AskML: How to compute marginals in Sum-Product Networks?

I remember reading some comments about Sum-Product Networks here on /r/MachineLearning, so I hope someone could help me understand this part.

I submitted the details of the question to CrossValidated: http://stats.stackexchange.com/questions/89682/how-to-compute-marginals-in-sum-product-networks

Basically, I'm trying to compute the posterior marginals of the sum nodes, i.e P(Y_k = i | e), where Y_k is a sum node, i is one of its child and e is the evidence, but for some reason I keep getting probabilities that don't depend on the evidence.

I would really appreciate if anyone could help me with this.