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Docker Installation for MME-VLA Policy Learning

This guide sets up Docker and NVIDIA GPU support so you can build and run the MME-VLA 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 MME-VLA Docker image

From the repository root:

docker build -t mme_vla:cuda12.8 .

Enter the docker

export PORT=8001
docker run --rm -it --gpus all \
  -e NVIDIA_DRIVER_CAPABILITIES=compute,graphics,utility,video \
  -v "$PWD/runs:/app/runs" -v "$PWD/data:/app/data" \
  -p $PORT:$PORT \
  mme_vla:cuda12.8

Evaluate the policy

# terminal 0
CUDA_VISIBLE_DEVICES=0 uv run scripts/serve_policy.py --seed=7  --port=$PORT policy:checkpoint --policy.dir=runs/ckpts/mme_vla_suite/perceptual-framesamp-modul/79999 --policy.config=mme_vla_suite

# terminal 1 
eval "$(micromamba shell hook --shell bash)
micromamba activate robomme 
CUDA_VISIBLE_DEVICES=1 python examples/robomme/eval.py --args.model_seed=7 --args.port=$PORT --args.policy_name=perceptual-framesamp-modul --args.model_ckpt_id=79999

4) Others

To stop the docker

docker ps
docker stop <container_id_or_name>

To rebuild the docker image

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