Shypd.aiThe largest open index of AI toolsNASLib is an AI Frameworks & Infra tool that facilitates Neural Architecture Search (NAS) research. It provides interfaces to state-of-the-art NAS search spaces and optimizers, enabling modular design and extension of NAS methods.
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NASLib is a modular and flexible framework designed to facilitate Neural Architecture Search (NAS) research by providing a common codebase to the community. It offers high-level abstractions for designing and reusing search spaces, along with interfaces to various benchmarks and evaluation pipelines. This enables researchers to implement and extend state-of-the-art NAS methods with minimal code. The library's modular nature allows for easy innovation on individual components, such as defining new search spaces while reusing existing optimizers, or proposing new optimizers with current search spaces. Developed by the AutoML Freiburg group, NASLib is continuously updated with new search spaces, optimizers, and benchmarks.
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