No package nvidia-docker2 available. Error: Nothing to do Client: Version: 1.8.2 API version: 1.20 Package Version: docker-1.8.2-7.el7.centos.x86_64 Go version: go1.4.2 Git commit: bb472f0/1.8.2 Built: OS/Arch: linux/amd64
参考:https://github.com/NVIDIA/nvidia-docker/issues/533 2、cannot connect to X server 原因:在docker中执行了GUI可视化代码,比如cv2.imshow() 解决方案:注释掉可视化代码(简单粗暴)或者参考https://www.zealseeker.com/archives/docker-for-gui-environment/ 3、在Dockerfile中condainstall/pip install 使用conda...
I’ve even included a section in the dockerfile to manually fetch nvidia-drivers-520 and nvidia-container-toolkit, to no avail. I have the CUDA toolkit installed on my local host. I have every single nvidia related package under the sun installed to m...
1> 直接使用如上脚本创建 gpu docker,会出现我的报错,应该是文件冲突了。首先不打开 gpu,而使用 cpu 来创建容器,也即打开上述我注释掉的部分,然后把创建 gpu docker 部分注释掉; 2> run 这个 cpu 容器,这里应该能够成功。在容器内删除报错文件,比如我这里删除/usr/lib/x86_64-linux-gnu/libnvidia-ml.so.1...
apt install docker fi if ! [ -x "$(command -v nvidia-docker)" ]; then apt install nvidia-docker2 fi if ! [ -x "$(command -v docker-compose)" ]; then curl -SL https://files.seeedstudio.com/wiki/reComputer/compose.tar.bz2 -o /tmp/compose.tar.bz2 tar xvf /tmp/compose.tar....
Description Hi, I have compiled jax from source and tried the prebuilt wheels, getting the same error. This is in a Docker container on the device. This is the error using the NVIDIA Jetson Orin Nano: jax 0.4.31.dev20240728+6a7822a73 /ho...
nvidia-container-cli: initialization error: WSL environment detected but no adapters were found: unknown. Note: Docker is running ok Thank you very much if you can help me. Thanks a lot
When running NVIDIA containerized workloads and taking advantage of NVIDIA GPU's, executing containers in either Docker or Podman, on Red Hat Enterprise Linux or within Red Hat OpenShift produces errors that are similar to: Raw container_linux.go:349: starting container process caused "process_lin...
$sudosystemctl restartdocker 1. 2. 3. 4. 5. Test the configuration by running a Docker container with GPU support: $dockerrun--gpusall nvidia/cuda:11.0-base nvidia-smi 1. If the output of the above command shows the NVIDIA System Management Interface (nvidia-smi) without any errors, it...
Docker Base image : nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 Pytorch 1.0.1 torchvision 0.2.2 apex 0.1 Question: Same application is working fine in Tesla T4 CUDA10.0 directly on the same software environment at the GPU server (without using docker image) ...