Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
This is the official PyTorch implementation for the paper Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets (ICLR 2021) : https://openreview.net/forum?id=rkQuFUmUOg3.
Abstract
Despite the success of recent Neural Architecture Search (NAS) methods on various tasks which have shown to output networks that largely outperform human-designed networks, conventional NAS methods have mostly tackled the optimization of searching for the network architecture for a single task (dataset), which does not generalize well across multiple tasks (datasets). Moreover, since such task-specific methods search for a neural architecture from scratch for every given task, they incur a large computational cost, which is problematic when the time and monetary budget are limited. In this paper, we propose an efficient NAS framework that is trained once on