Closed chinrw closed 1 year ago
Just wanna mention it is prolly not on ur side i have the Same without the core dumped msg, It is most likely an issue on how the docker image was compiled. I tried complying it on my own but it errors so it might be outdated.
This error message suggests that you use an outdated cpu with not all instruction sets needed. Rebuild the image from scratch with DOCKER_BUILDKIT=1 docker build --no-cache -t styler00dollar/vsgan_tensorrt:latest .
instead of downloading it and it will most likely resolve cpu related compatibility issues. I use a 7950x to compile the depenencies in docker and it seems like lacking avx support on other cpus is the reason. On my side, Arch and Windows 10 work fine.
Since I don't know what dependency throws that error and have no way to verify or recreate this problem myself, I will not support it. I need at least one confirmation that rebuilding the docker image from scratch works properly, then I can just close the issue.
OK, since I'm using the "outdated" i3900k which doesn't support AVX 512, I tried to build the docker image myself. And the original Dockerfile doesn't work due to some updated package versions. I have created a new pr for this.
I was suspecting some sort of AVX instruction set, but this seems to confirm AVX512 then.
due to some updated package versions.
Yeah, that happens all the time. I often do adjustments prior to building since versions can change. That's why I like to upload my docker images to dockerhub so others don't have to bother.
I have created a new pr for this.
My pc is currently not in a working state due to boot problems so I can't test it myself right now, but it looks good, thanks. I will just merge it in.
Does this mean you got it working by rebuilding the docker from scratch? If yes, would you mind to upload the image to dockerhub? I would then link it in the readme while I don't have a way to build it myself. Building the docker on a cpu that does not support AVX512 should be the easiest way to disable it for now. I could try to build the image on my steam deck or some other hardware I don't usually use, but I will need to see if it will work.
Hi, it works if I rebuild the docker from scratch. And here is the dockerhub link https://hub.docker.com/r/chin39/vsgan_tensorrt/.
Hi, it works if I rebuild the docker from scratch. And here is the dockerhub link https://hub.docker.com/r/chin39/vsgan_tensorrt/.
Could u link the docker file u used to build or did u use the github one styler updated ? Cause i get to a point at around 70/176 and it crashes. Retrying now from scratch will see if it works.
ERROR: failed to solve: process "/bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-12-1 cuda-cudart-12-1 cuda-compat-12-1 && rm -rf /var/lib/apt/lists/*" did not complete successfully: exit code: 100
@Anon1337Elite Hi, I am using the https://github.com/styler00dollar/VSGAN-tensorrt-docker/blob/main/Dockerfile since my PR has been merged. Does it have more error messages above? It should have some details rather than just exit code.
BTW, "/bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-12-1 cuda-cudart-12-1 cuda-compat-12-1 && rm -rf /var/lib/apt/lists/*"
may be affected by your network, could you try to rerun again?
@Anon1337Elite Hi, I am using the https://github.com/styler00dollar/VSGAN-tensorrt-docker/blob/main/Dockerfile since my PR has been merged. Does it have more error messages above? It should have some details rather than just exit code.
BTW,
"/bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-12-1 cuda-cudart-12-1 cuda-compat-12-1 && rm -rf /var/lib/apt/lists/*"
may be affected by your network, could you try to rerun again?
Thanks it worked the 3rd time.
Added relevant information into readme. Thanks.
Tried to build the docker on an old intel quad-core cpu and it worked. I will try to keep avx and non-avx docker images updated.
When I try to render the video by your docker image, it gave me this error
Use the default config
Only updated the engine path, and the code doesn't execute this far, it looks failed at
clip = core.ffms2.Source(source=video_path, cache=False)
Here is the complete log.