_Pandas - - - -
   ds1000_Numpy - - - -
   ds1000_Tensorflow 353ae7 accuracy gen 0.00
   ds1000_Scipy - - - -
   ds1000_Sklearn - - - -
   ds1000_Pytorch 353ae7 accuracy gen 0.00
   ds1000_Matplotlib 353ae7 accuracy gen 0.05

5. 请问这个错误和python版本有关系吗？