format

Author: utkarsh530

benchmarks/CPU_vs_GPU/benchmark.jl

@@ -77,7 +77,8 @@ for n_particles in Ns
     ## CPU solve
     backend = CPU()
     opt = ParallelSyncPSOKernel(n_particles; backend)
-    init_gbest, particles = ParallelParticleSwarms.init_particles(prob, opt, typeof(prob.u0))
+    init_gbest, particles = ParallelParticleSwarms.init_particles(
+        prob, opt, typeof(prob.u0))
 
     particles_eltype = eltype(particles) === Float64 ? Float32 : eltype(particles)
 

src/ode_pso.jl

@@ -92,7 +92,8 @@ function parameter_estim_ode!(prob::ODEProblem, cache,
 
         KernelAbstractions.synchronize(backend)
 
-        gbest = ParallelParticleSwarms.SPSOGBest(best_particle.best_position, best_particle.best_cost)
+        gbest = ParallelParticleSwarms.SPSOGBest(
+            best_particle.best_position, best_particle.best_cost)
         w = w * wdamp
     end
     return gbest
@@ -145,7 +146,8 @@ function parameter_estim_ode!(prob::ODEProblem, cache,
 
         KernelAbstractions.synchronize(backend)
 
-        gbest = ParallelParticleSwarms.SPSOGBest(best_particle.best_position, best_particle.best_cost)
+        gbest = ParallelParticleSwarms.SPSOGBest(
+            best_particle.best_position, best_particle.best_cost)
         w = w * wdamp
     end
     return gbest

test/lbfgs.jl

@@ -44,7 +44,8 @@ l0 = rosenbrock(x0, p)
 @show sol.objective
 
 @time sol = Optimization.solve(prob,
-    ParallelParticleSwarms.HybridPSO(; local_opt = ParallelParticleSwarms.BFGS(), backend = backend),
+    ParallelParticleSwarms.HybridPSO(;
+        local_opt = ParallelParticleSwarms.BFGS(), backend = backend),
     maxiters = 30)
 @show sol.objective
 
@@ -67,6 +68,7 @@ l0 = rosenbrock(x0, p)
 @show sol.objective
 
 @time sol = Optimization.solve(prob,
-    ParallelParticleSwarms.HybridPSO(; local_opt = ParallelParticleSwarms.BFGS(), backend = backend),
+    ParallelParticleSwarms.HybridPSO(;
+        local_opt = ParallelParticleSwarms.BFGS(), backend = backend),
     local_maxiters = 30)
 @show sol.objective

test/regression.jl

@@ -1,4 +1,5 @@
-using ParallelParticleSwarms, StaticArrays, SciMLBase, Test, LinearAlgebra, Random, KernelAbstractions
+using ParallelParticleSwarms, StaticArrays, SciMLBase, Test, LinearAlgebra, Random,
+      KernelAbstractions
 using QuasiMonteCarlo
 
 @testset "Rosenbrock test dimension = $(N)" for N in 2:3

test/reinit.jl

@@ -1,4 +1,5 @@
-using ParallelParticleSwarms, StaticArrays, SciMLBase, Test, LinearAlgebra, Random, KernelAbstractions
+using ParallelParticleSwarms, StaticArrays, SciMLBase, Test, LinearAlgebra, Random,
+      KernelAbstractions
 using QuasiMonteCarlo
 
 ## Solving the rosenbrock problem
@@ -28,10 +29,14 @@ cache = init(prob, ParallelSyncPSOKernel(n_particles; backend = CPU()))
 
 reinit!(cache)
 
-cache = init(prob, ParallelParticleSwarms.HybridPSO(; local_opt = ParallelParticleSwarms.BFGS(), backend = CPU()))
+cache = init(prob,
+    ParallelParticleSwarms.HybridPSO(;
+        local_opt = ParallelParticleSwarms.BFGS(), backend = CPU()))
 
 reinit!(cache)
 
-cache = init(prob, ParallelParticleSwarms.HybridPSO(; local_opt = ParallelParticleSwarms.LBFGS(), backend = CPU()))
+cache = init(prob,
+    ParallelParticleSwarms.HybridPSO(;
+        local_opt = ParallelParticleSwarms.LBFGS(), backend = CPU()))
 
 reinit!(cache)