Scheduling machine learning jobs to run in sequence

This might save you a few minutes of research time: I sometimes need to set up a number of Keras (or TensorFlow) runs to occur in sequence to run overnight, while I am away from work, etc. I don't want the processing to stop if any single job fails.

I use Task Spooler that is in Ubuntu and other Linux distros and can be installed on MacOS using "brew install task-spooler". Note, on Ubuntu, the command is tsp


You can schedule any shell command command to run by prepending "ts". Examples:

cd run1
ts python variational_auto.py
cd ../run2
ts python lstm_text_model.py
ts # get a list of all queued, running, and finished processes
ts -c 3 # get the stdout for process 3
ts -t 3 # get the tail output for process 3
ts -C # clear the list of finished jobs

This simple setup is not really appropriate for doing hyper parameter tuning but is useful to set up a series of runs.

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