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.