Repository: open-compass/opencompass
Issue: [Bug] 在对DeepSeek-R1-Distill-Qwen-1.5B模型评测livecodebench数据集时，lcb_test_output为什么为0呢？
Root cause: External Dependency Breakage

### 先决条件

- [x] 我已经搜索过 [问题](https://github.com/open-compass/opencompass/issues/) 和 [讨论](https://github.com/open-compass/opencompass/discussions) 但未得到预期的帮助。
- [x] 错误在 [最新版本](https://github.com/open-compass/opencompass) 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-11.8',
 'GCC': 'gcc (Ubuntu 11.4.0-2ubuntu1~20.04) 11.4.0',
 'GPU 0': 'NVIDIA GeForce RTX 3090',
 'MMEngine': '0.10.5',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 11.8, V11.8.89',
 '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: AVX2\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': '3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0]',
 'TorchVision': '0.20.1+cu124',
 'lmdeploy': "not installed:No module named 'lmdeploy'",
 'numpy_random_seed': 2147483648,
 'opencompass': '0.3.9+7f2aeef',
 'sys.platform': 'linux',
 'transformers': '4.46.3'}

### 重现问题 - 代码/配置示例

```
在vllm_qwen2_5_1_5b_instruct.py里面修改代码如下：
from opencompass.models import VLLMwithChatTemplate

models = [
    dict(
        type=VLLMwithChatTemplate,
        # abbr='qwen2.5-1.5b-instruct-vllm',
        abbr='DeepSeek-R1-Distill-Qwen-1.5B',
        path='/home/lyg/Pth/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B',
        # path='/home/lyg/Pth/Qwen/Qwen2.5-Math-1.5B',
        model_kwargs=dict(tensor_parallel_size=1, gpu_memory_utilization=0.8),
        # max_out_len=4096,
        max_out_len=32768,
        batch_size=16,
        generation_kwargs=dict(temperature=0.6, top_p=0.95),
        run_cfg=dict(num_gpus=1),
    )
]
```

### 重现问题 - 命令或脚本

python run.py --models vllm_qwen2_5_1_5b_instruct --datasets gpqa_gen_4baadb livecodebench_gen

### 重现问题 - 错误信息

![Image](https://github.com/user-attachments/assets/f80cbdc7-b9fb-4561-acf0-15a3d8317dfe)
qwen2.5-1.5b-instruct-vllm名称可以忽略不计

### 其他信息

_No response_

了解一下，你的vllm版本是哪个呢，低版本的vllm应该不支持DeepSeek-R1-Distill系列模型吧

请问解决了吗？

> 了解一下，你的vllm版本是哪个呢，低版本的vllm应该不支持DeepSeek-R1-Distill系列模型吧

我使用的是最新的lmdeploy 0.7.1 推理结果也是0

请问解决了吗？我也同样问题

同样问题，看了下predicitons中的内容，看起来reference的内容貌似不对。

`{
    "0": {
        "origin_prompt": [
            {
                "role": "HUMAN",
                "prompt": "### Question:\nYou are given a positive integer N.\r\nIf there are integers x and y such that N=2^x3^y, print Yes; otherwise, print No.\n\nInput\n\nThe input is given from Standard Input in the following format:\nN\n\nOutput\n\nPrint a single line containing Yes if there are integers x and y that satisfy the condition, and No otherwise.\n\nConstraints\n\n\n- 1\\leq N\\leq10^{18}\n- N is an integer.\n\nSample Input 1\n\n324\n\nSample Output 1\n\nYes\r\n\nFor x=2,y=4, we have 2^x3^y=2^23^4=4\\times81=324, so the condition is satisfied.\r\nThus, you should print Yes.\n\nSample Input 2\n\n5\n\nSample Output 2\n\nNo\r\n\nThere are no integers x and y such that 2^x3^y=5.\r\nThus, you should print No.\n\nSample Input 3\n\n32\n\nSample Output 3\n\nYes\r\n\nFor x=5,y=0, we have 2^x3^y=32\\times1=32, so you should print Yes.\n\nSample Input 4\n\n37748736\n\nSample Output 4\n\nYes\n\n### Format: Read the inputs from stdin solve the problem and write the answer to stdout (do not directly test on the sample inputs). Enclose your code within delimiters as follows.\n```python\n# YOUR CODE HERE\n```\n\n### Answer: (use the provided format with backticks)\n\n"
            }
        ],
        "prediction": "\n\n```python\n# Read input\nN = int(input())\n\n# Remove all factors of 2\nx = 0\nwhile N % 2 == 0:\n    N = N // 2\n    x += 1\n\n# Remove all factors of 3\ny = 0\nwhile N % 3 == 0:\n    N = N // 3\n    y += 1\n\n# Check if remaining number is 1\nif N == 1:\n    print(\"Yes\")\nelse:\n    print(\"No\")\n```",
        "gold": "abc324_b"`