Before revision:  Dynamically trained under such structural constraint, we can slice a narrower sub-model during inference whose run-time memory and computational operation consumption is roughly quadratic to the width controlled by a single parameter slice rate.
After revision:  Dynamically trained under such structural constraint, we can slice a narrower sub-model with fewer groups can be readily deployed for efficiency whose computation is roughly quadratic to the width controlled by a single parameter slice rate.