flex-direction:row; 
    }









Takeaways


We showed how to run a fully automated multi-objective Neural Architecture Search using Ax.


Using the Ax Scheduler, we were able to run the optimization automatically in a fully asynchronous fashion - this can be done locally (as done in the tutorial) or by deploying trials remotely to a cluster (simply by changing the TorchX scheduler configuration).


The state-of-the-art multi-objective Bayesian optimization algorithms available in Ax allowed us to efficiently explore the tradeoffs between validation accuracy and model size.


Advanced Functionality
Ax has a number of other advanced capabilities that we did not discuss in our tutorial. Among these are the following:
Early Stopping