Add default printing for show(io, ::ModelLike) #2505

odow · 2024-05-24T01:02:05Z

Still needs to fix tests and some finessing.
Let's see how many tests depend on show: https://github.com/jump-dev/MathOptInterface.jl/actions/runs/9218665500

odow · 2024-05-24T03:57:14Z

I think I like this:

julia> include("test/Bridges/sdpa_models.jl")

julia> model = MOI.Utilities.CachingOptimizer(
           MOI.Utilities.Model{Float64}(),
           MOI.Bridges.full_bridge_optimizer(StandardSDPAModel{Float64}(), Float64),
       )
A MOI.Utilities.CachingOptimizer:
├ state
│ └ EMPTY_OPTIMIZER
├ mode
│ └ AUTOMATIC
├ model_cache
│ An empty MOIU.Model{Float64}
└ optimizer
  A MOIB.LazyBridgeOptimizer{MOIU.GenericModel{Float64, MOIU.ObjectiveContainer{Float64}, MOIU.VariablesContainer{Float64}, StandardSDPAModelFunctionConstraints{Float64}}}
  ├ Variable bridges
  │ └ none
  ├ Constraint bridges
  │ └ none
  ├ Objective bridges
  │ └ none
  └ model
    An empty MOIU.GenericModel{Float64, MOIU.ObjectiveContainer{Float64}, MOIU.VariablesContainer{Float64}, StandardSDPAModelFunctionConstraints{Float64}}

julia> x = MOI.add_variable(model)
MOI.VariableIndex(1)

julia> MOI.add_constraint(model, 2.0 * x, MOI.LessThan(3.0))
MathOptInterface.ConstraintIndex{MathOptInterface.ScalarAffineFunction{Float64}, MathOptInterface.LessThan{Float64}}(1)

julia> MOI.Utilities.attach_optimizer(model)

julia> model
A MOI.Utilities.CachingOptimizer:
├ state
│ └ ATTACHED_OPTIMIZER
├ mode
│ └ AUTOMATIC
├ model_cache
│ A MOIU.Model{Float64}
│ ├ ObjectiveSense
│ │ └ FEASIBILITY_SENSE
│ ├ ObjectiveFunctionType
│ │ └ MOI.ScalarAffineFunction{Float64}
│ ├ NumberOfVariables
│ │ └ 1
│ └ NumberOfConstraints
│   └ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 1
└ optimizer
  A MOIB.LazyBridgeOptimizer{MOIU.GenericModel{Float64, MOIU.ObjectiveContainer{Float64}, MOIU.VariablesContainer{Float64}, StandardSDPAModelFunctionConstraints{Float64}}}
  ├ Variable bridges
  │ ├ MOIB.Variable.FreeBridge{Float64}
  │ └ MOIB.Variable.VectorizeBridge{Float64, MOI.Nonnegatives}
  ├ Constraint bridges
  │ ├ MOIB.Constraint.LessToGreaterBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.ScalarAffineFunction{Float64}}
  │ └ MOIB.Constraint.ScalarSlackBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.GreaterThan{Float64}}
  ├ Objective bridges
  │ └ none
  └ model
    A MOIU.GenericModel{Float64, MOIU.ObjectiveContainer{Float64}, MOIU.VariablesContainer{Float64}, StandardSDPAModelFunctionConstraints{Float64}}
    ├ ObjectiveSense
    │ └ FEASIBILITY_SENSE
    ├ ObjectiveFunctionType
    │ └ MOI.ScalarAffineFunction{Float64}
    ├ NumberOfVariables
    │ └ 3
    └ NumberOfConstraints
      ├ MOI.ScalarAffineFunction{Float64} in MOI.EqualTo{Float64}: 1
      └ MOI.VectorOfVariables in MOI.Nonnegatives: 2

odow · 2024-05-24T05:35:10Z

So this is actually super useful for debugging.

Cribbing from a recent post on discourse:

julia> using JuMP

julia> import HiGHS

julia> import MultiObjectiveAlgorithms as MOA

julia> model = Model(() -> MOA.Optimizer(HiGHS.Optimizer));

julia> set_silent(model)

julia> set_attribute(model, MOA.Algorithm(), MOA.Hierarchical())

julia> @variables(model, begin
           lb[i] <= z[i in 1:length(lb)] <= ub[i], Int
           d >= 0
       end);

julia> @constraints(model, begin
           z - lb .- d >= 0
           z - ub .+ d <= 0
           sum(z) <= 500
       end);

julia> @objective(model, Max, [sum(z), d]);

julia> optimize!(model)

julia> backend(model)
A MOI.Utilities.CachingOptimizer:
├ state
│ └ ATTACHED_OPTIMIZER
├ mode
│ └ AUTOMATIC
├ model_cache
│ A MOIU.UniversalFallback{MOIU.Model{Float64}}
│ ├ ObjectiveSense
│ │ └ MAX_SENSE
│ ├ ObjectiveFunctionType
│ │ └ MOI.VectorAffineFunction{Float64}
│ ├ NumberOfVariables
│ │ └ 11
│ └ NumberOfConstraints
│   ├ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 1
│   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonnegatives: 1
│   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonpositives: 1
│   ├ MOI.VariableIndex in MOI.GreaterThan{Float64}: 11
│   ├ MOI.VariableIndex in MOI.LessThan{Float64}: 10
│   └ MOI.VariableIndex in MOI.Integer: 10
└ optimizer
  A MOIB.LazyBridgeOptimizer{MultiObjectiveAlgorithms.Optimizer}
  ├ Variable bridges
  │ └ none
  ├ Constraint bridges
  │ ├ MOIB.Constraint.ScalarizeBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.GreaterThan{Float64}}
  │ └ MOIB.Constraint.ScalarizeBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.LessThan{Float64}}
  ├ Objective bridges
  │ └ none
  └ model
    A MultiObjectiveAlgorithms.Optimizer
    ├ ObjectiveSense
    │ └ MAX_SENSE
    ├ ObjectiveFunctionType
    │ └ MOI.VectorAffineFunction{Float64}
    ├ NumberOfVariables
    │ └ 11
    └ NumberOfConstraints
      ├ MOI.ScalarAffineFunction{Float64} in MOI.GreaterThan{Float64}: 10
      ├ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 11
      ├ MOI.VariableIndex in MOI.GreaterThan{Float64}: 11
      ├ MOI.VariableIndex in MOI.LessThan{Float64}: 10
      └ MOI.VariableIndex in MOI.Integer: 10

ericphanson · 2024-05-24T12:59:21Z

This looks nice! I wonder if it could be a bit more compact in cases when there's only 1 child? I've found too much scrolling in the REPL can make it harder to understand a printout. e.g.

A MOI.Utilities.CachingOptimizer:
├ state: ATTACHED_OPTIMIZER
├ mode: AUTOMATIC
├ model_cache: MOIU.UniversalFallback{MOIU.Model{Float64}}
│ ├ ObjectiveSense: MAX_SENSE
│ ├ ObjectiveFunctionType: MOI.VectorAffineFunction{Float64}
│ ├ NumberOfVariables: 11
│ └ NumberOfConstraints: 34
│   ├ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 1
│   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonnegatives: 1
│   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonpositives: 1
│   ├ MOI.VariableIndex in MOI.GreaterThan{Float64}: 11
│   ├ MOI.VariableIndex in MOI.LessThan{Float64}: 10
│   └ MOI.VariableIndex in MOI.Integer: 10
└ optimizer: MOIB.LazyBridgeOptimizer{MultiObjectiveAlgorithms.Optimizer}
  ├ Variable bridges: none
  ├ Constraint bridges
  │ ├ MOIB.Constraint.ScalarizeBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.GreaterThan{Float64}}
  │ └ MOIB.Constraint.ScalarizeBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.LessThan{Float64}}
  ├ Objective bridges: none
  └ model: MultiObjectiveAlgorithms.Optimizer
    ├ ObjectiveSense: MAX_SENSE
    ├ ObjectiveFunctionType: MOI.VectorAffineFunction{Float64}
    ├ NumberOfVariables: 11
    └ NumberOfConstraints: 52
      ├ MOI.ScalarAffineFunction{Float64} in MOI.GreaterThan{Float64}: 10
      ├ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 11
      ├ MOI.VariableIndex in MOI.GreaterThan{Float64}: 11
      ├ MOI.VariableIndex in MOI.LessThan{Float64}: 10
      └ MOI.VariableIndex in MOI.Integer: 10

This is kinda already done for contraints, like MOI.ScalarAffineFunction{Float64} in MOI.GreaterThan{Float64}: 10, so I think it could work also for NumberOfVariables, ObjectiveSense, ObjectiveFunctionType, state and mode.

I think it would also make sense for nones in things like Variable bridges, Constraint bridges.

I also tweaked it so instead of A MOIU.UniversalFallback{MOIU.Model{Float64}} on the following line, I removed the A and put it after a colon. To me the "A" was a bit confusing (I know it's the indefinite article, but the rest isn't really sentences so it's not clear if it means like some kind of "type A" vs "type B" or something). And IMO it reads a little better having it on the same line. I did the same for optimizer: MOIB.LazyBridgeOptimizer{MultiObjectiveAlgorithms.Optimizer} and model: MultiObjectiveAlgorithms.Optimizer.

Lastly I think it could also be nice to have NumberOfConstraints print a total, like I added here.

odow · 2024-05-25T03:38:31Z

@ericphanson done

odow · 2024-05-25T03:58:17Z

It's now:

julia> using JuMP

julia> import HiGHS

julia> import MultiObjectiveAlgorithms as MOA

julia> model = Model(() -> MOA.Optimizer(HiGHS.Optimizer));

julia> set_silent(model)

julia> set_attribute(model, MOA.Algorithm(), MOA.Hierarchical())

julia> lb = ones(10); ub = fill(10, 10);

julia> @variables(model, begin
           lb[i] <= z[i in 1:length(lb)] <= ub[i], Int
           d >= 0
       end);

julia> @constraints(model, begin
           z - lb .- d >= 0
           z - ub .+ d <= 0
           sum(z) <= 500
       end);

julia> @objective(model, Max, [sum(z), d]);

julia> optimize!(model)

julia> backend(model)
MOIU.CachingOptimizer
├ state: ATTACHED_OPTIMIZER
├ mode: AUTOMATIC
├ model_cache: MOIU.UniversalFallback{MOIU.Model{Float64}}
│ ├ ObjectiveSense: MAX_SENSE
│ ├ ObjectiveFunctionType: MOI.VectorAffineFunction{Float64}
│ ├ NumberOfVariables: 11
│ └ NumberOfConstraints: 34
│   ├ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 1
│   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonnegatives: 1
│   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonpositives: 1
│   ├ MOI.VariableIndex in MOI.GreaterThan{Float64}: 11
│   ├ MOI.VariableIndex in MOI.LessThan{Float64}: 10
│   └ MOI.VariableIndex in MOI.Integer: 10
└ optimizer:   MOIB.LazyBridgeOptimizer{MultiObjectiveAlgorithms.Optimizer}
  ├ Variable bridges: none
  ├ Constraint bridges:
  │ ├ MOIB.Constraint.ScalarizeBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.GreaterThan{Float64}}
  │ └ MOIB.Constraint.ScalarizeBridge{Float64, MOI.ScalarAffineFunction{Float64}, MOI.LessThan{Float64}}
  ├ Objective bridges: none
  └ model: MultiObjectiveAlgorithms.Optimizer
    ├ ObjectiveSense: MAX_SENSE
    ├ ObjectiveFunctionType: MOI.VectorAffineFunction{Float64}
    ├ NumberOfVariables: 11
    └ NumberOfConstraints: 52
      ├ MOI.ScalarAffineFunction{Float64} in MOI.GreaterThan{Float64}: 10
      ├ MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}: 11
      ├ MOI.VariableIndex in MOI.GreaterThan{Float64}: 11
      ├ MOI.VariableIndex in MOI.LessThan{Float64}: 10
      └ MOI.VariableIndex in MOI.Integer: 10

odow · 2024-05-25T04:00:45Z

Here's a problem;

julia> using JuMP, SCS

julia> model = Model(SCS.Optimizer);

julia> set_silent(model)

julia> @variable(model, x[1:2, 1:2] >= 0, PSD);

julia> @constraint(model, sum(x) == 1);

julia> optimize!(model)

julia> backend(model)
MOIU.CachingOptimizer
├ state: ATTACHED_OPTIMIZER
├ mode: AUTOMATIC
├ model_cache: MOIU.UniversalFallback{MOIU.Model{Float64}}
│ ├ ObjectiveSense: FEASIBILITY_SENSE
│ ├ ObjectiveFunctionType: MOI.ScalarAffineFunction{Float64}
│ ├ NumberOfVariables: 3
│ └ NumberOfConstraints: 5
│   ├ MOI.ScalarAffineFunction{Float64} in MOI.EqualTo{Float64}: 1
│   ├ MOI.VectorOfVariables in MOI.PositiveSemidefiniteConeTriangle: 1
│   └ MOI.VariableIndex in MOI.GreaterThan{Float64}: 3
└ optimizer:   MOIB.LazyBridgeOptimizer{MOIU.CachingOptimizer{SCS.Optimizer, MOIU.UniversalFallback{MOIU.Model{Float64}}}}
  ├ Variable bridges: none
  ├ Constraint bridges:
  │ ├ MOIB.Constraint.SetDotScalingBridge{Float64, MOI.PositiveSemidefiniteConeTriangle, MOI.VectorAffineFunction{Float64}, MOI.VectorOfVariables}
  │ ├ MOIB.Constraint.VectorizeBridge{Float64, MOI.VectorAffineFunction{Float64}, MOI.Nonnegatives, MOI.VariableIndex}
  │ ├ MOIB.Constraint.VectorizeBridge{Float64, MOI.VectorAffineFunction{Float64}, MOI.Zeros, MOI.ScalarAffineFunction{Float64}}
  │ └ SCS.ScaledPSDConeBridge{Float64, MOI.VectorAffineFunction{Float64}}
  ├ Objective bridges: none
  └ model:     MOIU.CachingOptimizer
    ├ state: EMPTY_OPTIMIZER
    ├ mode: AUTOMATIC
    ├ model_cache: MOIU.UniversalFallback{MOIU.Model{Float64}}
    │ ├ ObjectiveSense: FEASIBILITY_SENSE
    │ ├ ObjectiveFunctionType: MOI.ScalarAffineFunction{Float64}
    │ ├ NumberOfVariables: 3
    │ └ NumberOfConstraints: 5
    │   ├ MOI.VectorAffineFunction{Float64} in MOI.Zeros: 1
    │   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonnegatives: 3
    │   └ MOI.VectorAffineFunction{Float64} in SCS.ScaledPSDCone: 1
    └ optimizer: SCS.Optimizer
      ├ ObjectiveSense: FEASIBILITY_SENSE
      ├ ObjectiveFunctionType: ?
      ├ NumberOfVariables: ?
      └ NumberOfConstraints: 0

SCS doesn't support getting various attributes, so there is some weirdness. We could fix that though.

blegat · 2024-05-25T07:06:04Z

This is very nice, I like it ! It makes the MOI layers much less obscure

odow · 2024-05-25T07:55:31Z

Now it's

julia> backend(model)
MOIU.CachingOptimizer
├ state: ATTACHED_OPTIMIZER
├ mode: AUTOMATIC
├ model_cache: MOIU.UniversalFallback{MOIU.Model{Float64}}
│ ├ ObjectiveSense: FEASIBILITY_SENSE
│ ├ ObjectiveFunctionType: MOI.ScalarAffineFunction{Float64}
│ ├ NumberOfVariables: 3
│ └ NumberOfConstraints: 5
│   ├ MOI.ScalarAffineFunction{Float64} in MOI.EqualTo{Float64}: 1
│   ├ MOI.VectorOfVariables in MOI.PositiveSemidefiniteConeTriangle: 1
│   └ MOI.VariableIndex in MOI.GreaterThan{Float64}: 3
└ optimizer: MOIB.LazyBridgeOptimizer{MOIU.CachingOptimizer{SCS.Optimizer, MOIU.UniversalFallback{MOIU.Model{Float64}}}}
  ├ Variable bridges: none
  ├ Constraint bridges:
  │ ├ MOIB.Constraint.SetDotScalingBridge{Float64, MOI.PositiveSemidefiniteConeTriangle, MOI.VectorAffineFunction{Float64}, MOI.VectorOfVariables}
  │ ├ MOIB.Constraint.VectorizeBridge{Float64, MOI.VectorAffineFunction{Float64}, MOI.Nonnegatives, MOI.VariableIndex}
  │ ├ MOIB.Constraint.VectorizeBridge{Float64, MOI.VectorAffineFunction{Float64}, MOI.Zeros, MOI.ScalarAffineFunction{Float64}}
  │ └ SCS.ScaledPSDConeBridge{Float64, MOI.VectorAffineFunction{Float64}}
  ├ Objective bridges: none
  └ model: MOIU.CachingOptimizer
    ├ state: EMPTY_OPTIMIZER
    ├ mode: AUTOMATIC
    ├ model_cache: MOIU.UniversalFallback{MOIU.Model{Float64}}
    │ ├ ObjectiveSense: FEASIBILITY_SENSE
    │ ├ ObjectiveFunctionType: MOI.ScalarAffineFunction{Float64}
    │ ├ NumberOfVariables: 3
    │ └ NumberOfConstraints: 5
    │   ├ MOI.VectorAffineFunction{Float64} in MOI.Zeros: 1
    │   ├ MOI.VectorAffineFunction{Float64} in MOI.Nonnegatives: 3
    │   └ MOI.VectorAffineFunction{Float64} in SCS.ScaledPSDCone: 1
    └ optimizer: SCS.Optimizer
      ├ ObjectiveSense: unknown
      ├ ObjectiveFunctionType: unknown
      ├ NumberOfVariables: unknown
      └ NumberOfConstraints: unknown

ericphanson · 2024-05-25T16:20:21Z

looks great!

src/MathOptInterface.jl

odow · 2024-05-26T20:44:40Z

Thoughts @blegat?

blegat · 2024-05-27T06:15:10Z

Maybe we should add a test printing an empty model that every solver runs. It should be safe with the _try_catch but you never know, a solver could also segfault ^^

odow · 2024-05-27T06:20:11Z

src/Test/test_model.jl

+
+function test_model_show(model::MOI.ModelLike, ::Config{T}) where {T}
+    # We don't enforce any particular output.
+    @test sprint(show, model) isa String


@blegat see this test

And I checked with solver-tests.yml: https://github.com/jump-dev/MathOptInterface.jl/actions/runs/9218665500

odow · 2024-05-27T08:56:49Z

I think this is a really nice quality of life improvement. Don't know why we didn't do this earlier.

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WIP: add default summary for show(io, ::ModelLike)

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odow changed the title ~~WIP: add default summary for show(io, ::ModelLike)~~ Add default printing for show(io, ::ModelLike) May 24, 2024

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[FileFormats] remove show method in favor of summary #2510

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Add default printing for show(io, ::ModelLike) #2505

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Add default printing for show(io, ::ModelLike) #2505

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