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[Test] Minor fixes in nonlinear tests #1599

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Merged
merged 5 commits into from
Sep 15, 2021
Merged

[Test] Minor fixes in nonlinear tests #1599

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7b4903f
[Test] Minor fixes in nonlinear tests
frapac Sep 9, 2021
1e3d87b
Update src/Test/test_nonlinear.jl
odow Sep 9, 2021
6332b4b
fix test_nonlinear_hs071_NLPBlockDual with MAX_SENSE
frapac Sep 14, 2021
31bf16e
fix test_nonlinear_hs071_NLPBlockDual with MockOptimizer
frapac Sep 14, 2021
fa13e22
fix formatting failure
frapac Sep 14, 2021
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72 changes: 55 additions & 17 deletions src/Test/test_nonlinear.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,14 @@ function MOI.eval_constraint_jacobian(::HS071, J, x)
return
end

function MOI.eval_constraint_jacobian_transpose_product(::HS071, y, x, w)
y[1] = (x[2] * x[3] * x[4]) * w[1] + (2 * x[1]) * w[2]
y[2] = (x[1] * x[3] * x[4]) * w[1] + (2 * x[2]) * w[2]
y[3] = (x[1] * x[2] * x[4]) * w[1] + (2 * x[3]) * w[2]
y[4] = (x[1] * x[2] * x[3]) * w[1] + (2 * x[4]) * w[2]
return
end

function MOI.eval_hessian_lagrangian(d::HS071, H, x, σ, μ)
@assert d.enable_hessian
# Again, only lower left triangle
Expand Down Expand Up @@ -442,25 +450,46 @@ function test_nonlinear_hs071_NLPBlockDual(model::MOI.ModelLike, config::Config)
@requires MOI.supports(model, MOI.NLPBlock())
@requires _supports(config, MOI.optimize!)
@requires MOI.supports(model, MOI.VariablePrimalStart(), MOI.VariableIndex)
v = MOI.add_variables(model, 4)
n_variables = 4
v = MOI.add_variables(model, n_variables)
l = [1.1, 1.2, 1.3, 1.4]
u = [5.1, 5.2, 5.3, 5.4]
start = [2.1, 2.2, 2.3, 2.4]
MOI.add_constraint.(model, v, MOI.GreaterThan.(l))
MOI.add_constraint.(model, v, MOI.LessThan.(u))
cl = MOI.add_constraint.(model, v, MOI.GreaterThan.(l))
cu = MOI.add_constraint.(model, v, MOI.LessThan.(u))
MOI.set.(model, MOI.VariablePrimalStart(), v, start)
lb, ub = [25.0, 40.0], [Inf, 40.0]
evaluator = MOI.Test.HS071(true)
block_data = MOI.NLPBlockData(MOI.NLPBoundsPair.(lb, ub), evaluator, true)
MOI.set(model, MOI.NLPBlock(), block_data)
MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
MOI.optimize!(model)
dual = MOI.get(model, MOI.NLPBlockDual())
@test isapprox(dual, [0.178761800, 0.985000823], config)
MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
MOI.optimize!(model)
dual = MOI.get(model, MOI.NLPBlockDual())
@test isapprox(dual, [0.0, -5.008488315], config)

for sense in [MOI.MIN_SENSE, MOI.MAX_SENSE]
MOI.set(model, MOI.ObjectiveSense(), sense)
MOI.optimize!(model)
# Get primal solution
x = MOI.get(model, MOI.VariablePrimal(), v)
# Get dual solution
con_dual = MOI.get(model, MOI.NLPBlockDual())
var_dual_lb = MOI.get(model, MOI.ConstraintDual(), cl)
var_dual_ub = MOI.get(model, MOI.ConstraintDual(), cu)

# Evaluate ∇f(x)
g = zeros(n_variables)
MOI.eval_objective_gradient(evaluator, g, x)
# Evaluate ∑ μᵢ * ∇cᵢ(x)
jtv = zeros(n_variables)
MOI.eval_constraint_jacobian_transpose_product(
evaluator,
jtv,
x,
con_dual,
)

# Test that (x, μ, νl, νᵤ) satisfies stationarity condition
# σ ∇f(x) - ∑ μᵢ * ∇cᵢ(x) - νₗ - νᵤ = 0
σ = (sense == MOI.MAX_SENSE) ? -1.0 : 1.0
@test isapprox(σ .* g, jtv .+ var_dual_ub .+ var_dual_lb, config)
end
return
end

Expand All @@ -476,7 +505,11 @@ function setup_test(
MOI.Utilities.mock_optimize!(
mock,
config.optimal_status,
[1.1, 1.57355205213644, 2.6746837915674373, 5.4],
[1.1, 1.5735520521364397, 2.6746837915674373, 5.4],
(MOI.VariableIndex, MOI.GreaterThan{Float64}) =>
[28.590703804861093, 0.0, 0.0, 0.0],
(MOI.VariableIndex, MOI.LessThan{Float64}) =>
[0.0, 0.0, 0.0, -5.582550550234756],
)
MOI.set(mock, MOI.NLPBlockDual(), [0.178761800, 0.985000823])
end,
Expand All @@ -490,11 +523,16 @@ function setup_test(
1.7612041983937636,
3.6434497419346723,
],
(MOI.VariableIndex, MOI.GreaterThan{Float64}) =>
[0.0, 0.0, 0.0, 0.0],
(MOI.VariableIndex, MOI.LessThan{Float64}) =>
[0.0, 0.0, 0.0, 0.0],
)
MOI.set(mock, MOI.NLPBlockDual(), [0.0, -5.008488315])
end,
)
return
model.eval_variable_constraint_dual = false
return () -> model.eval_variable_constraint_dual = true
end

"""
Expand All @@ -513,15 +551,15 @@ function test_nonlinear_objective_and_moi_objective_test(
@requires _supports(config, MOI.optimize!)
@requires MOI.supports(model, MOI.VariablePrimalStart(), MOI.VariableIndex)
lb = [1.0]
ub = [2.0]
ub = [1.0]
block_data = MOI.NLPBlockData(
MOI.NLPBoundsPair.(lb, ub),
FeasibilitySenseEvaluator(true),
true,
)
x = MOI.add_variable(model)
@test MOI.get(model, MOI.NumberOfVariables()) == 1
# Avoid starting at zero because it's a critial point.
# Avoid starting at zero because it's a critical point.
MOI.set(model, MOI.VariablePrimalStart(), x, 1.5)
MOI.set(model, MOI.NLPBlock(), block_data)
MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
Expand Down Expand Up @@ -566,15 +604,15 @@ function test_nonlinear_without_objective(model::MOI.ModelLike, config::Config)
@requires _supports(config, MOI.optimize!)
@requires MOI.supports(model, MOI.VariablePrimalStart(), MOI.VariableIndex)
lb = [1.0]
ub = [2.0]
ub = [1.0]
block_data = MOI.NLPBlockData(
MOI.NLPBoundsPair.(lb, ub),
FeasibilitySenseEvaluator(true),
false,
)
x = MOI.add_variable(model)
@test MOI.get(model, MOI.NumberOfVariables()) == 1
# Avoid starting at zero because it's a critial point.
# Avoid starting at zero because it's a critical point.
MOI.set(model, MOI.VariablePrimalStart(), x, 1.5)
MOI.set(model, MOI.NLPBlock(), block_data)
MOI.optimize!(model)
Expand Down