i have a function` f(x1,x2)`

. sometimes i need dfdx1 , sometimes i need dfdx2, those cases are easy with the existing ForwardDiff API. the problem is when i need the two properties at once. gradient is one way, calling each time dfdx1 and dxdx2 is fine too, but is there a way to calculate two derivatives at once in one function evaluation? some example code to test

```
function f(x1,x2)
res = x1+x2
for i = 1:15
res = sin(res)+x1 - cos(x2)
end
return res
end
function df_grad(f,x1,x2)
x = [x1,x2]
_f = x-> f(xx[1],xx[2])
g = ForwardDiff.gradient(_f,x)
return g[1], g[2]
end
function df_twice(f,x1,x2)
return ForwardDiff.derivative(x->f(x,x2),x1) , ForwardDiff.derivative(x->f(x1,x),x2)
end
```