use `HessianConfig` to calculate gradients?

Hello,

Recently i came across with a problem in which already had a hessian cache, (HessianConfig + DiffResults.HessianResult), but it seems there aren't any methods for calculating for using HessianConfig (and HessianResult) when calculating gradients (of the same function with the same number and type of arguments).

I did this dirty hack to allow calculating gradients with HessianConfig + HessianResult:

hresult,hconfig = cache    
h_jconfig = hconfig.jacobian_config
seeds = h_jconfig.seeds
duals = h_jconfig.duals[1]
gconfig = ForwardDiff.GradientConfig{Nothing,eltype(aux),length(seeds),typeof(duals)}(seeds,duals)
gresult = ForwardDiff.MutableDiffResult(result.value,(result.derivs[1],))

It works for me, but it could be generalized (by passing the adequate function argument, for example)

It would be much easier to just do ForwardDiff.gradient!(hresult,f,x,hconfig) instead.

Start by tracing the existing HessianConfig, DiffResults.HessianResult, GradientConfig, and gradient! entry points to understand how cached Jacobian configuration is used. Compare the proposed HessianConfig-to-gradient path with the existing gradient result handling, then verify that gradient!(hresult, f, x, hconfig) produces the same gradients while reusing the cache.