在Ubuntu系统部署，heygem-f2f容器报错：RuntimeError: Found no NVIDIA driver on your system

[gavid0124]

完整报错信息如下： 2025-03-24 11:46:44] [app_local.py[line:230]] [WARNING] [ -> 服务不进行注册] [2025-03-24 11:46:44] [app_local.py[line:231]] [INFO] [TransDhTask init] Traceback (most recent call last): File "/code/app_local.py", line 231, in TransDhTask.instance() File "trans_dh_service.py", line 1207, in trans_dh_service.TransDhTask.instance File "trans_dh_service.py", line 1189, in trans_dh_service.TransDhTask.init File "compute_ctc_att_bnf.py", line 130, in compute_ctc_att_bnf.load_ppg_model File "/usr/local/python3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1152, in to return self._apply(convert) File "/usr/local/python3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 802, in _apply module._apply(fn) File "/usr/local/python3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 802, in _apply module._apply(fn) File "/usr/local/python3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 802, in _apply module._apply(fn) [Previous line repeated 1 more time] File "/usr/local/python3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 825, in _apply param_applied = fn(param) File "/usr/local/python3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1150, in convert return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking) File "/usr/local/python3/lib/python3.8/site-packages/torch/cuda/init.py", line 302, in _lazy_init torch._C._cuda_init() RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx

https://github.com/GuijiAI/HeyGem.ai/issues/158 试过这个，没成功。

也试过重新拉取镜像，也不行，命令：docker-compose pull && docker-compose up -d

系统是Ubuntu 22.04.5，显卡是8张4090。

[qiumiao1988]

请问安装成功了吗？ ubuntu

[gavid0124]

请问安装成功了吗？ ubuntu

heygem-f2f容器不行，起不来。

[whl88]

1. Execute the nvidia-smi command to confirm whether the graphics card driver is installed.
2. Install the NVIDIA Container Toolkit. The NVIDIA Container Toolkit is a necessary tool for Docker to use NVIDIA GPUs.

[gavid0124]

1. Execute the nvidia-smi command to confirm whether the graphics card driver is installed.
2. Install the NVIDIA Container Toolkit. The NVIDIA Container Toolkit is a necessary tool for Docker to use NVIDIA GPUs.

这几个肯定都有的，都是最基本的。

[blessing-gao]

我也是这个问题，nvidia-smi没问题，其他两个运行正常

[yuanli-wan]

不要使用docker desktop（win版），看似nvidia-smi成功，其实用torch都会出现torch.cuda.is_available() 为false，直接使用wsl ubuntu 安装docker（具体参照百度）,还要安装cuda toolkit，nvidia-container-tookit，然后再拉取f2 image就会成功识别gpu