Before revision:  In this paper, we try to solve this issue, and propose two effective approaches , namely 1) mutual information  based estimation and 2) reconstruction loss based estimation , to measure the hardness of learning the representation for a word and determine its computational depth.
After revision:  In this paper, we get rid of the halting unit and estimate the required depths in advance, which yields a faster depth-adaptive model. Specifically, two approaches are proposed to explicitly measure the hardness of input words and estimate corresponding adaptive depth , namely 1) mutual information based estimation and 2) reconstruction loss based estimation , to measure the hardness of learning the representation for a word and determine its computational depth.