return the expectation and its gridient in the same function exp'

[ywlds]

can we put the function exp' in YaoBlocks/src/autodiff/specializes.jl to support return the expection and its gridients? I try this by adding the energy = copy(outδ)'*copy(out), but I feel the parameters or energy dose not change in the iteration. Is there is something wrong due to the parameters is changed somehow? iteration and Loss function energy is : 1 -6.783714426018552 + 0.0im iteration and Loss function energy is : 2 -6.783714426018552 + 0.0im iteration and Loss function energy is : 3 -6.783714426018552 + 0.0im iteration and Loss function energy is : 4 -6.783714426018552 + 0.0im iteration and Loss function energy is : 5 -6.783714426018552 + 0.0im iteration and Loss function energy is : 6 -6.783714426018552 + 0.0im iteration and Loss function energy is : 7 -6.783714426018552 + 0.0im iteration and Loss function energy is : 8 -6.783714426018552 + 0.0im iteration and Loss function energy is : 9 -6.783714426018552 + 0.0im iteration and Loss function energy is : 10 -6.783714426018552 + 0.0im iteration and Loss function energy is : 11 -6.783714426018552 + 0.0im iteration and Loss function energy is : 12 -6.783714426018552 + 0.0im

I use the optimizier lbfgs. previously before I change the function expect' seems everything ok.

function lbfgs_optimize(circuit::AbstractBlock{N}, hc, niter::Int) where N iteration = 0 function f(params, grad)

reg = zero_state(N) |> dispatch!(circuit, params)

    _, grad1 =  expect'(hc,zero_state(N)=>circuit)
    print("grad1 is ",grad1)
    for i= 1: length(grad1)
        grad[i] = grad1[i]
    end
    loss = expect(hc, reg) |> real
    println("Loss function is", loss)
    iteration += 1
    loss
end
opt = Opt(:LD_LBFGS, nparameters(circuit))
min_objective!(opt, f)
maxeval!(opt, niter)

print("here is ok")

ftol_rel!(opt,1e-7) # default this value

cost, params, info = optimize(opt, parameters(circuit))

pl = zero_state(N) |> circuit |> probs

print("info is", info)

print("iteration time is ", iteration)

cost, params, info, iteration

end

This is the origin expect' function(except the comment)

function (::Adjoint{Any,typeof(expect)})(op::AbstractBlock, circuit::Pair{<:ArrayReg,<:AbstractBlock}) reg, c = circuit

println("try to modify")

out = copy(reg) |> c
outδ = copy(out) |> op

energy = copy(outδ)'*copy(out)

#println("energy is ", energy)
(in, inδ), paramsδ = apply_back((out, outδ), c)
return inδ => paramsδ .* 2

end

[ywlds]

I think i found the mistakes, there, the function just need to update the parameters, using dispatch!(circuit, params) then it works.