在docker容器中使用GPU-CUDA版本:N/A和torch.cuda.is_available返回False [英] Using GPU inside docker container - CUDA Version: N/A and torch.cuda.is_available returns False
问题描述
我正在尝试从Docker容器内部使用GPU.我正在Ubuntu 18.04上使用版本19.03的Docker.
I'm trying to use GPU from inside my docker container. I'm using docker with version 19.03 on Ubuntu 18.04.
如果我运行nvidia-smi，则在docker容器之外，我得到以下输出.
Outside the docker container if I run nvidia-smi I get the below output.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.05 Driver Version: 450.51.05 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 On | 00000000:00:1E.0 Off | 0 |
| N/A 30C P8 9W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
如果我在从nvidia/cuda docker image创建的容器中运行相同的东西，我将获得与上面相同的输出，并且一切运行顺利.torch.cuda.is_available()返回 True .
If I run the samething inside the container created from nvidia/cuda docker image, I get the same output as above and everything is running smoothly. torch.cuda.is_available() returns True.
但是，如果我在其他任何docker容器中运行相同的nvidia-smi命令，它将给出以下输出，您可以看到CUDA版本以 N/A 的形式出现.在容器内 torch.cuda.is_available()还会返回 False .
But If I run the same nvidia-smi command inside any other docker container, it gives the following output where you can see that the CUDA Version is coming as N/A. Inside the containers torch.cuda.is_available() also returns False.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.05 Driver Version: 450.51.05 CUDA Version: N/A |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 On | 00000000:00:1E.0 Off | 0 |
| N/A 30C P8 9W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
我已经使用以下命令安装了nvidia-container-toolkit.
I have installed nvidia-container-toolkit using the following commands.
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/ubuntu18.04/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo apt-get install nvidia-container-toolkit
sudo systemctl restart docker
我使用以下命令启动了容器
I started my containers using the following commands
sudo docker run --rm --gpus all nvidia/cuda nvidia-smi
sudo docker run -it --rm --gpus all ubuntu nvidia-smi
推荐答案
docker run --rm --gpus所有nvidia/cuda nvidia-smi 不应返回 CUDA版本:N/如果所有内容(又名nvidia驱动程序，CUDA工具包和nvidia-container-toolkit)都已正确安装在主机上，则为A .
鉴于 docker run --rm --gpus所有nvidia/cuda nvidia-smi 正确返回.我在容器内部的 CUDA版本:N/A 上也遇到了问题，我在解决问题上很幸运:
Given that docker run --rm --gpus all nvidia/cuda nvidia-smi returns correctly. I also had problem with CUDA Version: N/A inside of the container, which I had luck in solving:
请查看我的回答 https://stackoverflow.com/a/64422438/2202107 (显然，您需要进行调整并安装所有版本的匹配/正确版本)
Please see my answer https://stackoverflow.com/a/64422438/2202107 (obviously you need to adjust and install the matching/correct versions of everything)
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