LDA implementation with pymc3

Questions
4

Categorical is not implemented to handle high dimensional p, so you need to carefully validate the shape and reshape the input parameters:

alpha = np.ones((1, K))
beta = np.ones((1, V))
with pm.Model() as model:
    thetas = pm.Dirichlet("thetas", a=alpha, shape=(D, K))
    phis = pm.Dirichlet("phis", a=beta, shape=(K, V))
    z = pm.Categorical("zx", p=thetas, shape=(W, D))
    w = pm.Categorical("wx", 
                       p=t.reshape(phis[z], (D*W, V)), 
                       observed=data.reshape(D*W))

Something like this seems to work, but you should doubt check to make sure the shape and reshape is behaving as intended.

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