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

=== Inspecting a running container ===

Let's start the container in the background using the -d flag. Note that you will not see console output anymore.

<syntaxhighlight lang="bash">
> docker-compose up --build -d
</syntaxhighlight>

The container is now listed under running containers.

<syntaxhighlight lang="bash">
> docker ps
CONTAINER ID IMAGE                                                    COMMAND                CREATED        STATUS        PORTS     NAMES
bcc2a2e8f42e ccu.uni-konstanz.de:5000/bastian.goldluecke/tf_mnist:0.1 "/application/run.sh"  6 minutes ago  Up 6 minutes  6006/tcp  example_1_application_1
</syntaxhighlight>

We can check the console output by reading the logs, using the ID or the name of the container.

<syntaxhighlight lang="bash">
> docker logs example_1_application_1
</syntaxhighlight>

We can also open a shell inside the container, and inspect it's contents. In fact, you can also execute any other command in it.

<syntaxhighlight lang="bash">
> docker exec -it example_1_application_1 /bin/bash
root@fcb20664b49e:/workspace# nvidia-smi
Wed Jun  5 10:06:31 2019       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.67       Driver Version: 418.67       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Quadro GV100        On   | 00000000:03:00.0  On |                  Off |
| 38%   52C    P2    42W / 250W |  30981MiB / 32475MiB |      1%      Default |
+-------------------------------+----------------------+----------------------+

root@fcb20664b49e:/workspace# ls /application
nn.py  run.sh  tf-mnist.py
root@fcb20664b49e:/workspace# 
</syntaxhighlight>

We can also copy the output of the container into the filesystem of the host using an scp-like syntax:

<syntaxhighlight lang="bash">
> docker cp example_1_application_1:/tmp/data ./tmp
</syntaxhighlight>

Once you are done with trying things out, stop the container with

<syntaxhighlight lang="bash">
> docker kill example_1_application_1
</syntaxhighlight>