Get MAP parameters and value


#1

Sorry for the noob question, but I am having trouble understanding the standard pipeline that Edward seems to use. I am following the MAP tutorial, and I seem to have it running, but I don’t understand how to obtain the results of the maximisation. The “run” method returns nothing, and I don’t know what other methods I am supposed to call to get the results. This is what I have:

import edward as ed
import edward.models as em

mu = em.Uniform(low=-5., high=5.)
X = em.Normal(loc=mu, scale=1.)
inference = ed.MAP([mu],data={X: 3.})
inference.run()

How do I get the actual inferred parameters and posterior value from this?


#2

Is this not a standard thing? I looked through all the examples and docs but I still have no idea how to do basic things like this. Or are these some standard tensorflow objects that it is assumed I already know how to use?