We have a variable
y that’s three dimensional, PxRxC (precincts, races, candidates). In the model, P is a plate, R is to_event, and C is multinomial, meaning that pyro thinks of it as a PxR array of C vectors:
with pyro.plate('precincts',P): y = pyro.sample('y', dist.Multinomial(N,logits=logits).to_event(1))
In the guide, I’m doing some auxiliary sampling to figure out what y’s value should be, so when I get to actually sampling y itself, I’m using a delta distribution:
pyro.sample("y", dist.Delta(y).to_event(2) ) #Doesn't work
Unfortunately, to_event grabs two dimensions on the right, when what I want it to do is skip the rightmost (multinomial) dimension and grab the next two.
What can I do?