# Documentation NASLib!

NASLib is a Neural Architecture Search (NAS) library. Its purpose is to facilitate NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces.

Warning

This library is under construction and there is no official release yet. Feel free to play around and have a look but be aware that the APIs will be changed until we have a first release.

NASLib has been used to run an extensive comparison of 31 performance predictors. The results were published in the paper How Powerful are Performance Predictors in Neural Architecture Search? For more details take a look at its seperate README.

## Usage

    search_space = SimpleCellSearchSpace()

    optimizer = DARTSOptimizer(config)
    optimizer.adapt_search_space(search_space)

    trainer = Trainer(optimizer, config)
    trainer.search()        # Search for an architecture
    trainer.evaluate()      # Evaluate the best architecture

Online Documentation Contents:

- Manual
  - Requirements
  - Setting up a virtual environment
  - Setting up NASLib
- Example
- License
- Citing NASLib
- Contributions