Variational Inference of Mixture models?

Specific Domains Probabilistic programming
5

One follow on question. If you could please explain why K is required in the function signature. Consider the two nearly-identical models (the only difference being whether K is given as a keyword argument.)

@model gmm(x, K=3) = begin
    N = length(x)
    μ ~ filldist(Normal(0,1), K)
    w ~ Dirichlet(K, 1)
    for ii in 1:N
        x[ii] ~ MixtureModel(Normal, μ, w)
    end
end

@model gmm2(x) = begin
    K = 3
    N = length(x)
    μ = filldist(Normal(0,1), K)
    w ~ Dirichlet(K, 1)
    for ii in 1:N
        x[ii] ~ MixtureModel(Normal, μ, w)
    end
end

The following code executes successfully

model = gmm(Y)
advi = ADVI(10, 1000)
q = vi(model, advi)

Changing the first line above to model=gmm2(Y) gives an error. How can this be when gmm(Y) and gmm2(Y) appear to be functionally equivalent?