Why using this following simple model: with pm.Model() as linear_model: data_x = pm.Data('data_x', matrix_train) data_y = pm.Data('data_y', matrix_positive.flatten()) beta = pm.Normal('beta', mu=0, sd=20, shape=nfeatures) sigma = pm.HalfNormal('sigma', sd=20) mu = pm.Determ…

Looks like memory issue to me as well - sometimes pm.math.dot has weird memory issue - could you try doing tt.sum(data_x * beta[None, ...], axis=-1)

Hi, What do you mean by “gets stuck” exactly? Do you get an error message somewhere?

Nothing, just stuck. I’m using it on a jupyter notebook. It’s very weird because I don’t have this issue with other models. However for this model I have around 5k samples, maybe memory issues with 2 cores ? But then it would thrown an error or something.

Yeah, looks like memory issue – I think I remember that when using multiple cores, the data need to be actually kind of copied to each core. To verify this hypothesis, you can try diminishing the number of samples you give your models, to see if this runs. This won’t fix the issue though, contrary…

Sampling gets stuck with more than one core

Questions

perone May 30, 2020, 10:40am 6

It was the tt.mul indeed, so it seems to be related with memory issues. Thanks a lot @AlexAndorra and @junpenglao !

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Sampling gets stuck with more than one core

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