Introduce get_counters accessor

docs/src/guidelines.md

@@ -3,6 +3,7 @@
 These are guidelines for the creation of models using NLPModels to help keeping the models uniform, and for future reference in the creation of solvers.
 
 Table of contents:
+
 - [Bare minimum](@ref bare-minimum)
 - [Expected behaviour](@ref expected-behaviour)
 - [Advanced counters](@ref advanced-counters)
@@ -14,23 +15,28 @@ Your model should derive from `AbstractNLPModel` or some other abstract class de
 It is mandatory that it have a `meta :: NLPModelMeta` field, storing all the relevant problem information.
 The model also needs to provide `Counters` information. The easiest way is to define `counters :: Counters`.
 For instance:
+
 ```julia
 mutable struct MyModel{T, S} <: AbstractNLPModel{T, S}
   meta :: NLPModelMeta{T, S}
   counters :: Counters
 end
 ```
+
 For alternatives to storing `Counters` in the model, check [advanced counters](@ref advanced-counters).
 The minimum information that should be set for your model through `NLPModelMeta` is `nvar`, the number of variables.
 The following is a valid constructor for `MyModel`:
+
 ```julia
 function MyModel()
   return MyModel(NLPModelMeta(5), Counters())
 end
 ```
+
 More information can be passed to `NLPModelMeta`.
 See the full list [here](https://github.com/JuliaSmoothOptimizers/NLPModels.jl/blob/main/src/nlp/meta.jl#L32).
 The essential fields are
+
 - `x0`: Starting point (defaults to `zeros`)
 - `lvar`, `uvar`: Bounds on the variables (default to `(-∞,∞)`)
 - `ncon`: Number of constraints (defaults to `0`)
@@ -43,6 +49,7 @@ Luckily, many have a default implementation.
 We collect here the list of functions that should be implemented for a complete API.
 
 Here, the following notation applies:
+
 - `nlp` is your instance of `MyModel <: AbstractNLPModel`
 - `x` is the point where the function is evaluated
 - `y` is the vector of Lagrange multipliers (for constrained problems only)
@@ -112,25 +119,32 @@ The following is a non-exhaustive list of expected behaviour for methods.
 
 To further specialize your model, you can also define `show_header` and possibly `show`.
 The default `show_header` simply prints the `typeof` the NLPModel, so it should be specialized with the specific information that you prefer. For instance, `SlackModel` defines
+
 ```julia
 show_header(io :: IO, nlp :: SlackModel) = println(io, "SlackModel - Model with slack variables")
 ```
-Furthermore, we define a general `show` that calls `show_header` and specific `show` functions for the `meta` and the `counters`. If your model does not have `counters` in the default location, you must define `show` for them as well. Alternatively, you may desire to change the behaviour of show. Here is an example, again from `SlackModel`:
+
+Furthermore, we define a general `show` that calls `show_header` and specific `show` functions for the `meta` and the `counters`. If your model does not have `counters` in the default location, you must define `get_counters` for them as well. Alternatively, you may desire to change the behaviour of show. The default behaviour is
+
 ```julia
-function show(io :: IO, nlp :: SlackModel)
+function show(io :: IO, nlp :: AbstractNLPModel)
   show_header(io, nlp)
   show(io, nlp.meta)
-  show(io, nlp.model.counters)
+  show(io, get_counters(nlp.model))
 end
 ```
 
 ## [Advanced counters](@id advanced-counters)
 
 If a model does not implement `counters`, then it needs to define
+
+- `get_counters(nlp)` - get the `Counters` object associated with `nlp`
 - `neval_xxx(nlp)` - get field `xxx` of `Counters`
 - `reset!(nlp)` - resetting all counters
 - `increment!(nlp, s)` - increment counter `s`
+
 For instance
+
 ```julia
 for counter in fieldnames(Counters)
   @eval begin
@@ -144,19 +158,23 @@ function increment!(nlp :: MyModel, s :: Symbol)
   INCREMENT COUNTER s
 end
 ```
+
 One example of such model is the `SlackModel`, which stores an internal `model :: AbstractNLPModel`, thus defining
+
 ```julia
 $counter(nlp :: SlackModel) = $counter(nlp.model)
 reset!(nlp :: SlackModel) = reset!(nlp.model)
 increment!(nlp :: SlackModel, s :: Symbol) = increment!(nlp.model, s)
 ```
+
 This construction can be replicated calling the macro `@default_counters Model inner`.
 In the case of SlackModel, the equivalent call is
+
 ```julia
 @default_counters SlackModel model
 ```
 
-Furthermore, the `show` method has to be updated with the correct direction of `counter`. See [show](@ref show) for more information.
+Furthermore, the `show` method may have to be updated with the correct direction of `counter`. See [show](@ref show) for more information.
 
 ## [Advanced tests](@id advanced-tests)
 

src/nlp/counters.jl

@@ -1,4 +1,4 @@
-export Counters, sum_counters, increment!, decrement!, reset!
+export Counters, get_counters, sum_counters, increment!, decrement!, reset!
 
 """
     Counters
@@ -39,14 +39,26 @@ mutable struct Counters
 end
 
 # simple default API for retrieving counters
+
+# For backward compatibility.
+# In the future, forcing this method to raise an error if not implemented
+# would be more robust.
+"""
+        get_counters(nlp)
+
+Return the `Counters` struct associated with `nlp`.
+By default, this is `nlp.counters`, but it can be overridden in concrete models.
+"""
+get_counters(nlp::AbstractNLPModel) = nlp.counters
+
 for counter in fieldnames(Counters)
   @eval begin
     """
         $($counter)(nlp)
 
     Get the number of `$(split("$($counter)", "_")[2])` evaluations.
     """
-    $counter(nlp::AbstractNLPModel) = nlp.counters.$counter
+    $counter(nlp::AbstractNLPModel) = get_counters(nlp).$counter
     export $counter
   end
 end
@@ -61,7 +73,7 @@ Increment counter `s` of problem `nlp`.
 end
 
 for fun in fieldnames(Counters)
-  @eval increment!(nlp::AbstractNLPModel, ::Val{$(Meta.quot(fun))}) = nlp.counters.$fun += 1
+  @eval increment!(nlp::AbstractNLPModel, ::Val{$(Meta.quot(fun))}) = get_counters(nlp).$fun += 1
 end
 
 """
@@ -70,7 +82,8 @@ end
 Decrement counter `s` of problem `nlp`.
 """
 function decrement!(nlp::AbstractNLPModel, s::Symbol)
-  setproperty!(nlp.counters, s, getproperty(nlp.counters, s) - 1)
+  counters = get_counters(nlp)
+  setproperty!(counters, s, getproperty(counters, s) - 1)
 end
 
 """
@@ -92,7 +105,7 @@ end
 
 Sum all counters of problem `nlp` except `cons`, `jac`, `jprod` and `jtprod`.
 """
-sum_counters(nlp::AbstractNLPModel) = sum_counters(nlp.counters)
+sum_counters(nlp::AbstractNLPModel) = sum_counters(get_counters(nlp))
 
 """
     reset!(counters)
@@ -112,7 +125,7 @@ end
 Reset evaluation count and model data (if appropriate) in `nlp`.
 """
 function LinearOperators.reset!(nlp::AbstractNLPModel)
-  reset!(nlp.counters)
+  reset!(get_counters(nlp))
   reset_data!(nlp)
   return nlp
 end

src/nlp/show.jl

@@ -11,7 +11,7 @@ show_header(io::IO, nlp::AbstractNLPModel) = println(io, typeof(nlp))
 function Base.show(io::IO, nlp::AbstractNLPModel)
   show_header(io, nlp)
   show(io, nlp.meta)
-  show(io, nlp.counters)
+  show(io, get_counters(nlp))
 end
 
 """

src/nlp/utils.jl

@@ -162,7 +162,7 @@ macro default_counters(Model, inner, excluded = :())
     ex.args,
     :(
       Base.getproperty(nlp::$(esc(Model)), s::Symbol) =
-        (s == :counters ? nlp.$inner.counters : getfield(nlp, s))
+        (s == :counters ? get_counters(nlp.$inner) : getfield(nlp, s))
     ),
   )
   ex

src/nls/counters.jl

@@ -51,7 +51,7 @@ function sum_counters(c::NLSCounters)
   end
   return s
 end
-sum_counters(nls::AbstractNLSModel) = sum_counters(nls.counters)
+sum_counters(nls::AbstractNLSModel) = sum_counters(get_counters(nls))
 
 for counter in fieldnames(NLSCounters)
   counter == :counters && continue
@@ -61,14 +61,14 @@ for counter in fieldnames(NLSCounters)
 
     Get the number of `$(split("$($counter)", "_")[2])` evaluations.
     """
-    $counter(nls::AbstractNLSModel) = nls.counters.$counter
+    $counter(nls::AbstractNLSModel) = get_counters(nls).$counter
     export $counter
   end
 end
 
 for counter in fieldnames(Counters)
   @eval begin
-    $counter(nls::AbstractNLSModel) = nls.counters.counters.$counter
+    $counter(nls::AbstractNLSModel) = get_counters(nls).counters.$counter
     export $counter
   end
 end
@@ -84,16 +84,16 @@ end
 
 for fun in fieldnames(NLSCounters)
   fun == :counters && continue
-  @eval increment!(nls::AbstractNLSModel, ::Val{$(Meta.quot(fun))}) = nls.counters.$fun += 1
+  @eval increment!(nls::AbstractNLSModel, ::Val{$(Meta.quot(fun))}) = get_counters(nls).$fun += 1
 end
 
 for fun in fieldnames(Counters)
   @eval $NLPModels.increment!(nls::AbstractNLSModel, ::Val{$(Meta.quot(fun))}) =
-    nls.counters.counters.$fun += 1
+    get_counters(nls).counters.$fun += 1
 end
 
 function LinearOperators.reset!(nls::AbstractNLSModel)
-  reset!(nls.counters)
+  reset!(get_counters(nls))
   return nls
 end
 

src/nls/show.jl

@@ -1,7 +1,7 @@
 function Base.show(io::IO, nls::AbstractNLSModel)
   show_header(io, nls)
   show(io, nls.meta, nls.nls_meta)
-  show(io, nls.counters)
+  show(io, get_counters(nls))
 end
 
 """

test/nlp/utils.jl

@@ -22,6 +22,6 @@ end
   nlp = SuperNLPModel{Float64, Vector{Float64}}(SimpleNLPModel())
   increment!(nlp, :neval_obj)
   @test neval_obj(nlp.model) == 1
-  @test nlp.counters == nlp.model.counters
+  @test get_counters(nlp) == get_counters(nlp.model)
   @test neval_hprod(nlp) == 0  # because counters are forwarded, even though neval_hprod has not been forwarded
 end