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Don't change order of variables when NLPBlock is used #850

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Aug 23, 2019
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Don't change order of variables when NLPBlock is used #850

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61 changes: 37 additions & 24 deletions src/Utilities/copy.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -267,6 +267,21 @@ function pass_constraints(
end
end

function copy_free_variables(dest::MOI.ModelLike, idxmap::IndexMap, vis_src, copy_variables::Function)
if length(vis_src) != length(keys(idxmap.varmap))
vars = copy_variables(dest, length(vis_src) - length(idxmap.varmap))
i = 1
for vi in vis_src
if !haskey(idxmap.varmap, vi)
idxmap.varmap[vi] = vars[i]
i += 1
end
end
@assert i == length(vars) + 1
@assert length(vis_src) == length(idxmap.varmap)
end
end

function default_copy_to(dest::MOI.ModelLike, src::MOI.ModelLike)
Base.depwarn("default_copy_to(dest, src) is deprecated, use default_copy_to(dest, src, true) instead or default_copy_to(dest, src, false) if you do not want to copy names.", :default_copy_to)
default_copy_to(dest, src, true)
Expand All @@ -292,24 +307,29 @@ function default_copy_to(dest::MOI.ModelLike, src::MOI.ModelLike, copy_names::Bo
vector_of_variables_types = [S for (F, S) in constraint_types
if F == MOI.VectorOfVariables]

vector_of_variables_not_added = [
copy_vector_of_variables(dest, src, idxmap, S)
for S in vector_of_variables_types
]
single_variable_not_added = [
copy_single_variable(dest, src, idxmap, S)
for S in single_variable_types
]

if length(vis_src) != length(keys(idxmap.varmap))
# Copy free variables
variables_not_added = setdiff(Set(vis_src), keys(idxmap.varmap))
vars = MOI.add_variables(dest, length(variables_not_added))
for (vi, var) in zip(variables_not_added, vars)
idxmap.varmap[vi] = var
end
# The `NLPBlock` assumes that the order of variables does not change (#849)
if MOI.NLPBlock() in MOI.get(src, MOI.ListOfModelAttributesSet())
vector_of_variables_not_added = [
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Why do this only for NLPBlock and not always?

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You mean first determine how each variable is going to be added (either free or constrained) and then add them in the same order (hence splitting the add_variables call in separate one for each contiguous block) so that they are added in the same order even if some variables are contrained ?

Note that with #846, the need to not change the order of the variables might go away. The assumption that variables have indices 1 to n that is used by NLP in MOI does not match the rest of the MOI ecosystem and it will go away once NonlinearExpressionFunction implements map_variables.

MOI.get(src, MOI.ListOfConstraintIndices{MOI.VectorOfVariables, S}())
for S in vector_of_variables_types
]
single_variable_not_added = [
MOI.get(src, MOI.ListOfConstraintIndices{MOI.SingleVariable, S}())
for S in single_variable_types
]
else
vector_of_variables_not_added = [
copy_vector_of_variables(dest, src, idxmap, S)
for S in vector_of_variables_types
]
single_variable_not_added = [
copy_single_variable(dest, src, idxmap, S)
for S in single_variable_types
]
end

copy_free_variables(dest, idxmap, vis_src, MOI.add_variables)

# Copy variable attributes
pass_attributes(dest, src, copy_names, idxmap, vis_src)

Expand Down Expand Up @@ -652,14 +672,7 @@ function allocate_load(dest::MOI.ModelLike, src::MOI.ModelLike, copy_names::Bool
allocate_single_variable(dest, src, idxmap, S)
end

if length(vis_src) != length(keys(idxmap.varmap))
# Allocate free variables
variables_not_added = setdiff(Set(vis_src), keys(idxmap.varmap))
vars = allocate_variables(dest, length(variables_not_added))
for (vi, var) in zip(variables_not_added, vars)
idxmap.varmap[vi] = var
end
end
copy_free_variables(dest, idxmap, vis_src, allocate_variables)

# Allocate variable attributes
pass_attributes(dest, src, copy_names, idxmap, vis_src, allocate)
Expand Down
22 changes: 22 additions & 0 deletions test/Utilities/copy.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -57,3 +57,25 @@ end
MOIT.failcopytestca(mock)
MOIT.copytest(mock, MOIU.Model{Float64}())
end

struct DummyEvaluator <: MOI.AbstractNLPEvaluator end

@testset "Create variables in same ordering when NLPBlock is used (#849)" begin
model = MOIU.UniversalFallback(MOIU.Model{Float64}())
a = MOI.add_variable(model)
b, c = MOI.add_variables(model, 2)
x, cx = MOI.add_constrained_variable(model, MOI.GreaterThan(0.0))
y, cy = MOI.add_constrained_variables(model, MOI.Nonnegatives(1))
nlp_data = MOI.NLPBlockData(
[MOI.NLPBoundsPair(0.0, 1.0) for i in 1:5],
DummyEvaluator(), false)
MOI.set(model, MOI.NLPBlock(), nlp_data)
copy = MOIU.UniversalFallback(MOIU.Model{Float64}())
index_map = MOIU.default_copy_to(copy, model, true)
for vi in [a, b, c, x, y[1]]
@test index_map[vi] == vi
end
for ci in [cx, cy]
@test index_map[ci] == ci
end
end