🤖 Format .jl files

Author: amontoison

benchmark/run_local.jl

@@ -33,7 +33,7 @@ else
 end
 
 @info "RUN"
-@time result = with_logger(ConsoleLogger(Error)) do # remove warnings
+@time result = with_logger(ConsoleLogger(Error)) do  # remove warnings
   if "params.json" in (path == "" ? readdir() : readdir(path))
     loadparams!(suite, BenchmarkTools.load("params.json")[1], :evals, :samples)
   end

src/ad.jl

@@ -300,8 +300,7 @@ function ADModelNLSBackend(
 
   JBLS = jacobian_residual_backend
   b = @elapsed begin
-    jacobian_residual_backend =
-      if jacobian_residual_backend isa Union{AbstractNLPModel, ADBackend}
+    jacobian_residual_backend = if jacobian_residual_backend isa Union{AbstractNLPModel, ADBackend}
         jacobian_residual_backend
       else
         JBLS(nvar, x -> zero(eltype(x)), nequ, F!; show_time, kwargs...)
@@ -467,8 +466,7 @@ function ADModelNLSBackend(
 
   JBLS = jacobian_residual_backend
   b = @elapsed begin
-    jacobian_residual_backend =
-      if jacobian_residual_backend isa Union{AbstractNLPModel, ADBackend}
+    jacobian_residual_backend = if jacobian_residual_backend isa Union{AbstractNLPModel, ADBackend}
         jacobian_residual_backend
       else
         JBLS(nvar, x -> zero(eltype(x)), nequ, F!; show_time, kwargs...)

test/gpu.jl

@@ -16,6 +16,7 @@ end
 )
   @testset "Checking GPU multiple precision on problem $problem" for problem in
                                                                      NLPModelsTest.nlp_problems
+
     nlp_from_T = eval(Meta.parse(lowercase(problem) * "_autodiff"))
     CUDA.allowscalar() do
       # sparse Jacobian/Hessian doesn't work here
@@ -39,6 +40,7 @@ end
 )
   @testset "Checking GPU multiple precision on problem $problem" for problem in
                                                                      NLPModelsTest.nls_problems
+
     nls_from_T = eval(Meta.parse(lowercase(problem) * "_autodiff"))
     CUDA.allowscalar() do
       # sparse Jacobian/Hessian doesn't work here

test/nlp/nlpmodelstest.jl

@@ -1,6 +1,7 @@
 function nlp_nlpmodelstest(backend)
   @testset "Checking NLPModelsTest tests on problem $problem" for problem in
                                                                   NLPModelsTest.nlp_problems
+
     nlp_from_T = eval(Meta.parse(lowercase(problem) * "_autodiff"))
     nlp_ad = nlp_from_T(; backend = backend)
     nlp_man = eval(Meta.parse(problem))()

test/nls/nlpmodelstest.jl

@@ -1,6 +1,7 @@
 function nls_nlpmodelstest(backend)
   @testset "Checking NLPModelsTest tests on problem $problem" for problem in
                                                                   NLPModelsTest.nls_problems
+
     nls_from_T = eval(Meta.parse(lowercase(problem) * "_autodiff"))
     nls_ad = nls_from_T(; backend = backend)
     nls_man = eval(Meta.parse(problem))()