To build the docker image on your own machine, which may take 15-30 mins:
docker build -t stable-dreamfusion:latest .
If you have the error No CUDA runtime is found when building the wheels for tiny-cuda-nn you need to setup the nvidia-runtime for docker.
sudo apt-get install nvidia-container-runtime
Then edit /etc/docker/daemon.json and add the default-runtime:
{
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
},
"default-runtime": "nvidia"
}
And restart docker:
sudo systemctl restart docker
Now you can build tiny-cuda-nn inside docker.
To download the image (~6GB) instead:
docker pull supercabb/stable-dreamfusion:3080_0.0.1
docker tag supercabb/stable-dreamfusion:3080_0.0.1 stable-dreamfusion
You can launch an interactive shell inside the container:
docker run --gpus all -it --rm -v $(cd ~ && pwd):/mnt stable-dreamfusion /bin/bash
From this shell, all the code in the repo should work.
To run any single command <command...> inside the docker container:
docker run --gpus all -it --rm -v $(cd ~ && pwd):/mnt stable-dreamfusion /bin/bash -c "<command...>"
To train:
export TOKEN="#HUGGING FACE ACCESS TOKEN#"
docker run --gpus all -it --rm -v $(cd ~ && pwd):/mnt stable-dreamfusion /bin/bash -c "echo ${TOKEN} > TOKEN \
&& python3 main.py --text \"a hamburger\" --workspace trial -O"
Run test without gui:
export PATH_TO_WORKSPACE="#PATH_TO_WORKSPACE#"
docker run --gpus all -it --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:ro -v $(cd ~ && pwd):/mnt \
-v $(cd ${PATH_TO_WORKSPACE} && pwd):/app/stable-dreamfusion/trial stable-dreamfusion /bin/bash -c "python3 \
main.py --workspace trial -O --test"
Run test with gui:
export PATH_TO_WORKSPACE="#PATH_TO_WORKSPACE#"
xhost +
docker run --gpus all -it --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:ro -v $(cd ~ && pwd):/mnt \
-v $(cd ${PATH_TO_WORKSPACE} && pwd):/app/stable-dreamfusion/trial stable-dreamfusion /bin/bash -c "python3 \
main.py --workspace trial -O --test --gui"
xhost -