[Bug] SUPERGLUE-RTE评测任务无反应

[shedding-ash]

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

/home/liushizhuo/github/opencompass/opencompass/__init__.py:19: UserWarning: Starting from v0.4.0, all AMOTIC configuration files currently located in `./configs/datasets`, `./configs/models`, and `./configs/summarizers` will be migrated to the `opencompass/configs/` package. Please update your configuration file paths accordingly.
  _warn_about_config_migration()
{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda',
 'GCC': 'gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0',
 'GPU 0,1,2,3': 'NVIDIA GeForce RTX 3090',
 'MMEngine': '0.10.5',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 12.1, V12.1.105',
 'OpenCV': '4.10.0',
 'PyTorch': '2.5.1+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, 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=2.5.1, 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': '3.10.16 | packaged by conda-forge | (main, Dec  5 2024, 14:16:10) '
           '[GCC 13.3.0]',
 'TorchVision': '0.20.1+cu124',
 'lmdeploy': '0.6.5',
 'numpy_random_seed': 2147483648,
 'opencompass': '0.3.7+aeded4c',
 'sys.platform': 'linux',
 'transformers': '4.47.0'}

重现问题 - 代码/配置示例

python run.py configs/myeval.py 

# configs/myeval.py
from mmengine.config import read_base

with read_base():
    # 直接从预设数据集配置中读取需要的数据集配置
    from .datasets.piqa.piqa_ppl import piqa_datasets
    from .datasets.siqa.siqa_gen import siqa_datasets
    from .datasets.SuperGLUE_RTE.SuperGLUE_RTE_gen import RTE_datasets

# 将需要评测的数据集拼接成 datasets 字段
datasets = [*RTE_datasets]

path = '/home/liushizhuo/model/8B-lora-RTE'
# 使用 HuggingFaceCausalLM 评测 HuggingFace 中 AutoModelForCausalLM 支持的模型
from opencompass.models import HuggingFaceCausalLM

models = [
    dict(
        type=HuggingFaceCausalLM,
        # 以下参数为 HuggingFaceCausalLM 的初始化参数
        path=path,
        tokenizer_path=path,
        tokenizer_kwargs=dict(padding_side='left', truncation_side='left'),
        max_seq_len=2048,
        # 以下参数为各类模型都必须设定的参数，非 HuggingFaceCausalLM 的初始化参数
        abbr='llama-7b',            # 模型简称，用于结果展示
        max_out_len=100,            # 最长生成 token 数
        batch_size=100,              # 批次大小
        run_cfg=dict(num_gpus=4),   # 运行配置，用于指定资源需求
    )
]

重现问题 - 命令或脚本

python run.py configs/myeval.py

#config/myeval.py
from mmengine.config import read_base

with read_base():
    # 直接从预设数据集配置中读取需要的数据集配置
    from .datasets.piqa.piqa_ppl import piqa_datasets
    from .datasets.siqa.siqa_gen import siqa_datasets
    from .datasets.SuperGLUE_RTE.SuperGLUE_RTE_gen import RTE_datasets

# 将需要评测的数据集拼接成 datasets 字段
datasets = [*RTE_datasets]

path = '/home/liushizhuo/model/8B-lora-RTE'
# 使用 HuggingFaceCausalLM 评测 HuggingFace 中 AutoModelForCausalLM 支持的模型
from opencompass.models import HuggingFaceCausalLM

models = [
    dict(
        type=HuggingFaceCausalLM,
        # 以下参数为 HuggingFaceCausalLM 的初始化参数
        path=path,
        tokenizer_path=path,
        tokenizer_kwargs=dict(padding_side='left', truncation_side='left'),
        max_seq_len=2048,
        # 以下参数为各类模型都必须设定的参数，非 HuggingFaceCausalLM 的初始化参数
        abbr='llama-7b',            # 模型简称，用于结果展示
        max_out_len=100,            # 最长生成 token 数
        batch_size=100,              # 批次大小
        run_cfg=dict(num_gpus=4),   # 运行配置，用于指定资源需求
    )
]

重现问题 - 错误信息

没有生成日志文件 ，对应的文件夹中只有一个configs/20250104_211303_2969749.py文件

命令行卡在01/04 21:13:03 - OpenCompass - INFO - Partitioned into 1 tasks.
0%| | 0/1 [00:00<?, ?it/s]

没有生成进程运行在显卡

其他信息

No response