Discourage Finite Models (#151)

* Fix bug and discourage finite models

* Update finite model warning location

docs/src/guide/model.md

@@ -11,6 +11,12 @@ measures, objective, constraints, and all other data used in `InfiniteOpt`. This
 differs from `JuMP` models which store such information in a `MathOptInterface`
 model backend.
 
+!!! note 
+    `InfiniteOpt`'s `InfiniteModel`s are intended to be used for 
+    infinite-dimensional optimization problems. Finite problems (e.g., 
+    directly modeling a discrete time model) should instead be modeled using 
+    `Model`'s in [`JuMP`](https://jump.dev/JuMP.jl/stable/).
+
 ## Basic Usage
 Infinite models can be initialized with no arguments by default:
 ```jldoctest

docs/src/index.md

@@ -30,6 +30,11 @@ include:
 - Measures (e.g., ``\int_{t \in \mathcal{D}_t}y(t,x) dt``, ``\mathbb{E}[y(\xi)]``)
 - More
 
+!!! note 
+    `InfiniteOpt` is intended to be used for infinite-dimensional optimization 
+    problems. Finite problems (e.g., directly modeling a discrete time model) 
+    should instead be modeled using [`JuMP`](https://jump.dev/JuMP.jl/stable/).
+
 Moreover, `InfiniteOpt` decouples the infinite-dimensional formulations from the 
 finite transformations typically used to solve them. This readily enables diverse 
 techniques be used to solve these types of problems. By default, we employ 

src/TranscriptionOpt/transcribe.jl

@@ -872,7 +872,7 @@ function build_transcription_model!(
     set_parameter_supports(trans_model, inf_model)
     # check that there isn't a crazy amount of supports from taking the product
     supps = parameter_supports(trans_model)
-    num_supps = prod(length, supps)
+    num_supps = isempty(supps) ? 0 : prod(length, supps)
     if check_support_dims && length(supps) > 1 && num_supps > 15000 # NOTE this is an arbitrary cutoff
         @warn("Due to necessarily considering the combinatorics of independent " *
               "parameter supports, the model will be transcripted over up to $(num_supps) " *

src/optimize.jl

@@ -521,9 +521,13 @@ true
 ```
 """
 function build_optimizer_model!(model::InfiniteModel; kwargs...)
-  key = optimizer_model_key(model)
-  build_optimizer_model!(model, Val(key); kwargs...)
-  return
+    if num_parameters(model, InfiniteParameter) == 0
+        @warn("Finite models (i.e., `InfiniteModel`s with no infinite " * 
+              "parameters) should be modeled directly via a `Model` in JuMP.jl.")
+    end
+    key = optimizer_model_key(model)
+    build_optimizer_model!(model, Val(key); kwargs...)
+    return
 end
 
 ################################################################################

test/TranscriptionOpt/transcribe.jl

@@ -495,4 +495,14 @@ end
     @test transcription_constraint(FixRef(y)) isa Vector{ConstraintRef}
     @test transcription_constraint(BinaryRef(y)) isa Vector{ConstraintRef}
     @test transcription_constraint(UpperBoundRef(d1)) == UpperBoundRef.(d1t)
+
+    # test a finite model 
+    m = InfiniteModel()
+    @variable(m, y >= 0)
+    @objective(m, Min, y)
+    tm = transcription_model(m)
+    @test IOTO.build_transcription_model!(tm, m) isa Nothing 
+    @test transcription_variable(y) isa VariableRef 
+    @test lower_bound(transcription_variable(y)) == 0
+    @test objective_sense(tm) == MOI.MIN_SENSE
 end

test/optimizer.jl

@@ -29,6 +29,13 @@
     @test isa(build_optimizer_model!(m), Nothing)
     @test optimizer_model_ready(m)
     @test num_variables(optimizer_model(m)) == 14
+    # test finite model
+    m = InfiniteModel()
+    @variable(m, y >= 0)
+    @objective(m, Min, y)
+    warn = "Finite models (i.e., `InfiniteModel`s with no infinite " * 
+           "parameters) should be modeled directly via a `Model` in JuMP.jl."
+    @test_logs (:warn, warn) build_optimizer_model!(m)
 end
 
 # Test optimizer model querying methods