Replication of Knet.jl issue#74

replicate_issue74.jl

using Knet

function softmax(x,axis=0)
    return exp(logp(x, axis))
end

function loss(wbindings)
    out = zeros()
    for arg in 2:4
        progargs = softmax(wbindings[arg-1],1)
        out = progargs
     end
     return out
end

w = Any[Float32[0.562734,-0.33637],Float32[-1.21529,1.04808,-0.789922],Float32[-0.332284,0.325839,0.0651071,-0.618155]]
lossgradient = grad(loss)

lossgradient(w)