R2-solve!-0-allocation

src/R2_alg.jl

@@ -380,6 +380,7 @@ function SolverCore.solve!(
   end
 
   local ξ::T
+  local ρk::T
   σk = max(1 / ν, σmin)
   ν = 1 / σk
   sqrt_ξ_νInv = one(T)
@@ -438,7 +439,7 @@ function SolverCore.solve!(
     improper = (hkn == -Inf)
 
     Δobj = (fk + hk) - (fkn + hkn) + max(1, abs(fk + hk)) * 10 * eps()
-    global ρk = Δobj / ξ
+    ρk = Δobj / ξ
 
     verbose > 0 &&
       stats.iter % verbose == 0 &&

test/runtests.jl

@@ -1,7 +1,7 @@
 using LinearAlgebra: length
 using LinearAlgebra, Random, Test
 using ProximalOperators
-using NLPModels, NLPModelsModifiers, RegularizedProblems, RegularizedOptimization
+using NLPModels, NLPModelsModifiers, RegularizedProblems, RegularizedOptimization, SolverCore
 
 const global compound = 1
 const global nz = 10 * compound
@@ -135,3 +135,4 @@ for (h, h_name) ∈ ((NormL1(λ), "l1"),)
 end
 
 include("test_bounds.jl")
+include("test_allocs.jl")

test/test_allocs.jl

@@ -0,0 +1,49 @@
+"""
+    @wrappedallocs(expr)
+
+Given an expression, this macro wraps that expression inside a new function
+which will evaluate that expression and measure the amount of memory allocated
+by the expression. Wrapping the expression in a new function allows for more
+accurate memory allocation detection when using global variables (e.g. when
+at the REPL).
+
+This code is based on that of https://github.com/JuliaAlgebra/TypedPolynomials.jl/blob/master/test/runtests.jl
+
+For example, `@wrappedallocs(x + y)` produces:
+
+```julia
+function g(x1, x2)
+    @allocated x1 + x2
+end
+g(x, y)
+```
+
+You can use this macro in a unit test to verify that a function does not
+allocate:
+
+```
+@test @wrappedallocs(x + y) == 0
+```
+"""
+macro wrappedallocs(expr)
+    argnames = [gensym() for a in expr.args]
+    quote
+        function g($(argnames...))
+            @allocated $(Expr(expr.head, argnames...))
+        end
+        $(Expr(:call, :g, [esc(a) for a in expr.args]...))
+    end
+end
+
+
+# Test non allocating solve!
+@testset "allocs" begin
+    for (h, h_name) ∈ ((NormL0(λ), "l0"), (NormL1(λ), "l1"))
+      for solver ∈ (:R2Solver, )
+        reg_nlp = RegularizedNLPModel(bpdn, h)
+        solver = eval(solver)(reg_nlp)
+        stats = GenericExecutionStats(bpdn, solver_specific = Dict{Symbol, Float64}())
+        @test @wrappedallocs(solve!(solver, reg_nlp, stats)) == 0
+      end
+    end
+end