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Thorough health check not selecting the selected decoder for amf (uses vaapi) and videotoolbox (uses nvenc) #1114

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flipou83 opened this issue Nov 5, 2024 · 0 comments
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enhancement New feature or request

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@flipou83
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flipou83 commented Nov 5, 2024

Please put plugin requests/bugs at: https://github.com/HaveAGitGat/Tdarr_Plugins

Describe the bug
When using thorough health checks, I want to use my mac mini and my amd (cpu and gpu) windows machine. When I select videotoolbox to do thorough healthcheck it errors out and says it used nvenc decode engine.
When selecting amf from the dropdown on my AMD windows node the thorough health checks fails trying to use vaapi (which is only on linux I assume).

To Reproduce
have a windows node with amd cpu/gpu, do a thorough health check on gpu after selecting amf from the drop down menu.
have a macos m series node, do a thorough heatlh check on gpu after selecting videotoolbox from the drop down menu.

Expected behavior
I expected the windows node to actually use the APU and or GPU with the amf engine to decode and health check my files.
Same for the macos node with video toolbox.

Screenshots
If applicable, add screenshots to help explain your problem.

Please provide the following information:

  • Config files [can be found in /app/configs/ when using Docker or in the /configs folder next to Tdarr_Updater if not using Docker]

  • Job reports: https://docs.tdarr.io/docs/other/job-reports

  • Log files [can be found in /app/logs/ when using Docker or in the /logs folder next to Tdarr_Updater if not using Docker]

-Worker error [can be found on the 'Tdarr' tab by pressing the 'i' button on a failed item in the staged file section or in the transcode error section at the bottom]

  • OS: [e.g. Linux]
  • Browser [e.g. chrome, safari]
  • Version [e.g. 2.00.00]

Additional context
I've talked a lot of the discord about this issue and I've found a work around using cpu custom arguments in the thorough health check option of the node -hwaccel d3d11va.. It uses a bit of 3D ressources from my video card but is still not very fast and efficient.

@HaveAGitGat HaveAGitGat added the enhancement New feature or request label Dec 23, 2024
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