ReLU has a sharp corner at , where its slope jumps straight from to with nothing in between. Softplus is a smooth stand-in that looks like ReLU from a distance but rounds the corner off:
Far to the left it hugs . Far to the right it hugs the line . Near it bends smoothly, so its slope changes gradually instead of jumping.
Task: write softplus_with_slope(values). For each pre-activation in the list values, produce the pair [softplus(x), slope], where slope is the derivative of softplus at . Round both numbers to 4 decimal places and return the pairs as a list, in the same order as the input. An empty list gives an empty list.
The layer this runs in sees pre-activations as large as . Your function must return correct, finite numbers for them, and must not crash.