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You can now execute this image from any computer which has the nvidia docker infrastructure installed and is logged into our cluster registry. It is ready to be deployed using Kubernetes.
→Uploading the final container to the cluster registry
== Uploading the final container to the cluster registry ==
Once you are happy with your code, you can upload the container image to the cluster registry just as in the basic tutorial before:. Replace the tag by whatever you have used in the docker-compose.yml.
<syntaxhighlight lang="bash">
docker push ccu.uni-konstanz.de:5000/<your.username>/tf_mnist:0.1
</syntaxhighlight>
You can now execute this image from '''any''' computer which has the nvidia docker infrastructure installed and is logged into our cluster registry, for example like this:
<syntaxhighlight lang="bash">
docker run --runtime=nvidia -d ccu.uni-konstanz.de:5000/<your.username>/tf_mnist:0.1
</syntaxhighlight>
== Monitoring the training process with Tensorboard ==
