Check idata dims/coords for consistency before sampling begins · pymc-devs/pymc#7891

(11 comments) (1 reaction) (0 assignees)Python (7,926 stars) (1,902 forks)batch import

beginner friendlyhelp wantedmaintenanceshape problem

Description

This is a painful gotcha I get hit by once in a while. If you have inconsistencies between the model coords and variable shapes, PyMC will still happy sample (often for hours, ask me how I know), then error out when it gets to the final step of building the idata.

I don't think there needs to be complex logic to validate static shapes etc, I'm thinking we could do a smoke test on the model initial point (or a single prior draw) to make sure it can be converted to an idata, and raise before sampling if not.

Contributor guide

Tech stack: python
Domain: backend
Issue type: feature
Difficulty: 3
Estimated time: 1-2 days
Activity status: active
Clarity: clear
Prerequisites: basic PyMC knowledgeInferenceData structure understanding
Newbie friendliness: 65
Research direction: Examine the PyMC sampling pipeline, particularly the `sample()` function and how InferenceData is created. Look for where the model initial point is handled. The goal is to add a validation step that attempts a single prior draw and checks it can be converted to an idata before sampling begins. Review the discussion in issue #7891 for any additional constraints or proposed approaches. Consider the existing test suite for sampling to see where to add a test.