Review for NeurIPS paper: Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

Weaknesses: The search space is not the same as the google publications but similar to once-for-all. The se-ratio is 0.25 in this paper's code, the expansion rates are {4,6} in this paper and the maximum depth is 5 in every stage, slightly different. Thus, please report #params in Tab. 1. L120. In this paper, the author uses 2K images as the validation set (L212) and use the validation loss to train the meta-network M. I'm curious that the author claim that this step is time-consuming (L159), then how many iterations in total are used for updating M in this paper? The Kendall rank is important, and I prefer more results.