Let’s say I have two latent variables y,z in model() with factorized priors, e.g.
y = pyro.sample(“y”, …), z = pyro.sample(“z”, …).
How would I able to model the approximate posterior of y and z together, e.g. using a normalizing flow. If I do something like
sample = pyro.sample(“sample”, …)
y = sample
z = sample
I will have an error similar to this:
log_r_term = log_r_term - guide_trace.nodes[name][“log_prob”]