Skip to content

even more fixes and tests for mixed type AD #46

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
lkdvos merged 1 commit into from
Jun 1, 2026
Merged

even more fixes and tests for mixed type AD #46

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 11 additions & 11 deletions ext/VectorInterfaceEnzymeExt.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,15 @@ using Enzyme
using Enzyme.EnzymeCore
using Enzyme.EnzymeCore: EnzymeRules

function project_add!(C, A, α)
TC = Base.promote_op(+, scalartype(A), scalartype(α))
return if !(TC <: Real) && scalartype(C) <: Real
add!(C, real(add!(zerovector(C, TC), A, α)))
else
add!(C, A, α)
end
end

"""
project_scalar(x::Number, dx::Number)

Expand Down Expand Up @@ -104,7 +113,7 @@ function EnzymeRules.reverse(
α::Annotation{<:Number},
) where {RT}
Aval, αval = cache
!isa(A, Const) && !isa(C, Const) && add!(A.dval, C.dval, conj(αval))
!isa(A, Const) && !isa(C, Const) && project_add!(A.dval, C.dval, conj(αval))
Δα = if !isa(α, Const) && !isa(C, Const)
project_scalar(α.val, inner(Aval, C.dval))
elseif !isa(α, Const)
Expand Down Expand Up @@ -186,7 +195,7 @@ function EnzymeRules.reverse(
else
nothing
end
!isa(A, Const) && !isa(C, Const) && add!(A.dval, C.dval, conj(αval))
!isa(A, Const) && !isa(C, Const) && project_add!(A.dval, C.dval, conj(αval))
!isa(C, Const) && scale!(C.dval, conj(βval))
return (nothing, nothing, Δα, Δβ)
end
Expand Down Expand Up @@ -215,15 +224,6 @@ function EnzymeRules.forward(
end
end

function project_add!(C, A, α)
TC = Base.promote_op(+, scalartype(A), scalartype(α))
return if !(TC <: Real) && scalartype(C) <: Real
add!(C, real(add!(zerovector(C, TC), A, α)))
else
add!(C, A, α)
end
end


function EnzymeRules.augmented_primal(
config::EnzymeRules.RevConfigWidth{1},
Expand Down
22 changes: 11 additions & 11 deletions ext/VectorInterfaceMooncakeExt.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,15 @@ For example, we might compute a complex `dx` but only require the real part.
project_scalar(x::Number, dx::Number) = oftype(x, dx)
project_scalar(x::Real, dx::Complex) = project_scalar(x, real(dx))

function project_add!(C, A, α)
TC = Base.promote_op(+, scalartype(A), scalartype(α))
return if !(TC <: Real) && scalartype(C) <: Real
add!(C, real(add!(zerovector(C, TC), A, α)))
else
add!(C, A, α)
end
end

_needs_tangent(x) = _needs_tangent(typeof(x))
_needs_tangent(::Type{T}) where {T <: Number} =
Mooncake.rdata_type(Mooncake.tangent_type(T)) !== NoRData
Expand Down Expand Up @@ -72,7 +81,7 @@ function Mooncake.rrule!!(::CoDual{typeof(scale!)}, C_ΔC::CoDual, A_ΔA::CoDual

function scale_pullback(::NoRData)
copy!(C, C_cache)
add!(ΔA, ΔC, conj(α))
project_add!(ΔA, ΔC, conj(α))
Δαr = _needs_tangent(α) ? project_scalar(α, inner(A, ΔC)) : NoRData()
zerovector!(ΔC)
return NoRData(), NoRData(), NoRData(), Δαr
Expand Down Expand Up @@ -114,7 +123,7 @@ function Mooncake.rrule!!(::CoDual{typeof(add!)}, C_ΔC::CoDual, A_ΔA::CoDual,

Δαr = _needs_tangent(α) ? project_scalar(α, inner(A, ΔC)) : NoRData()
Δβr = _needs_tangent(β) ? project_scalar(β, inner(C, ΔC)) : NoRData()
add!(ΔA, ΔC, conj(α))
project_add!(ΔA, ΔC, conj(α))
scale!(ΔC, conj(β))

return NoRData(), NoRData(), NoRData(), Δαr, Δβr
Expand All @@ -140,15 +149,6 @@ end
# inner
# -----

function project_add!(C, A, α)
TC = Base.promote_op(+, scalartype(A), scalartype(α))
return if !(TC <: Real) && scalartype(C) <: Real
add!(C, real(add!(zerovector(C, TC), A, α)))
else
add!(C, A, α)
end
end

@is_primitive DefaultCtx Tuple{typeof(inner), AbstractArray, AbstractArray}

function Mooncake.rrule!!(::CoDual{typeof(inner)}, A_ΔA::CoDual, B_ΔB::CoDual)
Expand Down
9 changes: 5 additions & 4 deletions test/enzyme.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -61,13 +61,14 @@ eltypes = (Float64, ComplexF64)
end
end

@testset "add ($T)" for T in eltypes
@testset "add ($Tx, $Ty)" for Ty in eltypes, Tx in eltypes
n = 12
atol = rtol = n * precision(T)
atol = rtol = n * max(precision(Tx), precision(Ty))
T = Base.promote_op(+, Tx, Ty)

# Vector
x = randn(T, n)
y = randn(T, n)
x = randn(Tx, n)
y = randn(Ty, n)
α = randn(T)
β = randn(T)
for Tα in (Const, Active), Tβ in (Const, Active)
Expand Down
10 changes: 5 additions & 5 deletions test/mooncake.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -48,13 +48,13 @@ eltypes = (Float32, Float64, ComplexF64)
Mooncake.TestUtils.test_rule(rng, scale!!, my, mx, α; atol, rtol, is_primitive = false)
end

@testset "add pullbacks ($T)" for T in eltypes
@testset "add ($Tx, $Ty)" for Ty in eltypes, Tx in eltypes
n = 12
atol = rtol = n * precision(T)

atol = rtol = n * max(precision(Tx), precision(Ty))
T = Base.promote_op(+, Tx, Ty)
# Vector
x = randn(T, n)
y = randn(T, n)
x = randn(Tx, n)
y = randn(Ty, n)
α = randn(T)
β = randn(T)
Mooncake.TestUtils.test_rule(rng, add, y, x, α, β; atol, rtol, is_primitive = false)
Expand Down
Loading