Pm.sample() - How can the posterior be defined when there is no observed data to calculate the likelihood?

Had the same question @gms101 and thanks for the response @ricardoV94

One follow up question:
When we call pm.sample without observed data, the returned idata instance contains “posterior” and “sample_stats”. Given that we are sampling from the prior, would it make more sense to return an idata instance with “prior” populater, similar to what is obtained when calling sample_posterior_predictive?

In other words, should we expect the same behavior when pm.sample is queried with no observed data, as we would when calling pm.sample_prior_predictive?