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Refactor transformer to use _eval in tests #67

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Merged
blegat merged 2 commits into from
May 21, 2026
Merged

Refactor transformer to use _eval in tests #67

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1cc6c34
Refactor transformer to use _eval in tests
blegat May 21, 2026
c5e0da5
enable alloc
blegat May 21, 2026
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23 changes: 8 additions & 15 deletions test/JuMP.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -166,7 +166,12 @@ function test_parse_moi()
return
end

function _eval(model::JuMP.GenericModel{T}, func, x) where {T}
function _eval(
model::JuMP.GenericModel{T},
func,
x;
x_grad = T.(collect(1:length(x))),
) where {T}
mode = ArrayDiff.Mode{Vector{T}}()
ad = ArrayDiff.model(mode)
MOI.Nonlinear.set_objective(ad, JuMP.moi_function(func))
Expand All @@ -182,7 +187,6 @@ function _eval(model::JuMP.GenericModel{T}, func, x) where {T}
fill!(evaluator.backend.last_x, NaN)
@test 0 == @allocated MOI.eval_objective(evaluator, x)
end
x_grad = T.(collect(1:8))
g = zero(x)
MOI.eval_objective_gradient(evaluator, g, x_grad)
if VERSION >= v"1.12"
Expand All @@ -191,7 +195,7 @@ function _eval(model::JuMP.GenericModel{T}, func, x) where {T}
end
MOI.Nonlinear.set_objective(ad, nothing)
@test isnothing(ad.objective)
return sizes, val, g
return sizes, val, g, evaluator
end

function _test_neural(
Expand Down Expand Up @@ -646,21 +650,10 @@ function _check_transformer_loss(build_loss; seq = 2, d_emb = 2)
model = Model()
@variable(model, x[1:seq, 1:d_emb], container = ArrayDiff.ArrayOfVariables)
loss = build_loss(x)
mode = ArrayDiff.Mode()
ad = ArrayDiff.model(mode)
MOI.Nonlinear.set_objective(ad, JuMP.moi_function(loss))
evaluator = MOI.Nonlinear.Evaluator(
ad,
mode,
JuMP.index.(JuMP.all_variables(model)),
)
MOI.initialize(evaluator, [:Grad])
nvar = JuMP.num_variables(model)
x_pt = randn(nvar)
val = MOI.eval_objective(evaluator, x_pt)
_, val, g, evaluator = _eval(model, loss, x_pt; x_grad = x_pt)
@test isfinite(val)
g = zeros(nvar)
MOI.eval_objective_gradient(evaluator, g, x_pt)
@test all(isfinite, g)
h = 1e-6
g_fd = zeros(nvar)
Expand Down
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