Avoid extra objective evaluation in OptimizationOptimisers

Evaluate the objective through the optimizer loop without a discarded pre-loop call, so stochastic objectives keep the expected RNG sequence and reported evaluation counts match actual work.

Preserve positive fractional maxiters values that round to zero by evaluating the initial objective only when the loop performs no iterations, and count that fallback evaluation.

Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>

Author: ChrisRackauckas

lib/OptimizationOptimisers/Project.toml

@@ -24,6 +24,7 @@ Reexport = "1.2.2"
 SciMLBase = "2.122.1, 3"
 julia = "1.10"
 ComponentArrays = "0.15"
+CommonSolve = "0.2"
 ForwardDiff = "0.10, 1"
 Lux = "1"
 MLDataDevices = "1"
@@ -38,6 +39,7 @@ SciMLTesting = "09d9d899-5365-40a9-917a-5f67fddea283"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
+CommonSolve = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 MLDataDevices = "7e8f7934-dd98-4c1a-8fe8-92b47a384d40"
@@ -48,4 +50,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["SciMLTesting", "ComponentArrays", "ForwardDiff", "Lux", "MLDataDevices", "MLUtils", "Random", "Test", "Zygote", "Printf", "SafeTestsets", "Pkg"]
+test = ["SciMLTesting", "ComponentArrays", "CommonSolve", "ForwardDiff", "Lux", "MLDataDevices", "MLUtils", "Random", "Test", "Zygote", "Printf", "SafeTestsets", "Pkg"]

lib/OptimizationOptimisers/src/OptimizationOptimisers.jl

@@ -61,7 +61,7 @@ function SciMLBase.__solve(cache::OptimizationCache{O}) where {O <: AbstractRule
     G = copy(θ)
 
     local x, min_err, min_θ
-    x = cache.f(cache.u0, first(data))
+    x = nothing
     min_err = typemax(eltype(real(cache.u0))) #dummy variables
     min_opt = 1
     min_θ = cache.u0
@@ -151,6 +151,10 @@ function SciMLBase.__solve(cache::OptimizationCache{O}) where {O <: AbstractRule
             )
         end
     end
+    if isnothing(x)
+        x = cache.f(cache.u0, first(data))
+        fevals += 1
+    end
     cache.progress && @logmsg(
         LogLevel(-1), "Optimization",
         _id = progress_id, message = "Done", progress = 1.0

lib/OptimizationOptimisers/test/core_tests.jl

@@ -1,4 +1,7 @@
 using OptimizationOptimisers, ForwardDiff, OptimizationBase
+using CommonSolve: solve
+using Optimisers
+using SciMLBase: OptimizationFunction, OptimizationProblem
 using Test
 using Zygote
 using Lux, MLUtils, Random, ComponentArrays, Printf, MLDataDevices
@@ -117,6 +120,36 @@ using Lux, MLUtils, Random, ComponentArrays, Printf, MLDataDevices
         )
     end
 
+    @testset "Objective evaluations" begin
+        objective_calls = Ref(0)
+        fg_calls = Ref(0)
+        function counted_objective(x, p)
+            objective_calls[] += 1
+            return sum(abs2, x)
+        end
+        function counted_fg!(G, x, p)
+            fg_calls[] += 1
+            G .= 2 .* x
+            return sum(abs2, x)
+        end
+
+        optf = OptimizationFunction(counted_objective; fg = counted_fg!)
+        prob = OptimizationProblem(optf, ones(2), nothing)
+        sol = solve(prob, Optimisers.Adam(); maxiters = 3, save_best = false)
+
+        @test sol.stats.iterations == 3
+        @test fg_calls[] == sol.stats.iterations
+        @test objective_calls[] == 0
+
+        objective_calls[] = 0
+        fg_calls[] = 0
+        sol = solve(prob, Optimisers.Adam(); maxiters = 0.4, save_best = false)
+
+        @test sol.stats.iterations == 0
+        @test sol.stats.fevals == objective_calls[] == 1
+        @test fg_calls[] == 0
+    end
+
     @test_throws ArgumentError sol = solve(prob, Optimisers.Adam())
 end