docker: Error response from daemon: could not select device driver "" with capabilities: [[gpu]]

Hi there,

I am unable to get either docker or pip installation to run with GUI on a remote server (Ubuntu 18.04.5 LTS). nvidia-smi shows NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 With a GeForce RTX 2080 SUPER

After installing docker according to these direction: https://docs.docker.com/engine/install/ubuntu/
sudo docker run hello-world runs successfully I cloned the repository

git clone [e-mail]:StanfordVL/iGibson.git cd iGibson ./docker/pull-images.sh

docker images shows that I have these repositories download: igibson/igibson-gui latest f1609b44544a 6 days ago 8.11GB igibson/igibson latest e2d4fafb189b 6 days ago 7.48GB

But sudo ./docker/headless-gui/run.sh elicits this error: Starting VNC server on port 5900 with password 112358 please run “python simulator_example.py” once you see the docker command prompt: docker: Error response from daemon: could not select device driver “” with capabilities: [[gpu]].

sudo ./docker/base/run.sh also elicits: docker: Error response from daemon: could not select device driver “” with capabilities: [[gpu]].

One guess is that something is wrong with OpenGL, but I don’t know how to fix it. If I run glxinfo -B, I get name of display: localhost:12.0 libGL error: No matching fbConfigs or visuals found libGL error: failed to load driver: swrast display: localhost:12 screen: 0 direct rendering: No (If you want to find out why, try setting LIBGL_DEBUG=verbose) OpenGL vendor string: Intel Inc. OpenGL renderer string: Intel® Iris™ Plus Graphics 655 OpenGL version string: 1.4 (2.1 INTEL-14.7.8)

Note: I can successfully run xeyes on the server and have it show up on my local machine. And glxgears shows the gears image but the gears are not rotating. (and returns this error: libGL error: No matching fbConfigs or visuals found libGL error: failed to load driver: swrast )

I also tried the steps from the trouble shooting page: ldconfig -p | grep EGL yields libEGL_nvidia.so.0 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL_nvidia.so.0 libEGL_nvidia.so.0 (libc6) => /usr/lib/i386-linux-gnu/libEGL_nvidia.so.0 libEGL_mesa.so.0 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0 libEGL.so.1 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so.1 libEGL.so (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so And I checked that /usr/lib/x86_64-linux-gnu/libEGL.so -> libEGL.so.1.0.0

I also do not appear to have any directories such as /usr/lib/nvidia-vvv (I only have /usr/lib/nvidia, /usr/lib/nvidia-cuda-toolkit, and /usr/lib/nvidia-visual-profiler)

Any help would be very much appreciated! Thank you so much.

[izkula]

Okay, I solved the docker issue by installing the nvidia container toolkit (nvidia-docker2) Following this: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \ && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \ && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list sudo apt-get update sudo apt-get install -y nvidia-docker2 sudo systemctl restart docker sudo docker run --rm --gpus all nvidia/cuda:10.0-base nvidia-smi ----> It works (for this example) Now to try iGibson sudo ./docker/headless-gui/run.sh

It would still be great to figure out why the other install methods don’t work here, though

[fxia22]

For the build error, looks like CUDA_TOOLKIT_ROOT_DIR is not set, can you set it to where your cuda is located?

something like export CUDA_TOOLKIT_ROOT_DIR=/usr/loca/cuda-<version>

you can also configure the build not to use cuda (this way rendering to tensor is not available, but you can still use most of iGibson features), by changing this line to FALSE:

https://github.com/StanfordVL/iGibson/blob/master/gibson2/render/CMakeLists.txt#L11