It seem to have both feature and a discrete number passed into next layer, which one did you think of first? or it is both by design?
Both the "feature" and the "selected output" are designed to be passed to the next layer.
I never even ran an ablation that disabled the stem features; I assume the network would still train without them, but since the previous layer has already computed the features, it would be wasteful not to reuse them. Retaining the stem features also lets DDN adopt the more efficient single-shot-generator architecture.
Another deeper reason is that, unlike diffusion models, DDN does not need the Markov-chain property between adjacent layers.