Repository: open-compass/opencompass
Issue: [Bug] cannot use GPU when conduct evaluation
Root cause: Configuration Error

### Prerequisite

- [X] I have searched [Issues](https://github.com/open-compass/opencompass/issues/) and [Discussions](https://github.com/open-compass/opencompass/discussions) but cannot get the expected help.
- [X] The bug has not been fixed in the [latest version](https://github.com/open-compass/opencompass).

### Type

I have modified the code (config is not considered code), or I'm working on my own tasks/models/datasets.

### Environment

{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda',
 'GCC': 'gcc (GCC) 8.3.1 20191121 (Red Hat 8.3.1-5)',
 'GPU 0,1,2,3,4,5,6,7': 'NVIDIA A100-SXM4-40GB',
 'MMEngine': '0.10.5',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 12.1, V12.1.66',
 'OpenCV': '4.10.0',
 'PyTorch': '2.4.0+cu121',
 '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 v3.4.2 (Git Hash '
                              '1137e04ec0b5251ca2b4400a4fd3c667ce843d67)\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 12.1\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  (built against CUDA 12.4)\n'
                              '  - Magma 2.6.1\n'
                              '  - Build settings: BLAS_INFO=mkl, '
                              'BUILD_TYPE=Release, CUDA_VERSION=12.1, '
                              '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 -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-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=2.4.0, '
                              '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': '0.19.0+cu121',
 'lmdeploy': "not installed:No module named 'lmdeploy'",
 'numpy_random_seed': 2147483648,
 'opencompass': '0.3.7+f333be1',
 'sys.platform': 'linux',
 'transformers': '4.46.3'}

### Reproduces the problem - code/configuration sample

I have integrated the WMT2024 benchmark (https://www2.statmt.org/wmt24/translation-task.html) into the current project. It uses COMET to conduct evaluation, a pre-trained language model that should be run on GPU. COMET can use GPU to calculate scores when "--debug" is set. However, when "--debug" is not set, COMET cannot access to GPU.


### Reproduces the problem - command or script

**can access GPUs when calculating COMET scores:**
CUDA_VISIBLE_DEVICES=0 python run.py \
  --datasets wmt_news_gen \
  --hf-type chat \
  **--debug \**
  --work-dir outputs/test_project \
  --hf-path Llama-3.2-1B-Instruct
**cannot access GPUs when calculating COMET scores:**
CUDA_VISIBLE_DEVICES=0 python run.py \
  --datasets wmt_news_gen \
  --hf-type chat \
  --work-dir outputs/test_project \
  --hf-path Llama-3.2-1B-Instruct

### Reproduces the problem - error message

**can access GPUs when calculating COMET scores:**
Starting inference process...
  0%|                                                                                                                                                                                          | 0/1 [00:00<?, ?it/s]miniconda3/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:590: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.6` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.
  warnings.warn(
/miniconda3/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:595: UserWarning: `do_sample` is set to `False`. However, `top_p` is set to `0.9` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `top_p`.
  warnings.warn(
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:10<00:00, 10.32s/it]
12/12 11:08:01 - OpenCompass - INFO - Partitioned into 1 tasks.
Encoder model frozen.
Lightning automatically upgraded your loaded checkpoint from v1.8.3.post1 to v2.4.0. To apply the upgrade to your files permanently, run `python -m pytorch_lightning.utilities.upgrade_checkpoint ../../original_weights/wmt22-comet-da/checkpoints/model.ckpt`
Encoder model frozen.
/miniconda3/lib/python3.10/site-packages/pytorch_lightning/core/saving.py:195: Found keys that are not in the model state dict but in the checkpoint: ['encoder.model.embeddings.position_ids']
**GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs**
You are using a CUDA device ('NVIDIA A100-SXM4-40GB') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
        - Avoid using `tokenizers` before the fork if possible
        - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
        - Avoid using `tokenizers` before the fork if possible
        - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Predicting DataLoader 0: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  8.55it/s]

**cannot access GPUs when calculating COMET scores:**
**launch OpenICLInfer[Llama-3.2-1B-Instruct_hf/wmt_2024_news_cs-uk] on GPU 0**
12/12 11:51:26 - OpenCompass - INFO - Partitioned into 1 tasks.

  0%|          | 0/1 [00:00<?, ?it/s]
                                     

  0%|          | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [05:10<00:00, 310.83s/it]
100%|██████████| 1/1 [05:10<00:00, 310.83s/it]
**launch OpenICLEval[Llama-3.2-1B-Instruct_hf/wmt_2024_news_cs-uk] on CPU** 
dataset              version    metric                 mode      Llama-3.2-1B-Instruct_hf
-------------------  ---------  ---------------------  ------  --------------------------
wmt_2024_news_cs-uk  15dad7     BLEU                   gen                           0.57
wmt_2024_news_cs-uk  15dad7     CHRF                   gen                          11.89
wmt_2024_news_cs-uk  15dad7     TER                    gen                         350.76
wmt_2024_news_cs-uk  15dad7     wmt22_comet_da         gen                          33.30
wmt_2024_news_cs-uk  15dad7     wmt23_cometkiwi_da_xl  gen                          23.42

### Other information

_No response_