Merge pull request #123 from avik-pal/ap/fix_adjoint

Patch Adjoint Sensitivity for Simple Nonlinear Solve Algorithms

Author: ChrisRackauckas

Project.toml

@@ -1,7 +1,7 @@
 name = "SimpleNonlinearSolve"
 uuid = "727e6d20-b764-4bd8-a329-72de5adea6c7"
 authors = ["SciML"]
-version = "1.3.1"
+version = "1.3.2"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -19,16 +19,19 @@ SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 StaticArraysCore = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
 
 [weakdeps]
+ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 PolyesterForwardDiff = "98d1487c-24ca-40b6-b7ab-df2af84e126b"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 
 [extensions]
+SimpleNonlinearSolveChainRulesCoreExt = "ChainRulesCore"
 SimpleNonlinearSolvePolyesterForwardDiffExt = "PolyesterForwardDiff"
 SimpleNonlinearSolveStaticArraysExt = "StaticArrays"
 
 [compat]
 ADTypes = "0.2.6"
 ArrayInterface = "7"
+ChainRulesCore = "1"
 ConcreteStructs = "0.2"
 DiffEqBase = "6.126"
 FastClosures = "0.3"
@@ -39,6 +42,6 @@ MaybeInplace = "0.1"
 PrecompileTools = "1"
 Reexport = "1"
 SciMLBase = "2.7"
-StaticArraysCore = "1.4"
 StaticArrays = "1"
+StaticArraysCore = "1.4"
 julia = "1.9"

ext/SimpleNonlinearSolveChainRulesCoreExt.jl

@@ -0,0 +1,21 @@
+module SimpleNonlinearSolveChainRulesCoreExt
+
+using ChainRulesCore, DiffEqBase, SciMLBase, SimpleNonlinearSolve
+
+# The expectation here is that no-one is using this directly inside a GPU kernel. We can
+# eventually lift this requirement using a custom adjoint
+function ChainRulesCore.rrule(::typeof(SimpleNonlinearSolve.__internal_solve_up),
+        prob::NonlinearProblem,
+        sensealg::Union{Nothing, DiffEqBase.AbstractSensitivityAlgorithm}, u0, u0_changed,
+        p, p_changed, alg, args...; kwargs...)
+    out, ∇internal = DiffEqBase._solve_adjoint(prob, sensealg, u0, p,
+        SciMLBase.ChainRulesOriginator(), alg, args...; kwargs...)
+    function ∇__internal_solve_up(Δ)
+        ∂f, ∂prob, ∂sensealg, ∂u0, ∂p, ∂originator, ∂args... = ∇internal(Δ)
+        return (∂f, ∂prob, ∂sensealg, ∂u0, NoTangent(), ∂p, NoTangent(), ∂originator,
+            ∂args...)
+    end
+    return out, ∇__internal_solve_up
+end
+
+end

src/SimpleNonlinearSolve.jl

@@ -50,18 +50,26 @@ include("ad.jl")
 ## Default algorithm
 
 # Set the default bracketing method to ITP
-function SciMLBase.solve(prob::IntervalNonlinearProblem; kwargs...)
-    return solve(prob, ITP(); kwargs...)
-end
-
-function SciMLBase.solve(prob::IntervalNonlinearProblem, alg::Nothing,
-        args...; kwargs...)
+SciMLBase.solve(prob::IntervalNonlinearProblem; kwargs...) = solve(prob, ITP(); kwargs...)
+function SciMLBase.solve(prob::IntervalNonlinearProblem, alg::Nothing, args...; kwargs...)
     return solve(prob, ITP(), args...; kwargs...)
 end
 
 # By Pass the highlevel checks for NonlinearProblem for Simple Algorithms
 function SciMLBase.solve(prob::NonlinearProblem, alg::AbstractSimpleNonlinearSolveAlgorithm,
-        args...; kwargs...)
+        args...; sensealg = nothing, u0 = nothing, p = nothing, kwargs...)
+    if sensealg === nothing && haskey(prob.kwargs, :sensealg)
+        sensealg = prob.kwargs[:sensealg]
+    end
+    new_u0 = u0 !== nothing ? u0 : prob.u0
+    new_p = p !== nothing ? p : prob.p
+    return __internal_solve_up(prob, sensealg, new_u0, u0 === nothing, new_p, p === nothing,
+        alg, args...; kwargs...)
+end
+
+function __internal_solve_up(_prob::NonlinearProblem, sensealg, u0, u0_changed, p,
+        p_changed, alg::AbstractSimpleNonlinearSolveAlgorithm, args...; kwargs...)
+    prob = u0_changed || p_changed ? remake(_prob; u0, p) : _prob
     return SciMLBase.__solve(prob, alg, args...; kwargs...)
 end
 

test/Project.toml

@@ -9,8 +9,10 @@ Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 PolyesterForwardDiff = "98d1487c-24ca-40b6-b7ab-df2af84e126b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 NonlinearProblemLibrary = "0.1.2"

test/adjoint.jl

@@ -0,0 +1,14 @@
+using ForwardDiff, SciMLSensitivity, SimpleNonlinearSolve, Test, Zygote
+
+@testset "Simple Adjoint Test" begin
+    ff(u, p) = u .^ 2 .- p
+
+    function solve_nlprob(p)
+        prob = NonlinearProblem{false}(ff, [1.0, 2.0], p)
+        return sum(abs2, solve(prob, SimpleNewtonRaphson()).u)
+    end
+
+    p = [3.0, 2.0]
+
+    @test only(Zygote.gradient(solve_nlprob, p)) ≈ ForwardDiff.gradient(solve_nlprob, p)
+end

test/runtests.jl

@@ -15,6 +15,7 @@ end
         @time @safetestset "Matrix Resizing Tests" include("matrix_resizing_tests.jl")
         @time @safetestset "Least Squares Tests" include("least_squares.jl")
         @time @safetestset "23 Test Problems" include("23_test_problems.jl")
+        @time @safetestset "Simple Adjoint Tests" include("adjoint.jl")
     end
 
     if GROUP == "CUDA"