Editing Tutorials:container which trains MNIST using Tensorflow (section)

=== docker-compose.yml ===

Together with the comments, it should be pretty much self-explanatory. In summary, this docker-compose is going to build the application container, tag it with a specific name, and then run it once on our system, using a pre-configured entrypoint (i.e. a command which will be executed after container creation). Please edit this file now and set your own username in the tag id of the image.

<syntaxhighlight lang="yaml">
#
# This defines the version of the docker-compose.yml
# file format we are using.
#
version: '2.3'

#
# In this section, all the services we are going to
# start are defined. Each service corresponds to one
# container.
#
services:

    # Our application container is the only one we start.
    application:

        # This tells docker-compose that we intend to
        # build the application container from scratch, it
        # is not just a pre-existing image. The build configuration
        # (kind of a makefile) resides in the subdirectory
        # "application" in the file "Dockerfile".
        build: 
            context: ./application
            dockerfile: Dockerfile

        # This gives the container which has been built a "tag".
        # A tag is a unique name which you can use to refer to this container.
        # It should be of the form "<registry>/<username>/<application>:<version>
        # If <version> is not specified, it will get the default "latest".
        #
        # The registry should be the one of the CCU, same with your
        # username. You can also use a temporary image name here and
        # later use the "docker tag" commmand to rename it to the final name
        # you want to push to the registry.
        #
        image: ccu.uni-konstanz.de:5000/<your.username>/tf_mnist:0.1

        # The container needs the nvidia container runtime.
        # The following is equivalent to specifying "docker run --runtime=nvidia".
        # It is not necessary if nvidia is already configured as the
        # default runtime (as on the Kubernetes cluster).
        runtime: nvidia

        # Environment variables set when running the image,
        # which can for example used to configure the nVidia base
        # container or your application. You can use these to
        # configure your own code as well.
        #
        environment:
          - NVIDIA_VISIBLE_DEVICES=all

        # This container should only be started once, if it fails,
        # we have to fix errors anyway, if it exits successfully,
        # we are happy.
        restart: "no"

        # The entry point of the container, i.e. the script or executable
        # which is started after it has been created.
        entrypoint: "/application/run.sh"
</syntaxhighlight>