Merge pull request #56 from ChrisRackauckas/fix-formatting

Apply JuliaFormatter to fix code formatting

Author: ChrisRackauckas

README.md

@@ -3,7 +3,7 @@
 [![CI](https://github.com/SciML/ParallelParticleSwarms.jl/actions/workflows/CI.yml/badge.svg)](https://github.com/SciML/ParallelParticleSwarms.jl/actions/workflows/CI.yml)
 [![Build status](https://badge.buildkite.com/caf5d6f9d5129b5796049b085df39fd8fab055826b513d361e.svg)](https://buildkite.com/julialang/parallelparticleswarms-dot-jl)
 [![codecov](https://codecov.io/gh/utkarsh530/ParallelParticleSwarms.jl/graph/badge.svg?token=H5U5UAIRXX)](https://codecov.io/gh/utkarsh530/ParallelParticleSwarms.jl)
-[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
+[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor%27s%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
 [![SciML Code Style](https://img.shields.io/static/v1?label=code%20style&message=SciML&color=9558b2&labelColor=389826)](https://github.com/SciML/SciMLStyle)
 
 Accelerating convex/non-convex optimization with GPUs using Particle-Swarm based methods.

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(
+    init_gbest,
+    particles = ParallelParticleSwarms.init_particles(
         prob, opt, typeof(prob.u0))
 
     particles_eltype = eltype(particles) === Float64 ? Float32 : eltype(particles)

benchmarks/CPU_vs_GPU/wp_algs.jl

@@ -105,36 +105,41 @@ end
 for n_particles in Ns
     @info n_particles
 
-    obj, sol_time = solve_run(prob,
+    obj,
+    sol_time = solve_run(prob,
         ParallelSyncPSOKernel(n_particles; backend = CPU()),
         500)
 
     push!(cpu_loss, obj)
     push!(cpu_times, sol_time)
 
-    obj, sol_time = solve_run(prob,
+    obj,
+    sol_time = solve_run(prob,
         ParallelSyncPSOKernel(n_particles; backend = CUDABackend()),
         500)
 
     push!(gpu_sync_loss, obj)
     push!(gpu_sync_times, sol_time)
 
-    obj, sol_time = solve_run(prob,
+    obj,
+    sol_time = solve_run(prob,
         ParallelPSOKernel(n_particles; backend = CUDABackend(), global_update = false),
         500)
 
     push!(gpu_async_loss, obj)
     push!(gpu_async_times, sol_time)
 
-    obj, sol_time = solve_run(prob,
+    obj,
+    sol_time = solve_run(prob,
         ParallelPSOKernel(n_particles; backend = CUDABackend(), global_update = true),
         500;
         runs = 2)
 
     push!(gpu_queue_lock_loss, obj)
     push!(gpu_queue_lock_times, sol_time)
 
-    obj, solve_time = solve_run(prob,
+    obj,
+    solve_time = solve_run(prob,
         ParallelParticleSwarms.HybridPSO(; backend = CUDABackend(),
             pso = ParallelParticleSwarms.ParallelPSOKernel(n_particles;
                 global_update = false,
@@ -330,7 +335,8 @@ begin
     for iters in tot_maxiters
         @info iters
 
-        obj, sol_time = solve_run(uncons_prob,
+        obj,
+        sol_time = solve_run(uncons_prob,
             LBFGS(),
             iters;
             reltol = -Inf,
@@ -362,14 +368,16 @@ begin
         # ParallelPSOKernel(n_particles; backend = CUDABackend(), global_update = true),
         # maxiters = iters)
 
-        obj, sol_time = solve_run(prob,
+        obj,
+        sol_time = solve_run(prob,
             ParallelPSOKernel(n_particles; backend = CUDABackend(), global_update = true),
             iters)
 
         push!(queue_lock_losses, obj)
         push!(queue_lock_time, sol_time)
 
-        obj, sol_time = solve_run(prob,
+        obj,
+        sol_time = solve_run(prob,
             ParallelSyncPSOKernel(n_particles; backend = CPU()),
             iters)
 
@@ -388,7 +396,8 @@ begin
         #         local_opt = ParallelParticleSwarms.LBFGS()), maxiters = iters,
         #         local_maxiters = iters)
 
-        obj, solve_time = solve_run(prob,
+        obj,
+        solve_time = solve_run(prob,
             ParallelParticleSwarms.HybridPSO(; backend = CUDABackend(),
                 pso = ParallelParticleSwarms.ParallelPSOKernel(n_particles;
                     global_update = false,
@@ -402,7 +411,8 @@ begin
 
         # sol = solve(arr_prob, BBO_adaptive_de_rand_1_bin_radiuslimited(), maxiters = iters)
 
-        obj, sol_time = solve_run(arr_prob,
+        obj,
+        sol_time = solve_run(arr_prob,
             BBO_adaptive_de_rand_1_bin_radiuslimited(),
             iters * 100)
 

benchmarks/adam_opt.jl

@@ -100,7 +100,8 @@ using Adapt
 backend = CUDABackend()
 
 ## Initialize Particles
-gbest, particles = ParallelParticleSwarms.init_particles(soptprob,
+gbest,
+particles = ParallelParticleSwarms.init_particles(soptprob,
     ParallelSyncPSOKernel(n_particles; backend = CUDABackend()),
     typeof(prob.u0))
 

src/hybrid.jl

@@ -47,8 +47,9 @@ function SciMLBase.solve!(
     sol_bfgs = (x -> isnan(x) ? convert(eltype(prob.u0), Inf) : x).(sol_bfgs)
 
     minobj, ind = findmin(sol_bfgs)
-    sol_u, sol_obj = minobj > sol_pso.objective ? (sol_pso.u, sol_pso.objective) :
-                     (view(result, ind), minobj)
+    sol_u,
+    sol_obj = minobj > sol_pso.objective ? (sol_pso.u, sol_pso.objective) :
+              (view(result, ind), minobj)
     t1 = time()
 
     # @show sol_pso.stats.time

src/solve.jl

@@ -11,7 +11,8 @@ function SciMLBase.solve!(
         cache::PSOCache, opt::ParallelPSOKernel, args...; maxiters = 100, kwargs...)
     prob = cache.prob
     t0 = time()
-    gbest, particles = vectorized_solve!(cache.prob,
+    gbest,
+    particles = vectorized_solve!(cache.prob,
         cache.gbest,
         cache.particles,
         opt,
@@ -30,7 +31,8 @@ function SciMLBase.solve!(
         cache::PSOCache, opt::ParallelSyncPSOKernel, args...; maxiters = 100, kwargs...)
     prob = cache.prob
     t0 = time()
-    gbest, particles = vectorized_solve!(prob,
+    gbest,
+    particles = vectorized_solve!(prob,
         cache.gbest,
         cache.particles,
         opt,
@@ -73,7 +75,8 @@ function pso_solve(prob::OptimizationProblem,
         kwargs...)
     init_gbest, particles = init_particles(prob, opt, typeof(prob.u0))
     t0 = time()
-    gbest, particles = vectorized_solve!(prob,
+    gbest,
+    particles = vectorized_solve!(prob,
         init_gbest,
         particles,
         opt,