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Remove unsafe use of eval in symbolic.jl #10

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Merged
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Jun 13, 2022
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Remove unsafe use of eval in symbolic.jl #10

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26 changes: 10 additions & 16 deletions src/symbolic.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -20,47 +20,41 @@ function SymbolicFunction(f, _x::AbstractVector; hessian = false, sparse = false
if val isa Real
if sparse
sgrad = Symbolics.sparsejacobian([f(x)], x; simplify)
f_expr = Symbolics.build_function(sgrad, x)[1]
_g = eval(f_expr)
_g, _ = Symbolics.build_function(sgrad, x; expression = Val{false})
g = x -> vec(Matrix(T(_g(x))))
else
sgrad = Symbolics.jacobian([f(x)], x; simplify)
f_expr = Symbolics.build_function(sgrad, x)[1]
_g = eval(f_expr)
_g, _ = Symbolics.build_function(sgrad, x; expression = Val{false})
g = x -> vec(T(_g(x)))
end
if hessian
if sparse
shess = Symbolics.sparsejacobian(Base.invokelatest(g, x), x; simplify)
shess = Symbolics.sparsejacobian(g(x), x; simplify)
else
shess = Symbolics.jacobian(Base.invokelatest(g, x), x; simplify)
shess = Symbolics.jacobian(g(x), x; simplify)
end
h_expr = Symbolics.build_function(shess, x)[1]
_h = eval(h_expr)
_h, _ = Symbolics.build_function(shess, x; expression = Val{false})
h = x -> T(_h(x))
else
h = nothing
end
else
if sparse
sjac = Symbolics.sparsejacobian(f(x), x; simplify)
f_expr = Symbolics.build_function(sjac, x)[1]
_g = eval(f_expr)
_g, _ = Symbolics.build_function(sjac, x; expression = Val{false})
g = x -> Matrix(T(_g(x)))
else
sjac = Symbolics.jacobian(f(x), x; simplify)
f_expr = Symbolics.build_function(sjac, x)[1]
_g = eval(f_expr)
_g, _ = Symbolics.build_function(sjac, x; expression = Val{false})
g = x -> T(_g(x))
end
if hessian
if sparse
shess = Symbolics.sparsejacobian(vec(Base.invokelatest(g, x)), x; simplify)
shess = Symbolics.sparsejacobian(vec(g(x)), x; simplify)
else
shess = Symbolics.jacobian(vec(Base.invokelatest(g, x)), x; simplify)
shess = Symbolics.jacobian(vec(g(x)), x; simplify)
end
h_expr = Symbolics.build_function(shess, x)[1]
_h = eval(h_expr)
_h, _ = Symbolics.build_function(shess, x; expression = Val{false})
h = x -> reshape(T(_h(x)), length(val), N, N)
else
h = nothing
Expand Down
19 changes: 18 additions & 1 deletion test/symbolic.jl
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@@ -1,3 +1,16 @@
function _test_function_scoping()
model = Model()
addvar!(model, [0.0], [1.0])
set_objective!(model, x -> x[1])
add_eq_constraint!(model, x -> x[1])
return NonconvexIpopt.optimize(
symbolify(model),
IpoptAlg(),
[0.0];
options = IpoptOptions(),
)
end

@testset "SymbolicFunction" begin
@testset "Derivatives - simplify = $simplify, sparse = $sparse" for simplify in (false, true), sparse in (false, true)
f = SymbolicFunction(sum, rand(3); hessian = false, simplify, sparse)
Expand Down Expand Up @@ -30,6 +43,10 @@
sym_model = symbolify(m)
r = NonconvexIpopt.optimize(sym_model, alg, [1.234, 2.345], options = options)
@test abs(r.minimum - sqrt(8/27)) < 1e-6
@test norm(r.minimizer - [1/3, 8/27]) < 1e-6
@test norm(r.minimizer - [1/3, 8/27]) < 1e-6
end
@testset "function-scope" begin
r = _test_function_scoping()
@test abs(r.minimum) < 1e-6
end
end