Frequently Asked Questions

[junpenglao]

• Getting NaN or Inf during NUTS or VI (e.g., 'Bad initial energy: inf. The model might be misspecified., NaN occurred in optimization.)

Get nan or inf from model.logp (model.test point) is an attestation of incorrectly configured model?

A few thoughts: 1, In your model, the observed part you are doing: with model: ... mz = pm.Uniform("mz", lower=0, upper=1, observed=mz_freq) M = pm.Binomial("M", n=Yp, p=mz, observed=loss_shifte However, the node mz is not doing anything, since there is no prior on mz, in effect, this is equivalent to mz = mz_freq 2, Since we got -inf from model.logp (model.logp(model.test_point)), we want to identify which RV node is causing the problem. @aseyboldt suggest doing model.bijection.…

NaN occurred in optimization with NUTS

This is an issue I sometimes has as well, a few example on Github: FloatingPointError: NaN occurred in optimization with NUTS #2272 Issues getting variable in hierarchical model to update #2271 My first instinct is usually: model misspecification. For example, commenting on issue #2271: I would check the logp of each random variable and the model mu.logp(model.test_point) model.logp(model.test_point) Make sure that no logp is inf. Another quick try, is to reduce the learning rate (1e-3 i…