Overview

1. Basic usage examples demonstrate fundamental usage. Learn how to perform Hyperparameter Optimization (HPO), Neural Architecture Search (NAS), and Joint Architecture and Hyperparameter Search (JAHS). Understand how to analyze runs on a basic level.

2. Efficiency examples showcase how to enhance efficiency in NePS. Learn about expert priors, multi-fidelity, and parallelization to streamline your pipeline and optimize search processes.

3. Convenience examples show tensorboard compatibility and its integration, explore the compatibility with PyTorch Lightning, see the declarative API, understand file management within the evaluate pipeline function used in NePS.

4. Experimental examples tailored for NePS contributors. These examples provide insights and practices for experimental scenarios.