Finally, we want the length of each semantic capsule u i to represent the probability that u i 's semantic meaning is present in the current input, so we use a nonlinear "squash" function (Sabour et al., 2017) to limit its length in [0,1] as In the original capsule network, there is only one classification task and it uses class capsules to denote classes and their lengths as classification probabilities.
both datasets have a fixed training/test split.