01.11.2023, 06:42
The torch-addon only works with NVIDIA cards.
I could send you a link to the vs-mlrt addon (https://github.com/AmusementClub/vs-mlrt/).
I could send you a link to the vs-mlrt addon (https://github.com/AmusementClub/vs-mlrt/).

(01.11.2023, 06:42)Selur Wrote: [ -> ]The torch-addon only works with NVIDIA cards.
I could send you a link to the vs-mlrt addon (https://github.com/AmusementClub/vs-mlrt/).
damn..Quote:Isn't there any alternative that supports amd newest cards ?Aside from what vs-mlrt offers: not that I know of.
(01.11.2023, 19:00)Selur Wrote: [ -> ]Quote:Isn't there any alternative that supports amd newest cards ?Aside from what vs-mlrt offers: not that I know of.
Cu Selur
Quote: i think the vulkan api could have an advantage in speed using these addons.Okay.
(01.11.2023, 19:11)Selur Wrote: [ -> ]Quote: i think the vulkan api could have an advantage in speed using these addons.Okay.
From what I have seen so far in ml relates stuff, the direct cuda implementations are usually faster than their vulkan alternatives, especially if TensorRT is used.
Cu Selur
Quote:Is there much difference speedwise ?No clue, I bought an NVIDIA card since I knew that:
(01.11.2023, 19:44)Selur Wrote: [ -> ]Quote:Is there much difference speedwise ?No clue, I bought an NVIDIA card since I knew that:
a. they are widely used in universities for years (due to apis&co), so most new research projects&coder use them.
b. the video encoders of AMD hardware were always worse than from Intel and NVIDIA.
According to https://www.hpcwire.com/off-the-wire/amd...-rocm-5-7/ newer pytorch might support AMD cards, so there is hope, but since I don't own a RDNA3 card I can't really say how much trouble it would be for the developers to port their code for that.
Cu Selur
