Hello everyone, I am new member user.

I have a question related to this topic: How to wrap a JAX function for use in PyMC — PyMC example gallery

In that example, the likelihood is used to estimate the parameters of the Hidden Markov Model (HMM). But, I do not understand what is the purpose of the gradient function within the HMM class. Is the gradient used for updating each parameter in each sample or iteration?

Thank you in advance!