Katib for hyperparameter tuning
Katib is a scalable, Kubernetes-native AutoML platform that facilitates both hyperparameter tuning and NAS. Figure 6.13 shows the design of Katib. To learn more about how it works, readers should refer to Katib: A Distributed General AutoML Platform on Kubernetes:
Figure 6.13 – The design of Katib as a general AutoML system (Figure 2 from the paper: https://www.usenix.org/system/files/opml19papers-zhou.pdf)
Katib supports hyperparameter adjustment through the command line via a YAML file specification, as well as the Jupyter Notebook and the Python SDK. It also has a graphical UI for specifying tuning settings and visualizing the results, as shown here:
Figure 6.14 – The graphical interface of Katib
Katib allows you to choose a measure and whether to reduce or increase it. You can choose the hyperparameters you want to tweak and see the results of the entire experiment and individual...