Hey @Gireesh_Ramji
To better answer this question here’s some things things that will help. One is more cersion numbers for the major packages, at least PyMC and Pytensor.
For debugging here’s two strategies. Have you tried fixing certain distributions to specific values and seeing if sampling workings then? Perhaps n_exclusive_id_assumption
Another is passing in specific test point values and seeing if you get a logp and gradient back in regions you expect. This is a screenshot from my book. The API is PyMC3, so I don’t think the code 1:1 will work, but the idea is the same. Check if the model is returning reasonable values in places you think it should.
