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→Basic example without reading/writing data
We will start simple, and then gradually add more capability for our program:
== Basic example without reading/writing persistent data == Check out the subdirectory "example_1" of the tutorial code. The structure is as follows: <syntaxhighlight lang="bash">-- example_1 -- docker-compose.yml -- application -- Dockerfile -- src -- run.sh -- train_tf_mnist.py -- nn_tf_mnist.py</syntaxhighlight> In the subdirectory "application/src" is the actual Python code of the project, the rest are directives how to build and run the container. Let's first take a look at the application to get that out of the way. You should be able to run it directly on your system, without using containers: <syntaxhighlight lang="bash">cd example_1/application/srcpython train_tf_mnist.py</syntaxhighlight> Try it out, it should download the MNIST dataset to "/tmp/mnist" and then display some output about the training process. Let's take a look at the source. It has a sufficient number of comments so that it is hopefully self-explaining: <syntaxhighlight lang="bash">TODO</syntaxhighlight>
== Logging console output of our program ==
