Uh, let's look at my GHCi history...

It looks like I was last searching for 12-member sets of permutations of 7 which come close to generating every possible permutation of seven elements, as well as meeting a few other criteria, for an electronics project. It ended up being more like 10 lines plus comments, though, ~~plus a big table generated by GAP, which I formatted into a Haskell list using probably a line of Haskell plus file loading.~~

Unfortunately for providing code, me playing with the finished algorithm has eaten up my whole 100 lines of history. So, here's a two-liner I posted on Lemmy before, that implements a feed-forward neural net. It's not exactly what you asked for, but it gives you an idea.

layer layerInput layerWeights = map relu $ map sum $ map (zipWith (*) layerInput) layerWeights

foldl layer modelInput modelWeights

In practice, you might also need to define relu in another line:

relu x = if x > 0 then x else 0

Edit: No wait, I think that was a different problem related to the same project. There's another module attached that generates all permutations of n items. After breaking it up so it's a bit less write-only:

allPermutations :: Int -> [[Int]]
allPermutations 1 = [[0]]
allPermutations n = concat $ map (addItem $ allPermutations (n-1) ) [0..(n-1)]

addItem :: [[Int]]  -> Int -> [[Int]]
addItem old new = map (\y -> new : map (fitAround new) y) old

fitAround :: Int -> Int -> Int
fitAround n y
	| y >= n	= y+1
	| otherwise	= y