Running an example with Docker

Running an example with Docker#

From the root of the Isaac 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 Isaac 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 Isaac Lab container from the root of the Isaac Lab repository, we will run the following:

python docker/container.py start

The terminal will first pull the base IsaacSim image, build the Isaac Lab image’s additional layers on top of it, and run the Isaac Lab container. This should take several minutes upon 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 isaac-lab-base should appear, similar to below:

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

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

python docker/container.py enter

On entering the Isaac Lab container, we are in the terminal as the superuser, root. This environment contains a copy of the Isaac 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 isaaclab.sh script usable from anywhere by typing its alias isaaclab.

Additionally in the container, we have bind mounted the IsaacLab/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 Isaac Lab Docker container.

The Code#

The tutorial corresponds to the log_time.py script in the IsaacLab/source/standalone/tutorials/00_sim directory.

Code for log_time.py
 1# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
 2# All rights reserved.
 3#
 4# SPDX-License-Identifier: BSD-3-Clause
 5
 6"""
 7This script demonstrates how to generate log outputs while the simulation plays.
 8It accompanies the tutorial on docker usage.
 9
10.. code-block:: bash
11
12    # Usage
13    ./isaaclab.sh -p source/standalone/tutorials/00_sim/log_time.py
14
15"""
16
17"""Launch Isaac Sim Simulator first."""
18
19
20import argparse
21import os
22
23from omni.isaac.lab.app import AppLauncher
24
25# create argparser
26parser = argparse.ArgumentParser(description="Tutorial on creating logs from within the docker container.")
27# append AppLauncher cli args
28AppLauncher.add_app_launcher_args(parser)
29# parse the arguments
30args_cli = parser.parse_args()
31# launch omniverse app
32app_launcher = AppLauncher(args_cli)
33simulation_app = app_launcher.app
34
35"""Rest everything follows."""
36
37from omni.isaac.lab.sim import SimulationCfg, SimulationContext
38
39
40def main():
41    """Main function."""
42    # Specify that the logs must be in logs/docker_tutorial
43    log_dir_path = os.path.join("logs")
44    if not os.path.isdir(log_dir_path):
45        os.mkdir(log_dir_path)
46    # In the container, the absolute path will be
47    # /workspace/isaaclab/logs/docker_tutorial, because
48    # all python execution is done through /workspace/isaaclab/isaaclab.sh
49    # and the calling process' path will be /workspace/isaaclab
50    log_dir_path = os.path.abspath(os.path.join(log_dir_path, "docker_tutorial"))
51    if not os.path.isdir(log_dir_path):
52        os.mkdir(log_dir_path)
53    print(f"[INFO] Logging experiment to directory: {log_dir_path}")
54
55    # Initialize the simulation context
56    sim_cfg = SimulationCfg(dt=0.01)
57    sim = SimulationContext(sim_cfg)
58    # Set main camera
59    sim.set_camera_view([2.5, 2.5, 2.5], [0.0, 0.0, 0.0])
60
61    # Play the simulator
62    sim.reset()
63    # Now we are ready!
64    print("[INFO]: Setup complete...")
65
66    # Prepare to count sim_time
67    sim_dt = sim.get_physics_dt()
68    sim_time = 0.0
69
70    # Open logging file
71    with open(os.path.join(log_dir_path, "log.txt"), "w") as log_file:
72        # Simulate physics
73        while simulation_app.is_running():
74            log_file.write(f"{sim_time}" + "\n")
75            # perform step
76            sim.step()
77            sim_time += sim_dt
78
79
80if __name__ == "__main__":
81    # run the main function
82    main()
83    # close sim app
84    simulation_app.close()

The Code Explained#

The Isaac Lab Docker container has several volumes to facilitate persistent storage between the host computer and the container. One such volume is the /workspace/isaaclab/logs directory. The log_time.py script designates this directory as the location to which a log.txt should be written:

    # Specify that the logs must be in logs/docker_tutorial
    log_dir_path = os.path.join("logs")
    if not os.path.isdir(log_dir_path):
        os.mkdir(log_dir_path)
    # In the container, the absolute path will be
    # /workspace/isaaclab/logs/docker_tutorial, because
    # all python execution is done through /workspace/isaaclab/isaaclab.sh
    # and the calling process' path will be /workspace/isaaclab
    log_dir_path = os.path.abspath(os.path.join(log_dir_path, "docker_tutorial"))
    if not os.path.isdir(log_dir_path):
        os.mkdir(log_dir_path)
    print(f"[INFO] Logging experiment to directory: {log_dir_path}")

As the comments note, os.path.abspath() will prepend /workspace/isaaclab because in the Docker container all python execution is done through /workspace/isaaclab/isaaclab.sh. The output will be a file, log.txt, with the sim_time written on a newline at every simulation step:

    # Prepare to count sim_time
    sim_dt = sim.get_physics_dt()
    sim_time = 0.0

    # Open logging file
    with open(os.path.join(log_dir_path, "log.txt"), "w") as log_file:
        # Simulate physics
        while simulation_app.is_running():
            log_file.write(f"{sim_time}" + "\n")
            # perform step
            sim.step()
            sim_time += sim_dt

Executing the Script#

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

isaaclab -p source/standalone/tutorials/00_sim/log_time.py --headless

Now log.txt will have been produced at /workspace/isaaclab/logs/docker_tutorial. If we exit the container by typing exit, we will return to IsaacLab/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 /isaaclab/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 Isaac 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 Isaac Lab Docker container with the following command:

./container.py stop

This will bring down the Docker Isaac 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 isaac-lab-base image:

docker image rm isaac-lab-base

A subsequent run of docker image ls will show that the image tagged isaac-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.