I recently updated from pymc3 to pymc v5. I’m also using arviz version 0.17.1. I have a model with a large number of parameters and due to memory considerations, I’m trying to stick with MultiTrace instead of InferenceData by using trace = pm.sample(return_inferencedata=False). In previous versions …

Workarounds for `arviz` no longer supporting `MultiTrace`?

jessegrabowski January 16, 2025, 7:39am 5

Do we compute deterministics when return_inferencedata=False? That’s usually the culprit for out-of-memory errors

Topic		Replies	Views
Memory spike at the end of the MCMC sampling Questions	10	2681	July 15, 2022
Plotting a trace potentially causes my Python kernel to crash? Questions	9	1724	February 26, 2020
Coordinates in PyMC & InferenceData Objects Sharing arviz	0	388	June 15, 2022
Excessive memory - Multiple regression Questions	9	2931	October 24, 2017
Pm.sample result does not work with az.plot_trace or other az functions v5	9	1433	June 22, 2022