Hi,
I’m a new user. Pyro seems like a very useful tool, but I’m having trouble handling missing data. I’ve want to use poutine.mask to ignore missing data as in done in the answer to this question: Modeling missingness indicators.
When I try doing this in the SVI tutorial, I get a type error, but my mask is definitely of type torch.uint8, not NoneType
ValueError: Expected mask to be a boolean but got <class ‘NoneType’>
Trace Shapes:
Param Sites:
Sample Sites:
latent_fairness dist |
value |
Here’s a colab link to the modified tutorial: Google Colab
Am I using poutine.mask correctly?
Thanks!