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?