That’s right. But the thing is I want to implement dropout after each kernel filter. Currently the dropout layer works over the entire previous layer, but according to the paper "Bayesian CNN with approximate bernouilli variational inference, we’ll need to implement dropout after each filter during convolution.
So for that purpose I’ll need to modify the dropout implementation itself which is why I wanted to know where the apply() function would be available in order to change that.
Thanks!