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This script (dispatch_tasks.py) creates 3 tasks (task_script.py) with different hyper-parameters and a dataset and pushes these tasks into the database.
On your GPU servers (for testing, it can be a new terminal on your local machine), run tasks as shown in run_tasks.py.
This script pulls and runs pending tasks, and saves the models and results to the database.
When all tasks complete, the dispatcher (dispatch_tasks.py) then selects the best model according to its accuracy.
Save and load models
task_script.py shows how to save model.
dispatch_tasks.py shows how to find and load the model with the best testing accuracy.
Save and load datasets
dispatch_tasks.py shows how to save a dataset.
task_script.py show how to find and load a dataset.