Running an example with Docker

From the root of the UW Lab repository, the docker directory contains all the Docker relevant files. These include the three files (Dockerfile, docker-compose.yaml, .env) which are used by Docker, and an additional script that we use to interface with them, container.py.

In this tutorial, we will learn how to use the UW Lab Docker container for development. For a detailed description of the Docker setup, including installation and obtaining access to an Isaac Sim image, please reference the Docker Guide. For a description of Docker in general, please refer to their official documentation.

Building the Container

To build the UW Lab container from the root of the UW Lab repository, we will run the following:

python docker/container.py start

The terminal will first pull the base IsaacSim image, build the UW Lab image’s additional layers on top of it, and run the UW Lab container. This should take several minutes for the first build but will be shorter in subsequent runs as Docker’s caching prevents repeated work. If we run the command docker container ls on the terminal, the output will list the containers that are running on the system. If everything has been set up correctly, a container with the NAME uw-lab-base should appear, similar to below:

CONTAINER ID   IMAGE               COMMAND   CREATED           STATUS         PORTS     NAMES
483d1d5e2def   uw-lab-base      "bash"    30 seconds ago   Up 30 seconds             uw-lab-base

Once the container is up and running, we can enter it from our terminal.

python docker/container.py enter

On entering the UW Lab container, we are in the terminal as the superuser, root. This environment contains a copy of the UW Lab repository, but also has access to the directories and libraries of Isaac Sim. We can run experiments from this environment using a few convenient aliases that have been put into the root .bashrc. For instance, we have made the uwlab.sh script usable from anywhere by typing its alias uwlab.

Additionally in the container, we have bind mounted the UWLab/source directory from the host machine. This means that if we modify files under this directory from an editor on the host machine, the changes are reflected immediately within the container without requiring us to rebuild the Docker image.

We will now run a sample script from within the container to demonstrate how to extract artifacts from the UW Lab Docker container.

Executing the Script

We will execute the script to produce a log, adding a --headless flag to our execution to prevent a GUI:

uwlab -p scripts/tutorials/00_sim/log_time.py --headless

Now log.txt will have been produced at /workspace/uwlab/logs/docker_tutorial. If we exit the container by typing exit, we will return to UWLab/docker in our host terminal environment. We can then enter the following command to retrieve our logs from the Docker container and put them on our host machine:

./container.py copy

We will see a terminal readout reporting the artifacts we have retrieved from the container. If we navigate to /uwlab/docker/artifacts/logs/docker_tutorial, we will see a copy of the log.txt file which was produced by the script above.

Each of the directories under artifacts corresponds to Docker volumes mapped to directories within the container and the container.py copy command copies them from those volumes to these directories.

We could return to the UW Lab Docker terminal environment by running container.py enter again, but we have retrieved our logs and wish to go inspect them. We can stop the UW Lab Docker container with the following command:

./container.py stop

This will bring down the Docker UW Lab container. The image will persist and remain available for further use, as will the contents of any volumes. If we wish to free up the disk space taken by the image, (~20.1GB), and do not mind repeating the build process when we next run ./container.py start, we may enter the following command to delete the uw-lab-base image:

docker image rm uw-lab-base

A subsequent run of docker image ls will show that the image tagged uw-lab-base is now gone. We can repeat the process for the underlying NVIDIA container if we wish to free up more space. If a more powerful method of freeing resources from Docker is desired, please consult the documentation for the docker prune commands.