changed some variable names

ext/SIMDiffKernelAbstractions.jl

@@ -250,22 +250,22 @@ end
 
 @kernel function kerh(y1,y2,@Const(f),@Const(itr),@Const(x),@Const(adj1),@Const(adj2))
     I = @index(Global)
-    SIMDiff.hrpass0(f.f(itr[I], SIMDiff.TripleSource(x)), f.comp2, y1, y2, SIMDiff.offset2(f,I), 0, adj1, adj2)
+    SIMDiff.hrpass0(f.f(itr[I], SIMDiff.SecondAdjointNodeSource(x)), f.comp2, y1, y2, SIMDiff.offset2(f,I), 0, adj1, adj2)
 end
 
 @kernel function kerh2(y1,y2,@Const(f),@Const(itr),@Const(x),@Const(adjs1),@Const(adj2))
     I = @index(Global)
-    SIMDiff.hrpass0(f.f(itr[I], SIMDiff.TripleSource(x)), f.comp2, y1, y2, SIMDiff.offset2(f,I), 0, adjs1[SIMDiff.offset0(f,itr,I)], adj2)
+    SIMDiff.hrpass0(f.f(itr[I], SIMDiff.SecondAdjointNodeSource(x)), f.comp2, y1, y2, SIMDiff.offset2(f,I), 0, adjs1[SIMDiff.offset0(f,itr,I)], adj2)
 end
 
 @kernel function kerj(y1,y2,@Const(f),@Const(itr),@Const(x),@Const(adj))
     I = @index(Global)
-    SIMDiff.jrpass(f.f(itr[I], SIMDiff.DualSource(x)), f.comp1, SIMDiff.offset0(f,itr,I), y1, y2, SIMDiff.offset1(f,I), 0, adj)
+    SIMDiff.jrpass(f.f(itr[I], SIMDiff.AdjointNodeSource(x)), f.comp1, SIMDiff.offset0(f,itr,I), y1, y2, SIMDiff.offset1(f,I), 0, adj)
 end
 
 @kernel function kerg(y,@Const(f),@Const(itr),@Const(x),@Const(adj))
     I = @index(Global)
-    SIMDiff.grpass(f.f(itr[I], SIMDiff.DualSource(x)), f.comp1, y, SIMDiff.offset1(f,I), 0, adj)
+    SIMDiff.grpass(f.f(itr[I], SIMDiff.AdjointNodeSource(x)), f.comp1, y, SIMDiff.offset1(f,I), 0, adj)
 end
 
 @kernel function kerf(y,@Const(f),@Const(itr),@Const(x))

src/SIMDiff.jl

@@ -3,8 +3,6 @@ module SIMDiff
 import NLPModels
 
 include("graph.jl")
-include("dual.jl")
-include("triple.jl")
 include("register.jl")
 include("functionlist.jl")
 include("function.jl")
@@ -14,6 +12,6 @@ include("hessian.jl")
 include("nlp.jl")
 include("templates.jl")
 
-export data, variable, objective, constraint, constraint!, WrapperModel
+export data, variable, objective, constraint, constraint!
 
 end # module SIMDiffes

src/function.jl

@@ -19,11 +19,11 @@ function Func(gen::Base.Generator, o0=0, o1=0, o2=0)
     f = gen.f(p)
 
 
-    d = f(Identity(),DualSource(NaNSource{Float16}()))
+    d = f(Identity(),AdjointNodeSource(NaNSource{Float16}()))
     y1 = []
     SIMDiff.grpass(d,nothing,y1,nothing,0,NaN16)
 
-    t = f(Identity(),TripleSource(NaNSource{Float16}()))
+    t = f(Identity(),SecondAdjointNodeSource(NaNSource{Float16}()))
     y2 = []
     SIMDiff.hrpass0(t,nothing,y2,nothing,nothing,0,NaN16,NaN16)
 

src/gradient.jl

@@ -1,53 +1,53 @@
-@inbounds @inline function drpass(d::D, y, adj) where D <: Dual1
+@inbounds @inline function drpass(d::D, y, adj) where D <: AdjointNode1
     offset = drpass(d.inner, y, adj * d.y)
     nothing
 end
-@inbounds @inline function drpass(d::D, y, adj) where D <: Dual2
+@inbounds @inline function drpass(d::D, y, adj) where D <: AdjointNode2
     offset = drpass(d.inner1, y, adj * d.y1)
     offset = drpass(d.inner2, y, adj * d.y2)
     nothing
 end
-@inbounds @inline function drpass(d::D, y, adj) where D <: DualVar
+@inbounds @inline function drpass(d::D, y, adj) where D <: AdjointNodeVar
     y[d.i] += adj
     nothing
 end
 @inbounds @inline function drpass(f::F, x, y, adj) where F <: Func
 end
 function gradient!(y,f,x, adj)
     @simd for k in eachindex(f.itr)
-        drpass(f.f.f(f.itr[k],DualSource(x)), y, adj)
+        drpass(f.f.f(f.itr[k],AdjointNodeSource(x)), y, adj)
     end
     return y
 end
 
 
-@inbounds @inline function grpass(d::D, comp, y, o1, cnt, adj) where D <: Dual1
+@inbounds @inline function grpass(d::D, comp, y, o1, cnt, adj) where D <: AdjointNode1
     cnt = grpass(d.inner, comp, y, o1, cnt, adj * d.y)
     return cnt
 end
-@inbounds @inline function grpass(d::D, comp, y, o1, cnt, adj) where D <: Dual2
+@inbounds @inline function grpass(d::D, comp, y, o1, cnt, adj) where D <: AdjointNode2
     cnt = grpass(d.inner1, comp, y, o1, cnt, adj * d.y1)
     cnt = grpass(d.inner2, comp, y, o1, cnt, adj * d.y2)
     return cnt
 end
-@inbounds @inline function grpass(d::D, comp, y, o1, cnt, adj) where D <: DualVar
+@inbounds @inline function grpass(d::D, comp, y, o1, cnt, adj) where D <: AdjointNodeVar
     y[o1 + comp(cnt += 1)] += adj
     return cnt
 end
 
-@inbounds @inline function grpass(d::DualVar, comp::Nothing, y, o1, cnt, adj) # despecialization
+@inbounds @inline function grpass(d::AdjointNodeVar, comp::Nothing, y, o1, cnt, adj) # despecialization
     push!(y,d.i)
     return (cnt += 1)
 end
-@inbounds @inline function grpass(d::D, comp, y::V, o1, cnt, adj) where {D <: DualVar, V <: AbstractVector{Tuple{Int,Int}}}
+@inbounds @inline function grpass(d::D, comp, y::V, o1, cnt, adj) where {D <: AdjointNodeVar, V <: AbstractVector{Tuple{Int,Int}}}
     ind = o1 + comp(cnt += 1)
     y[ind] = (d.i,ind)
     return cnt
 end
 
 function sgradient!(y,f,x, adj)
     @simd for k in eachindex(f.itr)
-        grpass(f.f.f(f.itr[k], DualSource(x)), f.itr.comp1, y, offset1(f,k), 0, adj)
+        grpass(f.f.f(f.itr[k], AdjointNodeSource(x)), f.itr.comp1, y, offset1(f,k), 0, adj)
     end
     return y
 end

src/graph.jl

@@ -1,8 +1,8 @@
 abstract type AbstractIndex end
 abstract type AbstractNode end
 abstract type AbstractPar <: AbstractNode end
-abstract type AbstractDual end
-abstract type AbstractTriple  end
+abstract type AbstractAdjointNode end
+abstract type AbstractSecondAdjointNode  end
 
 struct Var{I} <: AbstractNode
     i::I
@@ -58,3 +58,69 @@ struct NaNSource{T} <: AbstractVector{T} end
 @inbounds (v::ParIndexed)(i::Identity,x) = NaN16 # despecialized
 @inbounds (v::Par)(i::Identity,x) = NaN16 # despecialized
 @inbounds (v::Var)(i::Identity,x) = x[v.i] # despecialized
+
+
+struct AdjointNode1{F, T, I} <: AbstractAdjointNode
+    x::T
+    y::T
+    inner::I
+end
+struct AdjointNode2{F, T, I1,I2} <: AbstractAdjointNode
+    x::T
+    y1::T
+    y2::T
+    inner1::I1
+    inner2::I2
+end
+struct AdjointNodeVar{I,T} <: AbstractAdjointNode
+    i::I
+    x::T
+end
+struct AdjointNodeSource{T, VT <: AbstractVector{T}}
+    inner::VT
+end
+struct AdjointNodeNullSource end
+
+@inline AdjointNode1(f::F,x::T,y,inner::I) where {F,T,I} = AdjointNode1{F,T,I}(x,y,inner)
+@inline AdjointNode2(f::F,x::T,y1,y2,inner1::I1,inner2::I2) where {F,T,I1,I2} = AdjointNode2{F,T,I1,I2}(x,y1,y2,inner1,inner2)
+
+
+AdjointNodeSource(::Nothing) = AdjointNodeNullSource()
+
+@inbounds @inline Base.getindex(x::I,i) where I <: AdjointNodeNullSource = AdjointNodeVar(i,NaN16)
+@inbounds @inline Base.getindex(x::I,i) where I <: AdjointNodeSource = AdjointNodeVar(i, x.inner[i])
+
+
+struct SecondAdjointNode1{F, T, I} <: AbstractSecondAdjointNode
+    x::T
+    y::T
+    h::T
+    inner::I
+end
+struct SecondAdjointNode2{F, T, I1,I2} <: AbstractSecondAdjointNode
+    x::T
+    y1::T
+    y2::T
+    h11::T
+    h12::T
+    h22::T
+    inner1::I1
+    inner2::I2
+end
+
+struct SecondAdjointNodeVar{I,T} <: AbstractSecondAdjointNode
+    i::I
+    x::T
+end
+struct SecondAdjointNodeSource{T, VT <: AbstractVector{T}}
+    inner::VT
+end
+
+@inline SecondAdjointNode1(f::F,x::T,y,h,inner::I) where {F,T,I} = SecondAdjointNode1{F,T,I}(x,y,h,inner)
+@inline SecondAdjointNode2(f::F,x::T,y1,y2,h11,h12,h22,inner1::I1,inner2::I2) where {F,T,I1,I2} = SecondAdjointNode2{F,T,I1,I2}(x,y1,y2,h11,h12,h22,inner1,inner2)
+
+struct SecondAdjointNodeNullSource end
+SecondAdjointNodeSource(::Nothing) = SecondAdjointNodeNullSource()
+
+@inbounds @inline Base.getindex(x::I,i) where I <: SecondAdjointNodeNullSource = SecondAdjointNodeVar(i,NaN)
+@inbounds @inline Base.getindex(x::I,i) where I <: SecondAdjointNodeSource = SecondAdjointNodeVar(i, x.inner[i])