Hi!
For the Normal distribution, one can use rsample() allowing computation of the gradient through a sample. This does not exist for a Categorical distribution.
How can we do the same?
Example:
mu, sigma = neural_net(input)
sample = Normal(mu, sigma).rsample()

I would like to do something like:
probs = neural_net(input)
sample = Categorical(probs).rsample()