28 lines
1.5 KiB
Markdown
28 lines
1.5 KiB
Markdown
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# Running Experiments with Lambda:
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This is not supposed to be a instruction on how to do it properly, but it is a writeup on how i did it.
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If you want to do it properly, extend the command line Arguments for haga-lambda and allow runtime tweaking of Hyperparams and Datasets. While at it, generalizing LamdaCalculusV1 would be smart, too. You can use LamdaCalculusV2 as a template on how to do it more properly. (I wrote that later, and was IMO quite a bit smarter about it. I sadly didn't have time to fix up V1...)
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You just want to do the same hack i did or know about it?
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create a branch for each Dataset-experiment pair. e.g. iris_1 ... iris_9
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here git is your friend, especially if you inevitably screw up.
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e.g. echo git\ checkout\ iris_{1..9}\;\ git\ cherry-pick\ 7ced1e1\; will create a command for applying the commit 7ced1e1 to every iris branch.
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Adapt the build.sbatch and run.sbatch and **commit them**!
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clone the branch you committed to on the cluster.
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create the required folders! If you forget the output one, slurm will fail silently!
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Make sure to sbatch an adapted **build.sbatch before run.sbatch**!
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build.sbatch will need to be adapted for and run on every node you will use!
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Otherwise stuff WILL break!
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sbatch run.sbatch
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You can use squeue to monitor progress.
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A huge slew of raw data will be dumped into the output Folder. The error files contain results, the output files stats during training.
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On how to process these results, see: https://merl.dnshome.de/git/Hans/haga-graphics
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