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→Access the containers on the nVidia GPU cloud
Copy it and place it in a file somewhere safe so that you remember it. You can generate a new one anytime, but then the old one will become invalid.
You can now tell docker to login to the nVidia GPU cloud container registry so that you can pull container images from there.
For this, use the shell command
<syntaxhighlight lang="bash">
docker login -u '$oauthtoken' --password-stdin nvcr.io <<< ' your API key here between the quotes '
</syntaxhighlight>
That's it. I suggest you put the above command in a script in $USER/bin, so you can quickly rerun it after a reboot, then you also do not forget your key. Remember to protect your folders from being read by other users if they contain this kind of sensitive information.
You can test whether everything worked by pulling a container from the nVidia cloud and then firing up Python inside the container:
<syntaxhighlight lang="bash">
docker run -it --runtime=nvidia nvcr.io/nvidia/tensorflow:18.06-py3 python
</syntaxhighlight>
The first time will be slow, as it needs to download all the images, after that, they will be in your local storage and start up much faster.
The next tutorial will show how to use these images as a basis for your own applications.
