pymc-devs/pymc

Compile single function in InferenceDataConverter._extract_log_likelihood

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#5,256 opened on Dec 12, 2021

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Description

After #5245 we no longer need to create one function per observed variable, which may be more efficient.

https://github.com/pymc-devs/pymc/blob/10523ef548d68848d6408f78d52fefea9be5c521/pymc/backends/arviz.py#L266-L271

This requires some understanding of how to feed the right information to the InferenceData object, possibly with some extra room for improvements in InferenceDataConverter.log_likelihood_vals_point which has a TODO as well:

https://github.com/pymc-devs/pymc/blob/10523ef548d68848d6408f78d52fefea9be5c521/pymc/backends/arviz.py#L240-L245

Contributor guide

Research direction
Investigate the current implementation of InferenceDataConverter. extract log likelihood and log likelihood vals point. Understand how to compile a single function for all observed variables by modifying the model graph and ensure the InferenceData object is correctly populated.
Tech stack
python
Domain
backend
Issue type
Refactor
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
PythonPyMC
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40