- aeppl.dists.create_discrete_mc_op(srng, size, Gammas, gamma_0)#
This returns a
Scanthat performs the follow:
states = categorical(gamma_0) for t in range(1, N):
states[t] = categorical(Gammas[t, state[t-1]])
The Aesara graph representing the above is wrapped in an
OpFromGraphso that we can easily assign it a specific log-probability.
TODO: Eventually, AePPL should be capable of parsing more sophisticated
Scan`s and producing nearly the same log-likelihoods, and the use of `OpFromGraphwill no longer be necessary.