Repository: open-compass/opencompass
Issue: [Bug] No predictions found
Root cause: Environment Incompatibility

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

### Environment

{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda',
 'GCC': 'gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0',
 'GPU 0': 'NVIDIA RTX A6000',
 'MMEngine': '0.10.5',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 12.2, V12.2.140',
 'OpenCV': '4.10.0',
 'PyTorch': '2.4.1+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: AVX2\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 90.2  (built against CUDA 12.5)\n'
                              '    - Built with CuDNN 90.1\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=2.4.1, '
                              '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': '0.19.1+cu121',
 'lmdeploy': "not installed:No module named 'lmdeploy'",
 'numpy_random_seed': 2147483648,
 'opencompass': '0.3.1+5485207',
 'sys.platform': 'linux',
 'transformers': '4.45.1'}

### Reproduces the problem - code/configuration sample

python run.py configs/eval_api_demo.py

### Reproduces the problem - command or script

python run.py configs/eval_api_demo.py

### Reproduces the problem - error message

Parameter 'function'=<function OpenICLEvalTask._score.<locals>.postprocess at 0x78622515d990> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting and caching to work. If you reuse this transform, the caching mechanism will consider it to be different from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.

Map:   0%|          | 0/64 [00:00<?, ? examples/s]
Map: 100%|██████████| 64/64 [00:00<00:00, 29740.25 examples/s]
09/27 16:10:15 - OpenCompass - ERROR - /home/niwang/code/opencompass/opencompass/tasks/openicl_eval.py - _score - 253 - Task [qwen2-7b-instruct-vllm/demo_gsm8k]: No predictions found.
09/27 16:10:15 - OpenCompass - INFO - time elapsed: 1.40s

### Other information

Parameter 'function'=<function OpenICLEvalTask._score.<locals>.postprocess at 0x78622515d990> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting and caching to work. If you reuse this transform, the caching mechanism will consider it to be different from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.

Map:   0%|          | 0/64 [00:00<?, ? examples/s]
Map: 100%|██████████| 64/64 [00:00<00:00, 29740.25 examples/s]
09/27 16:10:15 - OpenCompass - ERROR - /home/niwang/code/opencompass/opencompass/tasks/openicl_eval.py - _score - 253 - Task [qwen2-7b-instruct-vllm/demo_gsm8k]: No predictions found.
09/27 16:10:15 - OpenCompass - INFO - time elapsed: 1.40s


Please check the outputs folder or use --debug to get more log information

(eval) ➜  opencompass git:(0.3.1) ✗ python run.py configs/eval_api_demo.py --debug
2024-09-27 16:18:43,206 - modelscope - INFO - PyTorch version 2.4.1 Found.
2024-09-27 16:18:43,206 - modelscope - INFO - Loading ast index from /home/niwang/.cache/modelscope/ast_indexer
2024-09-27 16:18:43,222 - modelscope - INFO - Loading done! Current index file version is 1.14.0, with md5 6125c95129253668f1d5845043e06d6e and a total number of 976 components indexed
09/27 16:18:45 - OpenCompass - INFO - Current exp folder: outputs/default/20240927_161845
09/27 16:18:45 - OpenCompass - WARNING - SlurmRunner is not used, so the partition argument is ignored.
09/27 16:18:45 - OpenCompass - INFO - Partitioned into 1 tasks.
09/27 16:18:46 - OpenCompass - INFO - Task [qwen2-7b-instruct-vllm/demo_gsm8k,qwen2-7b-instruct-vllm/demo_math]
Traceback (most recent call last):
  File "/home/niwang/code/opencompass/run.py", line 8, in <module>
    main()
  File "/home/niwang/code/opencompass/opencompass/cli/main.py", line 308, in main
    runner(tasks)
  File "/home/niwang/code/opencompass/opencompass/runners/base.py", line 38, in __call__
    status = self.launch(tasks)
  File "/home/niwang/code/opencompass/opencompass/runners/local.py", line 123, in launch
    task.run(cur_model=getattr(self, 'cur_model',
  File "/home/niwang/code/opencompass/opencompass/tasks/openicl_infer.py", line 73, in run
    self.model = build_model_from_cfg(model_cfg)
  File "/home/niwang/code/opencompass/opencompass/utils/build.py", line 25, in build_model_from_cfg
    return MODELS.build(model_cfg)
  File "/home/niwang/miniconda3/envs/eval/lib/python3.10/site-packages/mmengine/registry/registry.py", line 570, in build
    return self.build_func(cfg, *args, **kwargs, registry=self)
  File "/home/niwang/miniconda3/envs/eval/lib/python3.10/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
    obj = obj_cls(**args)  # type: ignore
  File "/home/niwang/code/opencompass/opencompass/models/vllm_with_tf_above_v4_33.py", line 34, in __init__
    assert LLM, ('Please install VLLM with `pip install vllm`. note: torch==2.1.2 is required.')
AssertionError: Please install VLLM with `pip install vllm`. note: torch==2.1.2 is required.

Hello, I would like to ask if the issue has been resolved. What was the problem, and I am also encountering the same issue.

I have installed vllm==0.8.5, but I still encounter the problem: AssertionError: Please install VLLM with pip install vllm. note: torch==2.1.2 is required. Has anyone fixed it? help!