I don’t see this in the documentation, but is there a way to get predictions from a bambi model to run in parallel? It seems that there is no way to pass a number of cores into the function like with fit() at the moment, so is it possible to break up the new data and give each chunk to a different core to process?
.predict() calls a method that mostly uses numpy arrays to compute the precitions (i.e. it does not call any PyMC related function). In my experience this results in faster computations. Do you have a use-case where this is slow and you’re thinking about going parallel?
I’m not sure about the following, but doesn’t NumPy automatically perform some parallel stuff when computing dot products? (.predict() uses dot products basically)