README.md

Docker setup

This docker setup is tested on Ubunu20.04.

make sure you are under directory yourworkspace/Wonder3D/

run

docker build --no-cache -t wonder3d/deploy:cuda11.7 -f docker/Dockerfile .

then run

docker run --gpus all -it wonder3d/deploy:cuda11.7 bash

Nvidia Container Toolkit setup

You will have trouble enabling gpu for docker if you haven't installed NVIDIA Container Toolkit on you local machine before. You can skip this section if you have already installed it. Follow the instruction in this website to install it.

https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

or you can run the following command to install it with apt:

1.Configure the production repository:

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

2.Update the packages list from the repository:

sed -i -e '/experimental/ s/^#//g' /etc/apt/sources.list.d/nvidia-container-toolkit.list

3.Install the NVIDIA Container Toolkit packages:

sudo apt-get install -y nvidia-container-toolkit

Remember to restart the docker:

sudo systemctl restart docker

now you can run the following command:

docker run --gpus all -it wonder3d/deploy:cuda11.7 bash

Install Tiny Cudann

After you start the container, run the following command to install tiny cudann. Somehow this pip installation can not be done during the docker build, so you have to do it manually after the docker is started.

pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch

Now you should be good to go, good luck and have fun :)