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16 changes: 14 additions & 2 deletions src/Nonlinear/ReverseAD/utils.jl
Original file line number Diff line number Diff line change
Expand Up @@ -42,13 +42,25 @@ struct _UnsafeVectorView{T} <: DenseVector{T}
ptr::Ptr{T}
end

Base.getindex(x::_UnsafeVectorView, i) = unsafe_load(x.ptr, i + x.offset)
function Base.getindex(x::_UnsafeVectorView, i::Integer)
return unsafe_load(x.ptr, i + x.offset)
end

Base.getindex(x::_UnsafeVectorView, i::CartesianIndex{1}) = getindex(x, i[1])

function Base.setindex!(x::_UnsafeVectorView, value, i)
function Base.setindex!(x::_UnsafeVectorView, value, i::Integer)
# We don't need to worry about `value` being the right type here because
# x.ptr is a `::Ptr{T}`, so even though it is called `unsafe_store!`, there
# is still a type convertion that happens so that we're not just chucking
# the bits of value into `x.ptr`.
unsafe_store!(x.ptr, value, i + x.offset)
return value
end

function Base.setindex!(x::_UnsafeVectorView, value, i::CartesianIndex{1})
return setindex!(x, value, i[1])
end

Base.length(v::_UnsafeVectorView) = v.len

Base.size(v::_UnsafeVectorView) = (v.len,)
Expand Down
59 changes: 59 additions & 0 deletions test/Nonlinear/ReverseAD.jl
Original file line number Diff line number Diff line change
Expand Up @@ -1304,6 +1304,65 @@ function test_toposort_subexpressions()
return
end

function test_eval_user_defined_operator_ForwardDiff_gradient!()
model = MOI.Nonlinear.Model()
x = MOI.VariableIndex.(1:4)
p = MOI.Nonlinear.add_parameter(model, 2.0)
ex = MOI.Nonlinear.add_expression(model, :($p * $(x[1])))
ψ(x) = sin(x)
t(x, y) = x + 3y
MOI.Nonlinear.register_operator(model, :ψ, 1, ψ)
MOI.Nonlinear.register_operator(model, :t, 2, t)
MOI.Nonlinear.add_constraint(
model,
:($ex^3 + sin($(x[2])) / ψ($(x[2])) + t($(x[3]), $(x[4]))),
MOI.LessThan(0.0),
)
d = MOI.Nonlinear.Evaluator(model, MOI.Nonlinear.SparseReverseMode(), x)
MOI.initialize(d, [:Jac])
X = [1.1, 1.2, 1.3, 1.4]
g = [NaN]
MOI.eval_constraint(d, g, X)
@test only(g) ≈ 17.148
@test MOI.jacobian_structure(d) == [(1, 1), (1, 2), (1, 3), (1, 4)]
J = [NaN, NaN, NaN, NaN]
MOI.eval_constraint_jacobian(d, J, X)
@test J ≈ [2.0^3 * 3.0 * 1.1^2, 0.0, 1.0, 3.0]
return
end

function test_eval_user_defined_operator_type_mismatch()
model = MOI.Nonlinear.Model()
x = MOI.VariableIndex.(1:4)
p = MOI.Nonlinear.add_parameter(model, 2.0)
ex = MOI.Nonlinear.add_expression(model, :($p * $(x[1])))
ψ(x) = sin(x)
t(x, y) = x + 3y
function ∇t(ret, x, y)
ret[1] = 1 # These are intentionally the wrong type
ret[2] = 3 // 1 # These are intentionally the wrong type
return
end
MOI.Nonlinear.register_operator(model, :ψ, 1, ψ, cos)
MOI.Nonlinear.register_operator(model, :t, 2, t, ∇t)
MOI.Nonlinear.add_constraint(
model,
:($ex^3 + sin($(x[2])) / ψ($(x[2])) + t($(x[3]), $(x[4]))),
MOI.LessThan(0.0),
)
d = MOI.Nonlinear.Evaluator(model, MOI.Nonlinear.SparseReverseMode(), x)
MOI.initialize(d, [:Jac])
X = [1.1, 1.2, 1.3, 1.4]
g = [NaN]
MOI.eval_constraint(d, g, X)
@test only(g) ≈ 17.148
@test MOI.jacobian_structure(d) == [(1, 1), (1, 2), (1, 3), (1, 4)]
J = [NaN, NaN, NaN, NaN]
MOI.eval_constraint_jacobian(d, J, X)
@test J ≈ [2.0^3 * 3.0 * 1.1^2, 0.0, 1.0, 3.0]
return
end

end # module

TestReverseAD.runtests()
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