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

=== application/Dockerfile ===

This is equivalent to a makefile for our application container. Also hopefully self-explanatory due to the comments.

<syntaxhighlight lang="bash">
# First, we define the base image of the container.
#
# Our example container is derived from nVidia's image
# 'tensorflow:18.06-py3', the code stands
# for container version 18.06 (nVidia's internal version number),
# which contains tensorflow set up for python3
#
FROM nvcr.io/nvidia/tensorflow:18.06-py3

#
# This is the maintainer of the container, referenced
# by e-Mail address.
#
MAINTAINER ccu@uni-konstanz.de

#
# This is the first line which tells us how this container
# differs from the base image.
#
# In this case, we copy the subdirectory "src" from
# the directory containing the Dockerfile into the
# directory "/application" of the container image.
#
COPY src /application

#
# Many COPY commands can be issued, as well as RUN
# commands which run commands inside the container, e.g.
# to install stuff.
#
# The following is just an example, it is not necessary for
# the application to run. The final container image will
# now contain the "nano" editor just in case you need it
# when logging into the container (yes, you can do this while it's
# running). You should always squeeze as many package
# installations as possible into one RUN command, as each one
# will generate a new intermediate container image.
#
# Note that COPY as well as RUN are executed with sudo
# privileges inside the container. Yes, this also means
# you can access anything on the host, that's why being
# a docker user is basically equivalent to being a sudo user
# on a system. When running on the Kubernetes cluster,
# container privileges are of course much more limited.
#
RUN apt-get update && apt-get install -y nano

#
# this is what will be executed by default when the container is run
#
ENTRYPOINT [ "/application/run.sh" ]
</syntaxhighlight>

That's basically already what is different from a container deployment to executing the application directly on your system. Of course, there are more details to learn, in particular about how to mount external filesystems of the cluster into the container, so you can read/write persistent data. More on this later. Let's now run the container defined in the above configuration files.