Use value_and_gradient for efficiency and update dependency versions

Co-authored-by: yebai <3279477+yebai@users.noreply.github.com>

Author: Copilot

examples/1-mauna-loa/script.jl

@@ -229,9 +229,8 @@ function optimize_loss(loss, θ_init; optimizer=default_optimizer, maxiter=1_000
     backend = AutoMooncake()
     function fg!(F, G, x)
         if F !== nothing && G !== nothing
-            val = loss_packed(x)
-            grad = only(gradient(loss_packed, backend, x))
-            G .= grad
+            val, grad = value_and_gradient(loss_packed, backend, x)
+            G .= only(grad)
             return val
         elseif G !== nothing
             grad = only(gradient(loss_packed, backend, x))

examples/3-parametric-heteroscedastic/script.jl

@@ -54,9 +54,8 @@ end;
 backend = AutoMooncake()
 function objective_and_gradient(F, G, flat_θ)
     if G !== nothing
-        val = objective(flat_θ)
-        grad = only(gradient(objective, backend, flat_θ))
-        copyto!(G, grad)
+        val, grad = value_and_gradient(objective, backend, flat_θ)
+        copyto!(G, only(grad))
         if F !== nothing
             return val
         end

test/Project.toml

@@ -17,13 +17,13 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 Aqua = "0.8"
-DifferentiationInterface = "0.5, 0.6"
+DifferentiationInterface = "0.7"
 Distributions = "0.19, 0.20, 0.21, 0.22, 0.23, 0.24, 0.25"
 Documenter = "1"
 FillArrays = "0.11, 0.12, 0.13, 1"
 FiniteDifferences = "0.9.6, 0.10, 0.11, 0.12"
 LinearAlgebra = "1"
-Mooncake = "0.3, 0.4, 0.5"
+Mooncake = "0.4"
 PDMats = "0.11"
 Pkg = "1"
 Plots = "1"