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→Basic example without reading/writing persistent data
Try it out, it should download the MNIST dataset (if not already on your system) and then display some output about the training process. We will not take a look at the source code, you will understand it if you are familiar with Tensorflow. Instead, we will understand the Docker framework.
The first important part is the docker-compose.yml.
=== docker-compose.yml ===
Together with the comments, it should be pretty much self-explanatory. In summary, this docker-compose is going to build a new container, tag it with a specific name, and then run it on our system, using a pre-configured entrypoint (i.e. a command which will be executed after container creation).
<syntaxhighlight lang="yaml">
#
image: ccu.uni-konstanz.de:5000/<your.username>/tf_mnist:0.1
# The container needs the nvidia container runtime.
# 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:
