I’ve defined a model that fits my data fairly well:
def model(data): blah blah blah... trace = pm.sample() return trace
The data is an array of (~300,2) floats. I would like to run this model over and over with different data. However, there’s a lot of overhead that seems to happen before the actual sampling. Is there any way to cache that and just rerun?