Non-diagonal SDE adjoint

[ChrisRackauckas]

The current implementation of the adjoints on SDEs requires diagonal noise. We should make sure to work out the more general case and add handling for that.

[ChrisRackauckas]

I think it's something like:

if S.noiseterm
     vecjacobian!(dλ, λ, p, t, S, dy=dy)
     for (i, λi) in enumerate(λ)
       _, back = Zygote.pullback(y, prob.p) do u, p
         f(u, p, t)[:,i]
       end
       _,tmp2 = back(FillArrays.Fill(λi,length(λ)')
       dgrad[:,i] .= vec(tmp2)
     end
   else
     vecjacobian!(dλ, λ, p, t, S, dgrad=dgrad, dy=dy)
   end

[mschauer]

In support of this: Each of the columns of the noise matrix is scaled with dW[k] like the drift vector is scaled with dt. So by taking the total derivative, you expect a sum over terms which are scaled variants of what you get for an ODE adjoint.