Implicit AD: Corrected NestedAD error checking, added error tests and custom error displays (#518)

* Fixed NestedAD check

* Implement AD error checks

* Add custom showerror functions for NestedADError and MultipleTagError

* fixed error with AD error checking tests

Author: Garren-H

src/base/errors.jl

@@ -92,8 +92,14 @@ struct NestedADError <: Exception
     msg::String
 end
 NestedADError() = NestedADError("")
+function Base.showerror(io::IO, e::NestedADError)
+    print(io, "NestedADError: ", e.msg)
+end
 
 struct MultipleTagError <: Exception
     msg::String
 end
-MultipleTagError() = MultipleTagError("")
+MultipleTagError() = MultipleTagError("")
+function Base.showerror(io::IO, e::MultipleTagError)
+    print(io, "MultipleTagError: ", e.msg)
+end

src/methods/differentials.jl

@@ -280,7 +280,7 @@ function nested_ad_check(a::A) where A
     AT = eltype(a)
     if AT <: ForwardDiff.Dual
         V = ForwardDiff.valtype(AT)
-        V isa ForwardDiff.Dual && throw(NestedADError("Found nested Duals of type $AT. This is currently not supported in implicit differentiation."))
+        V <: ForwardDiff.Dual && throw(NestedADError("Found nested Duals of type $AT. This is currently not supported in implicit differentiation."))
     end
     return nothing
 end
@@ -319,4 +319,4 @@ end
 function implicit_ad_check(a::Tuple)
     nested_ad_check(a)
     multiple_tag_ad_check(a)
-end
+end

test/test_differentials.jl

@@ -82,6 +82,29 @@ end
         @test all(ddp[2] .≈ dp)
         @test all(ddp[1] .≈ d2p)
     end
+    
+    @testset "AD Error Checks" begin
+        import ForwardDiff
+        import Clapeyron: MultipleTagError, NestedADError, __gradients_for_root_finders
+        f_test(x,tups) = tups[1]*tups[2]*x # just a generic function to check error handling
+        tag1 = ForwardDiff.Tag{:tag1,Float64}
+        tag2 = ForwardDiff.Tag{:tag2,Float64}
+        Tdual1 = ForwardDiff.Dual{tag1,Float64,1}
+        Tdual2 = ForwardDiff.Dual{tag2,Float64,1}
+        parts = ForwardDiff.Partials{1,Float64}((1.0,))
+        theta1,theta2 = 0.5,2.0;
+        x = 0.0
+        x_dual = ForwardDiff.Dual{tag1,Float64,1}(x,parts)
+        tups_primal = (theta1,theta2)
+        tups_Dual2 = (Tdual1(theta1,parts),Tdual2(theta2,parts))
+        tups_nestedDual = (ForwardDiff.Dual{tag2,Tdual1,1}(Tdual1(theta1,parts)),theta2)
+        # Test multiple tag error
+        @test_throws MultipleTagError __gradients_for_root_finders(x,tups_Dual2,tups_primal,f_test)
+        # Test nested dual error
+        @test_throws NestedADError __gradients_for_root_finders(x,tups_nestedDual,tups_primal,f_test)
+        # Test dual as x error 
+        @test_throws ErrorException __gradients_for_root_finders(x_dual,(theta1,theta2),tups_primal,f_test)
+    end
 end