Automated deployment of Deeplabcut

[j-i-l]

This implements an ansible role to setup and configure a vanilla ubuntu machine (with nvidia gpu) for DeepLabCut

[j-i-l]

We might want to rename the role as it installs DeepLabCut3.

Or we split it up into several roles:

• setting up conda
• installing pytorch
• installing deeplabcut

Up to installing conda could be a reasonable split. Afterwards pytorch could also be installed with RocM on AMD hardware. Also deeplabcut works with pytorch only from 3.0 on (see DeepLabCut/DeepLabCut#2613) and needs tensorflow for earlier versions...

[j-i-l]

This is quite the mess for a declarative setup.

the constraint tf <=2.10 applies also for ubuntu (not 2.12 as indicated. tf 2.10 limits us to python <=3.10.

We should adapt our default parameter values accordingly!

[j-i-l]

A better approach might be to directly checkout a repo that contains some analysis performed with DeepLabCut and fetch the dlc version form the repo's requirements.txt.