in my current project my goal is to create a variety of bayesian models (ranging from simple spline models to GPs) in pymc for my data and to compare the results eventually. As I want to keep track of all the different runs of different models I have already executed, I am looking for an infrastructure that is able to track the following points:
- Prior model before inference
- Model parameters like mean and std of prior distributions
- Dataframe that was used for the run
- Resulting InferenceData object
Afterwards, the reinitiation of runs should be possible. I had a quick look into Mlflow which is absolutely capable of the last 3 points but doesn’t support pymc models which makes the first point a bit difficult. I am hoping to find a kind of all-in-one solution.
Any suggestions? Thanks in advance!