Repository: open-compass/opencompass
Issue: [Bug] 
Root cause: Resource Mishandling

### Prerequisite

- [X] I have searched [Issues](https://github.com/InternLM/opencompass/issues/) and [Discussions](https://github.com/InternLM/opencompass/discussions) but cannot get the expected help.
- [X] The bug has not been fixed in the [latest version](https://github.com/InternLM/opencompass).

### Type

I'm evaluating with the officially supported tasks/models/datasets.

### Environment

{'CUDA available': True,                                                                                                                                                                                          'CUDA_HOME': '/mnt/petrelfs/share/cuda-11.8',                                                                                                                                                                    'GCC': 'gcc (GCC) 7.5.0',                                                                                                                                                                                        'GPU 0,1,2,3,4,5,6,7': 'NVIDIA A100-SXM4-80GB',                                                                                                                                                                  'MMEngine': '0.8.4',                                                                                                                                                                                             'NVCC': 'Cuda compilation tools, release 11.8, V11.8.89',                                                                                                                                                        'OpenCV': '4.8.0',                                                                                                                                                                                               'PyTorch': '2.0.1+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 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 11.8\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;-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 -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=2.0.1, 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': '3.10.11 (main, May 16 2023, 00:28:57) [GCC 11.2.0]',
 'TorchVision': '0.15.2+cu118',
 'numpy_random_seed': 2147483648,
 'opencompass': '0.1.0+',
 'sys.platform': 'linux'}

### Reproduces the problem - code/configuration sample

```python
from mmengine.config import read_base

from opencompass.partitioners import SizePartitioner, NaivePartitioner
from opencompass.runners import LocalRunner, SlurmRunner
from opencompass.tasks import OpenICLInferTask, OpenICLEvalTask
from opencompass.models import HuggingFaceCausalLM

with read_base():
    # from .datasets.alpaca_farm.alpaca_farm_gen_collie_wo_input import alpaca_farm_no_input_datasets
    # from .datasets.alpaca_farm.alpaca_farm_gen_collie_with_input import alpaca_farm_with_input_datasets
    # from .datasets.humaneval.humaneval_gen_collie import humaneval_datasets
    # from .datasets.gsm8k.gsm8k_gen_collie import gsm8k_datasets
    from .datasets.mmlu.mmlu_gen_collie import mmlu_datasets
    from .datasets.bbh.bbh_gen_collie import bbh_datasets

    from .summarizers.groups.mmlu import mmlu_summary_groups
    from .summarizers.groups.bbh import bbh_summary_groups

datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])

models = [
    dict(
        type=HuggingFaceCausalLM,
        abbr='llama-7b',
        path="/mnt/petrelfs/share_data/llm_llama/llama2/llama-2-7b-hf",
        # path="huggyllama/llama-7b",
        tokenizer_path="/mnt/petrelfs/share_data/llm_llama/llama2/llama-2-7b-hf",
        tokenizer_kwargs=dict(padding_side='left',
                              truncation_side='left',
                              use_fast=False,
                              ),
        max_out_len=300,
        max_seq_len=2048,
        batch_size=8,
        model_kwargs=dict(device_map='auto'),
        batch_padding=True,  # if false, inference with for-loop without batch padding
        run_cfg=dict(num_gpus=1, num_procs=1),
    )
]


work_dir = './outputs/llama2-7b/'

infer = dict(
    partitioner=dict(type=SizePartitioner, max_task_size=20000, gen_task_coef=10),
    # partitioner=dict(type='NaivePartitioner'),
    runner=dict(
        type=LocalRunner,
        max_num_workers=8,
        task=dict(type=OpenICLInferTask),
        # retry=5
    ),
)

eval = dict(
    partitioner=dict(type=NaivePartitioner),
    runner=dict(
        type=LocalRunner,
        max_num_workers=8,
        task=dict(type=OpenICLEvalTask),
        # retry=0
    ),
)

summarizer = dict(
    dataset_abbrs = ['mmlu', 'bbh'],
    summary_groups=sum([v for k, v in locals().items() if k.endswith("_summary_groups")], []),
)

# python run.py configs/eval_collie.py -p llm -r -l --debug 2>&1 | tee log.txt
```

### Reproduces the problem - command or script

```shell
python run.py configs/eval_collie.py
```

### Reproduces the problem - error message

RuntimeError: The server socket has failed to listen on any local network address. The server socket has failed to bind to [::]:26500 (errno: 98 - Address already in use). The server socket has failed to bind to 0.0.0.0:26500 (errno: 98 - Address already in use).


### Other information

It seems like the port is already in use. I'm using the Local Runner and wonder if there is any way like `retry` for Slurm Runner?

I found that adding the argument `-r` and running again could solve this problem.