docker_installation.md

Docker Installation for RoboMME

This guide sets up Docker and NVIDIA GPU support so you can build and run the RoboMME image.

1) Install Docker Engine

Skip this if you already installed docker.

Follow Docker’s official instructions for Ubuntu:

• Docker Engine install guide: https://docs.docker.com/engine/install/ubuntu/

After installing, make sure the service is running:

docker run --rm hello-world

2) Install NVIDIA Container Toolkit (GPU support)

Skip this if you already installed nvidia-ctk.

Install the toolkit (Ubuntu):

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
  sudo gpg --dearmor --batch --yes -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg

curl -fsSL 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

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

Configure Docker to use the NVIDIA runtime and restart Docker:

sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

Verify GPU access inside a container:

docker run --rm --gpus all nvidia/cuda:12.8.0-base-ubuntu24.04 nvidia-smi

3) Build the RoboMME Docker image

From the repository root:

docker build -t robomme:cuda12.8 .

Enter the docker

# download the robomme_data_h5 from https://huggingface.co/Yinpei/robomme_data_h5
export robomme_data_path=<robomme_data_h5_path>

docker run --rm -it --gpus all \
  -e NVIDIA_DRIVER_CAPABILITIES=compute,graphics,utility,video \
  -v "$PWD/runs:/app/runs" \
  -v "$robomme_data_path:/app/data/robomme_data_h5:ro" \
  robomme:cuda12.8

Run sample scripts

uv run ./scripts/run_example.py

4) Others

To stop the docker

docker ps
docker stop <container_id_or_name>

To rebuild the docker image

docker build --no-cache -t robomme:cuda12.8 .