Automated deployment of Deeplabcut #5
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We might want to rename the role as it installs DeepLabCut3. Or we split it up into several roles:
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... |
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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! |
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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. |
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This implements an ansible role to setup and configure a vanilla ubuntu machine (with nvidia gpu) for DeepLabCut