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DEEP-BO Guide

Welcome!

We are delighted to introduce DEEP-BO, an automatic hyperparameter optimization framework. We hope DEEP-BO will be helpful to optimize your DNN model.

This guide is organized as thus:

Table of Contents

• 1. Introduction
• 2. Preparation
  • 2.1. Hyperparameter Configuration
  • 2.2. Evaluation Task
• 3. How to Run
  • 3.1. Run Configuration
  • 3.2. Runner Interface
  • 3.3. Web Interface
  • 3.4. Parallelization
• 4. Trouble Shootings
  • 4.1. Debugging Errors
  • 4.2. Networking Issues

If you are using DEEP-BO for the first time, it is recommended that you read the overview in Chapter 1. When your model is prepared and wants to be optimized, start to read Chapter 2. You can learn how to design the hyperparameter configuration of your model, and to make to train your model independently.

When your preparation is successfully finished, read Chapter 3 to optimize the hyperparameters of yours. In Run Configuration section, the parameters of DEEP-BO to support various system configurations are described. Here you can learn how to configure it for your system. It is recommended that you run DEEP-BO in single BO mode for the first time(Runner Interface). Even if you have plan to run parallel BO, it is a good idea to check for errors in single mode. This reduces the possibility of fatal errors that can occur during long-term parallel execution. The section Web Interface describes the communication mechanism through the REST API. Refer to the Parallelization section to configure a parallel BO system consist of many processors.

NOTICE

4. Trouble shootings is under construction. If you have any issue or suggestions, create an issue in 'Issues' of top menu. Frequency asked and solved issues will be revealed in this section.

Acknowledgements

Thanks to ch-shin for your update suggestion.

(SPECIAL THANKS TO BE UPDATED)

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT).