2024-01-18, 04:28 PM
UPDATE: For everyone that might have struggled with this like me.
It seems somewhere along the line, the Jellyfin configuration lost access to the NVIDIA GPU's, while docker was able to see it, and by all means jellyfin should be able to access it by default, for some reason it just absolutely refused to. I came across this wonderful answer on stackoverflow https://stackoverflow.com/questions/70761192/docker-compose-equivalent-of-docker-run-gpu-all-option
If like me you have encountered this issue, and if like me you have gone down insane rabbit holes, and if like me, you use the standard docker-compose file recommended by jellyfin, you simply need to add the following code to the compose file for Jellyfin to correctly detect and access your gpu. (Change the count variable to all "count: all" to get access to all gpu's if you're running and using more than one)
Jellyfin can now properly transcode all compatible files.
It seems somewhere along the line, the Jellyfin configuration lost access to the NVIDIA GPU's, while docker was able to see it, and by all means jellyfin should be able to access it by default, for some reason it just absolutely refused to. I came across this wonderful answer on stackoverflow https://stackoverflow.com/questions/70761192/docker-compose-equivalent-of-docker-run-gpu-all-option
If like me you have encountered this issue, and if like me you have gone down insane rabbit holes, and if like me, you use the standard docker-compose file recommended by jellyfin, you simply need to add the following code to the compose file for Jellyfin to correctly detect and access your gpu. (Change the count variable to all "count: all" to get access to all gpu's if you're running and using more than one)
Quote:
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
Jellyfin can now properly transcode all compatible files.