@berakrishn I am aware of two things that can inflate the runtime of pm.sample
in non-obvious ways:
- ArviZ re-evaluates the likelihood of all samples by default. If evaluation of your likelihood is expensive pass
idata_kwargs=dict(log_likelihood=False)
to turn it off - if the chains did not converge, the convergence diagnostics are slower to compute. Passing
compute_convergence_checks=False
disables them.
I recommend the latter until you found the right DE-MCMC(-Z) settings for your model.