New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[Issue]: Can't use the GPU in Jellyfin QNAP Docker image for hardware acceleration #9806
Comments
I doubt you can’t use the standard NVIDIA driver package from the distro. Instead, you should install it according to QNAP’s documentation. |
On the QNAP Host there is already automatically installed a Nvidia driver and its working |
I see. So you don't need to install user mode driver from the repo since the versions are mismatched.
Remove them and check the extra docker cli from this doc - https://www.qnap.com/en-us/how-to/tutorial/article/how-to-use-tensorflow-with-container-station |
thanks, thats what I also tried and I checked with the extra devices and mappings from the doc - everything is already there in my container:
|
Maybe this one helps? https://gist.github.com/weshofmann/620b924cde5dd498880e9315e48e793b?permalink_comment_id=4487458#gistcomment-4487458
|
@grossmaul there is no kernel in a container.
means you should have the same Nvidia library version inside the container as the kernel driver on the host. |
yeah, yesterday I learned that I shall not edit anything inside of the container, so I reverted everything and went to the host instead. The command by @nyanmisaka gives this output:
So I highly suspect that its a driver issue from QNAP. There is only one driver (plus Kernel driver) I can install and nothing else... Now I opened a support case with QNAP |
Finally found the solution! Had to use this fix. My solution works on a QNAP TS-673A (applicable for every TS-x76A, like TS-476A and TS-876A) with a Quadro P400 (but other cards should work too since the solution is independent from the GPU model). Problem I want to fix:
This causes that containers can't use the GPU for hardware acceleration (HWA) Step One:
After this you get a proper output from
Step Two:Now you have to do the same inside of the container, but swap the path with the linked path in your container's environmet.
Done!HWA works in Jellyfin now! |
Hi! |
Good morning, Could you share here the docker compose that you are using? look at mine
Eniot |
hi @Eniot666 , this is my compose: services: Check that u have MD0_DATA and i have CACHEDEV1_DATA |
hi, @deejayexe, Thanks. The devices were the wrong way See my final yml compose :
result here :
|
This evening I'm trying to start the transcoding of a film and I get an error:
Do you know if you also need to put this container in place: Have you done anything else on QNAP that could explain why it doesn't work... |
Good morning, I am answering myself, it is also necessary to follow: everything works fine now:
my new docker compose :
on the other hand, no use noted here:
tensorflow container once created can be deleted Edit : you can delete it after but after a reboot you also have to create it again. |
Please describe your bug
Hi there,
I'm having the issue that I can't get Jellyfin to use my GPU (Nvidia Quadro P400) on my QNAP TS-673A due to persistent Nvidia driver in the kernel.
I was following your guide here: https://jellyfin.org/docs/general/administration/hardware-acceleration/
and working on the command line inside of the docker image.
I'm already passing the GPU to the container and its recognized:
OS inside of the container:
Your guide also guided me to this site, where I followed the instructions to install the GPU driver for Debian 11 "Bullseye":
https://wiki.debian.org/NvidiaGraphicsDrivers
From that I used those commands:
Added this to
/etc/apt/sources.list
While Installing I get this message:
(none of those suggested things worked)
When executing
nvidia-smi
I get this:So I suspect that there is already a newer version of the Nvidia driver embedded in the kernel of this docker image, which I cant use.
Kernel info:
I already tried to purge everything (
apt purge nvidia* libnvidia*
) and installed again. Same error.When installed:
(it outputs nothing when no driver installed)
And no, reboot did not help too (I can't do more than stopping and starting the container)
When trying to enable hardware encoding in the Jellyfin settings and start a video, then I get the iconic error message with incompatible media.
I hope you can help with with that issue.
Jellyfin Version
Other
if other:
10.8.10
Environment
Jellyfin logs
No response
FFmpeg logs
Please attach any browser or client logs here
No response
Please attach any screenshots here
No response
Code of Conduct
The text was updated successfully, but these errors were encountered: