Sorting is an important procedure in computer science. However, the argsort operator - which takes as input a vector and returns its sorting per-mutation - has a discrete image and thus zero gradients almost everywhere. This prohibits end-to-end, gradient-based learning of models that rely on the argsort operator. A natural way to overcome this problem is to replace the argsort operator with a continuous relaxation. Recent work has shown a number of ways to do this. However, the relaxations prop…