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AssertionError: k == rinfo.nnz + N #2897
Description
Activity
MWE, or just any standalone example, would be greatly appreciated.
I've been mucking around with this, and I can't get the assert to trigger. Nothing seems obviously wrong reading through the code, so I guess I need an example.
Here is the model.
On my side, this works on v1.46 but not v1.47 where I get the assertion error.Thanks! I can reproduce:
julia> using Revise julia> using JuMP, Ipopt julia> model = read_from_file("/Users/odow/Downloads/model.mof.json"; use_nlp_block = false) A JuMP Model ├ solver: none ├ objective_sense: MIN_SENSE │ └ objective_function_type: NonlinearExpr ├ num_variables: 195 ├ num_constraints: 312 │ ├ NonlinearExpr in MOI.EqualTo{Float64}: 100 │ ├ AffExpr in MOI.EqualTo{Float64}: 11 │ ├ QuadExpr in MOI.EqualTo{Float64}: 50 │ ├ VariableRef in MOI.GreaterThan{Float64}: 88 │ ├ VariableRef in MOI.LessThan{Float64}: 55 │ └ VariableRef in MOI.Parameter{Float64}: 8 └ Names registered in the model: none julia> set_optimizer(model, Ipopt.Optimizer) julia> optimize!(model) ERROR: AssertionError: k == rinfo.nnz + N Stacktrace: [1] _indirect_recover_structure(rinfo::MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:447
Working on this now.
julia> using JuMP, Ipopt julia> begin model = Model(Ipopt.Optimizer) @variable(model, x[1:7]) @objective( model, Min, x[1]*x[5] + x[2]*x[4] + x[2]*x[6] + x[3]*x[5] + (x[1]*x[4]+x[3]*x[6])*x[7] ) optimize!(model) end ERROR: AssertionError: k == rinfo.nnz + N
Is the sparsity detection correct? Are the parentheses in the last term necessary?
Simpler and pure MOI. All bilinear terms appear necessary.
julia> import MathOptInterface as MOI julia> begin nlp = MOI.Nonlinear.Model() x = MOI.VariableIndex.(1:6) MOI.Nonlinear.set_objective( nlp, Expr( :call, :+, :($(x[1]) * $(x[4])), :($(x[1]) * $(x[5])), :($(x[2]) * $(x[4])), :($(x[2]) * $(x[6])), :($(x[3]) * $(x[5])), :($(x[3]) * $(x[6])), ) ) backend = MOI.Nonlinear.SparseReverseMode() evaluator = MOI.Nonlinear.Evaluator(nlp, backend, x) MOI.initialize(evaluator, [:Hess]) end ERROR: AssertionError: k == rinfo.nnz + N Stacktrace: [1] _indirect_recover_structure(rinfo::MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:447 [2] hessian_color_preprocess(edgelist::Set{…}, num_total_var::Int64, seen_idx::MathOptInterface.Nonlinear.ReverseAD.Coloring.IndexedSet) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:489 [3] MathOptInterface.Nonlinear.ReverseAD._FunctionStorage(nodes::Vector{…}, const_values::Vector{…}, num_variables::Int64, coloring_storage::MathOptInterface.Nonlinear.ReverseAD.Coloring.IndexedSet, want_hess::Bool, subexpressions::Vector{…}, dependent_subexpressions::Vector{…}, subexpression_linearity::Vector{…}, subexpression_edgelist::Vector{…}, subexpression_variables::Vector{…}, moi_index_to_consecutive_index::Dict{…}) @ MathOptInterface.Nonlinear.ReverseAD ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/types.jl:97 [4] initialize(d::MathOptInterface.Nonlinear.ReverseAD.NLPEvaluator, requested_features::Vector{Symbol}) @ MathOptInterface.Nonlinear.ReverseAD ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/mathoptinterface_api.jl:104 [5] initialize(evaluator::MathOptInterface.Nonlinear.Evaluator{…}, features::Vector{…}) @ MathOptInterface.Nonlinear ~/git/jump-dev/MathOptInterface/src/Nonlinear/evaluator.jl:105 [6] top-level scope @ REPL[283]:19 Some type information was truncated. Use `show(err)` to see complete types.
Does the error go away if you add diagonal
x[i]^2terms?Nope. Sparsity detection is correct. It's something in the colouring.
julia> begin nlp = MOI.Nonlinear.Model() x = MOI.VariableIndex.(1:6) MOI.Nonlinear.set_objective( nlp, Expr( :call, :+, :($(x[1]) * $(x[4])), :($(x[1]) * $(x[5])), :($(x[2]) * $(x[4])), :($(x[2]) * $(x[6])), :($(x[3]) * $(x[5])), :($(x[3]) * $(x[6])), ) ) backend = MOI.Nonlinear.SparseReverseMode() evaluator = MOI.Nonlinear.Evaluator(nlp, backend, x) MOI.initialize(evaluator, [:Hess]) end edgelist = Set([(4, 2), (5, 1), (4, 1), (6, 2), (5, 3), (6, 3)]) ERROR: AssertionError: k == rinfo.nnz + N Stacktrace: [1] _indirect_recover_structure(rinfo::MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:447
Try force-adding the diagonal entries to the sparsity pattern.
julia> using MathOptInterface.Nonlinear.ReverseAD: Coloring julia> begin I = [4, 5, 4, 6, 5, 6] J = [2, 1, 1, 2, 3, 3] g = Coloring.UndirectedGraph(I, J, length(I)) color, num_colors = Coloring.acyclic_coloring(g) rinfo = Coloring.recovery_preprocess(g, color, num_colors, 1:6) I, J = Coloring._indirect_recover_structure(rinfo) end ERROR: AssertionError: k == rinfo.nnz + N Stacktrace: [1] _indirect_recover_structure(rinfo::MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:447 [2] top-level scope @ REPL[33]:7
Diagonals don't help:
julia> begin I = [1, 2, 3, 4, 5, 6, 4, 5, 4, 6, 5, 6] J = [1, 2, 3, 4, 5, 6, 2, 1, 1, 2, 3, 3] g = Coloring.UndirectedGraph(I, J, length(I)) color, num_colors = Coloring.acyclic_coloring(g) rinfo = Coloring.recovery_preprocess(g, color, num_colors, 1:6) I, J = Coloring._indirect_recover_structure(rinfo) end ERROR: AssertionError: k == rinfo.nnz + N Stacktrace: [1] _indirect_recover_structure(rinfo::MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/git/jump-dev/MathOptInterface/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:447 [2] top-level scope @ REPL[34]:7
I need to have some lunch. Will be back in a bit
So the colouring changed.
julia> using MathOptInterface.Nonlinear.ReverseAD: Coloring julia> I = [4, 5, 4, 6, 5, 6] 6-element Vector{Int64}: 4 5 4 6 5 6 julia> J = [2, 1, 1, 2, 3, 3] 6-element Vector{Int64}: 2 1 1 2 3 3 julia> g = Coloring.UndirectedGraph(I, J, length(I)) MathOptInterface.Nonlinear.ReverseAD.Coloring.UndirectedGraph([5, 4, 4, 6, 5, 6, 2, 1, 1, 3, 2, 3], [2, 3, 1, 4, 5, 6, 1, 3, 2, 5, 4, 6], [1, 3, 5, 7, 9, 11, 13], [(4, 2), (5, 1), (4, 1), (6, 2), (5, 3), (6, 3)]) julia> color, num_colors = Coloring.acyclic_coloring(g) ([1, 1, 1, 2, 2, 2], 2) julia> rinfo = Coloring.recovery_preprocess(g, color, num_colors, 1:6) MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo([[4, 2, 5, 1, 6, 3]], [[4, 3, 6, 5, 2, 1]], [[0, 1, 6, 3, 2, 5]], [1, 1, 1, 2, 2, 2], 2, 6, [1, 2, 3, 4, 5, 6]) julia> I, J = Coloring._indirect_recover_structure(rinfo) ERROR: AssertionError: k == rinfo.nnz + N
where previously
(moi) pkg> st Status `/private/tmp/moi/Project.toml` ⌃ [b8f27783] MathOptInterface v1.46.0 Info Packages marked with ⌃ have new versions available and may be upgradable. julia> using MathOptInterface.Nonlinear.ReverseAD: Coloring julia> I = [4, 5, 4, 6, 5, 6] 6-element Vector{Int64}: 4 5 4 6 5 6 julia> J = [2, 1, 1, 2, 3, 3] 6-element Vector{Int64}: 2 1 1 2 3 3 julia> g = Coloring.UndirectedGraph(I, J, length(I)) MathOptInterface.Nonlinear.ReverseAD.Coloring.UndirectedGraph([5, 4, 4, 6, 5, 6, 2, 1, 1, 3, 2, 3], [2, 3, 1, 4, 5, 6, 1, 3, 2, 5, 4, 6], [1, 3, 5, 7, 9, 11, 13], [(4, 2), (5, 1), (4, 1), (6, 2), (5, 3), (6, 3)]) julia> color, num_colors = Coloring.acyclic_coloring(g) ([1, 1, 1, 2, 2, 3], 3) julia> rinfo = Coloring.recovery_preprocess(g, color, num_colors, 1:6) MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo([[4, 2, 5, 1, 3], [6, 2, 3]], [[2, 5, 3, 4, 1], [2, 3, 1]], [[0, 1, 4, 1, 3], [0, 1, 1]], [1, 1, 1, 2, 2, 3], 3, 6, [1, 2, 3, 4, 5, 6]) julia> I, J = Coloring._indirect_recover_structure(rinfo) ([1, 2, 3, 4, 5, 6, 4, 5, 5, 4, 6, 6], [1, 2, 3, 4, 5, 6, 2, 3, 1, 1, 2, 3])
PR incoming. Twas my fault for not being careful when I swapped out the data structure.
The assert did a good job then!
Reacted by Alexis Montoison and basberr
Hi all,
After the update from v1.46 to v.1.47, some of my codes now trigger this error.
This might be related to this recent change: #2882
(which btw has sped up the resolution of some of my problems by a factor ~2, so that's very nice!)
I did not manage to isolate a MWE yet but I verified that my code works with v.1.46.
Here is the stacktrace in case it evokes something to you (it's with Ipopt but I get the same with MadNLP)
ERROR: AssertionError: k == rinfo.nnz + N Stacktrace: [1] _indirect_recover_structure(rinfo::MathOptInterface.Nonlinear.ReverseAD.Coloring.RecoveryInfo) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/.julia/packages/MathOptInterface/9lCV5/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:447 [2] hessian_color_preprocess(edgelist::Set{…}, num_total_var::Int64, seen_idx::MathOptInterface.Nonlinear.ReverseAD.Coloring.IndexedSet) @ MathOptInterface.Nonlinear.ReverseAD.Coloring ~/.julia/packages/MathOptInterface/9lCV5/src/Nonlinear/ReverseAD/Coloring/Coloring.jl:489 [3] MathOptInterface.Nonlinear.ReverseAD._FunctionStorage(nodes::Vector{…}, const_values::Vector{…}, num_variables::Int64, coloring_storage::MathOptInterface.Nonlinear.ReverseAD.Coloring.IndexedSet, want_hess::Bool, subexpressions::Vector{…}, dependent_subexpressions::Vector{…}, subexpression_linearity::Vector{…}, subexpression_edgelist::Vector{…}, subexpression_variables::Vector{…}, moi_index_to_consecutive_index::Dict{…}) @ MathOptInterface.Nonlinear.ReverseAD ~/.julia/packages/MathOptInterface/9lCV5/src/Nonlinear/ReverseAD/types.jl:97 [4] initialize(d::MathOptInterface.Nonlinear.ReverseAD.NLPEvaluator, requested_features::Vector{Symbol}) @ MathOptInterface.Nonlinear.ReverseAD ~/.julia/packages/MathOptInterface/9lCV5/src/Nonlinear/ReverseAD/mathoptinterface_api.jl:123 [5] initialize(evaluator::MathOptInterface.Nonlinear.Evaluator{…}, features::Vector{…}) @ MathOptInterface.Nonlinear ~/.julia/packages/MathOptInterface/9lCV5/src/Nonlinear/evaluator.jl:105 [6] _setup_model(model::IpoptMathOptInterfaceExt.Optimizer) @ IpoptMathOptInterfaceExt ~/.julia/packages/Ipopt/qJgV6/ext/IpoptMathOptInterfaceExt/MOI_wrapper.jl:1341 [7] optimize!(model::IpoptMathOptInterfaceExt.Optimizer) @ IpoptMathOptInterfaceExt ~/.julia/packages/Ipopt/qJgV6/ext/IpoptMathOptInterfaceExt/MOI_wrapper.jl:1356 [8] optimize! @ ~/.julia/packages/MathOptInterface/9lCV5/src/Bridges/bridge_optimizer.jl:367 [inlined] [9] optimize! @ ~/.julia/packages/MathOptInterface/9lCV5/src/MathOptInterface.jl:122 [inlined] [10] optimize!(m::MathOptInterface.Utilities.CachingOptimizer{…}) @ MathOptInterface.Utilities ~/.julia/packages/MathOptInterface/9lCV5/src/Utilities/cachingoptimizer.jl:370 [11] optimize!(model::JuMP.Model; ignore_optimize_hook::Bool, _differentiation_backend::MathOptInterface.Nonlinear.SparseReverseMode, kwargs::@Kwargs{}) @ JuMP ~/.julia/packages/JuMP/e83v9/src/optimizer_interface.jl:609 [12] optimize! @ ~/.julia/packages/JuMP/e83v9/src/optimizer_interface.jl:560 [inlined]