refactor: Move NonlinearSolvePolyAlgorithm to Base

Project.toml

@@ -89,7 +89,7 @@ NLSolvers = "0.5"
 NLsolve = "4.5"
 NaNMath = "1"
 NonlinearProblemLibrary = "0.1.2"
-NonlinearSolveBase = "1.2"
+NonlinearSolveBase = "1.3"
 NonlinearSolveFirstOrder = "1"
 NonlinearSolveQuasiNewton = "1"
 NonlinearSolveSpectralMethods = "1"

lib/NonlinearSolveBase/Project.toml

@@ -1,7 +1,7 @@
 name = "NonlinearSolveBase"
 uuid = "be0214bd-f91f-a760-ac4e-3421ce2b2da0"
 authors = ["Avik Pal <[email protected]> and contributors"]
-version = "1.2.0"
+version = "1.3.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"

lib/NonlinearSolveBase/src/NonlinearSolveBase.jl

@@ -47,6 +47,7 @@ include("linear_solve.jl")
 include("timer_outputs.jl")
 include("tracing.jl")
 include("wrappers.jl")
+include("polyalg.jl")
 
 include("descent/common.jl")
 include("descent/newton.jl")
@@ -81,4 +82,6 @@ export RelTerminationMode, AbsTerminationMode,
 export DescentResult, SteepestDescent, NewtonDescent, DampedNewtonDescent, Dogleg,
        GeodesicAcceleration
 
+export NonlinearSolvePolyAlgorithm
+
 end

lib/NonlinearSolveBase/src/polyalg.jl

@@ -0,0 +1,202 @@
+"""
+    NonlinearSolvePolyAlgorithm(algs; start_index::Int = 1)
+
+A general way to define PolyAlgorithms for `NonlinearProblem` and
+`NonlinearLeastSquaresProblem`. This is a container for a tuple of algorithms that will be
+tried in order until one succeeds. If none succeed, then the algorithm with the lowest
+residual is returned.
+
+### Arguments
+
+  - `algs`: a tuple of algorithms to try in-order! (If this is not a Tuple, then the
+    returned algorithm is not type-stable).
+
+### Keyword Arguments
+
+  - `start_index`: the index to start at. Defaults to `1`.
+
+### Example
+
+```julia
+using NonlinearSolve
+
+alg = NonlinearSolvePolyAlgorithm((NewtonRaphson(), Broyden()))
+```
+"""
+@concrete struct NonlinearSolvePolyAlgorithm <: AbstractNonlinearSolveAlgorithm
+    static_length <: Val
+    algs <: Tuple
+    start_index::Int
+end
+
+function NonlinearSolvePolyAlgorithm(algs; start_index::Int = 1)
+    @assert 0 < start_index ≤ length(algs)
+    algs = Tuple(algs)
+    return NonlinearSolvePolyAlgorithm(Val(length(algs)), algs, start_index)
+end
+
+@concrete mutable struct NonlinearSolvePolyAlgorithmCache <: AbstractNonlinearSolveCache
+    static_length <: Val
+    prob <: AbstractNonlinearProblem
+
+    caches <: Tuple
+    alg <: NonlinearSolvePolyAlgorithm
+
+    best::Int
+    current::Int
+    nsteps::Int
+
+    stats::NLStats
+    total_time::Float64
+    maxtime
+
+    retcode::ReturnCode.T
+    force_stop::Bool
+
+    maxiters::Int
+    internalnorm
+
+    u0
+    u0_aliased
+    alias_u0::Bool
+end
+
+function SII.symbolic_container(cache::NonlinearSolvePolyAlgorithmCache)
+    return cache.caches[cache.current]
+end
+SII.state_values(cache::NonlinearSolvePolyAlgorithmCache) = cache.u0
+
+function Base.show(io::IO, ::MIME"text/plain", cache::NonlinearSolvePolyAlgorithmCache)
+    println(io, "NonlinearSolvePolyAlgorithmCache with \
+                 $(Utils.unwrap_val(cache.static_length)) algorithms:")
+    best_alg = ifelse(cache.best == -1, "nothing", cache.best)
+    println(io, "    Best Algorithm: $(best_alg)")
+    println(
+        io, "    Current Algorithm: [$(cache.current) / $(Utils.unwrap_val(cache.static_length))]"
+    )
+    println(io, "    nsteps: $(cache.nsteps)")
+    println(io, "    retcode: $(cache.retcode)")
+    print(io, "    Current Cache: ")
+    NonlinearSolveBase.show_nonlinearsolve_cache(io, cache.caches[cache.current], 4)
+end
+
+function InternalAPI.reinit!(
+        cache::NonlinearSolvePolyAlgorithmCache, args...; p = cache.p, u0 = cache.u0
+)
+    foreach(cache.caches) do cache
+        InternalAPI.reinit!(cache, args...; p, u0)
+    end
+    cache.current = cache.alg.start_index
+    InternalAPI.reinit!(cache.stats)
+    cache.nsteps = 0
+    cache.total_time = 0.0
+end
+
+function SciMLBase.__init(
+        prob::AbstractNonlinearProblem, alg::NonlinearSolvePolyAlgorithm, args...;
+        stats = NLStats(0, 0, 0, 0, 0), maxtime = nothing, maxiters = 1000,
+        internalnorm = L2_NORM, alias_u0 = false, verbose = true, kwargs...
+)
+    if alias_u0 && !ArrayInterface.ismutable(prob.u0)
+        verbose && @warn "`alias_u0` has been set to `true`, but `u0` is \
+                          immutable (checked using `ArrayInterface.ismutable`)."
+        alias_u0 = false  # If immutable don't care about aliasing
+    end
+
+    u0 = prob.u0
+    u0_aliased = alias_u0 ? copy(u0) : u0
+    alias_u0 && (prob = SciMLBase.remake(prob; u0 = u0_aliased))
+
+    return NonlinearSolvePolyAlgorithmCache(
+        alg.static_length, prob,
+        map(alg.algs) do solver
+            SciMLBase.__init(
+                prob, solver, args...;
+                stats, maxtime, internalnorm, alias_u0, verbose, kwargs...
+            )
+        end,
+        alg, -1, alg.start_index, 0, stats, 0.0, maxtime,
+        ReturnCode.Default, false, maxiters, internalnorm,
+        u0, u0_aliased, alias_u0
+    )
+end
+
+@generated function InternalAPI.step!(
+        cache::NonlinearSolvePolyAlgorithmCache{Val{N}}, args...; kwargs...
+) where {N}
+    calls = []
+    cache_syms = [gensym("cache") for i in 1:N]
+    for i in 1:N
+        push!(calls,
+            quote
+                $(cache_syms[i]) = cache.caches[$(i)]
+                if $(i) == cache.current
+                    InternalAPI.step!($(cache_syms[i]), args...; kwargs...)
+                    $(cache_syms[i]).nsteps += 1
+                    if !NonlinearSolveBase.not_terminated($(cache_syms[i]))
+                        if SciMLBase.successful_retcode($(cache_syms[i]).retcode)
+                            cache.best = $(i)
+                            cache.force_stop = true
+                            cache.retcode = $(cache_syms[i]).retcode
+                        else
+                            cache.current = $(i + 1)
+                        end
+                    end
+                    return
+                end
+            end)
+    end
+
+    push!(calls, quote
+        if !(1 ≤ cache.current ≤ length(cache.caches))
+            minfu, idx = findmin_caches(cache.prob, cache.caches)
+            cache.best = idx
+            cache.retcode = cache.caches[idx].retcode
+            cache.force_stop = true
+            return
+        end
+    end)
+
+    return Expr(:block, calls...)
+end
+
+# Original is often determined on runtime information especially for PolyAlgorithms so it
+# is best to never specialize on that
+function build_solution_less_specialize(
+        prob::AbstractNonlinearProblem, alg, u, resid;
+        retcode = ReturnCode.Default, original = nothing, left = nothing,
+        right = nothing, stats = nothing, trace = nothing, kwargs...
+)
+    return SciMLBase.NonlinearSolution{
+        eltype(eltype(u)), ndims(u), typeof(u), typeof(resid), typeof(prob),
+        typeof(alg), Any, typeof(left), typeof(stats), typeof(trace)
+    }(
+        u, resid, prob, alg, retcode, original, left, right, stats, trace
+    )
+end
+
+function findmin_caches(prob::AbstractNonlinearProblem, caches)
+    resids = map(caches) do cache
+        cache === nothing && return nothing
+        return NonlinearSolveBase.get_fu(cache)
+    end
+    return findmin_resids(prob, resids)
+end
+
+@views function findmin_resids(prob::AbstractNonlinearProblem, caches)
+    norm_fn = prob isa NonlinearLeastSquaresProblem ? Base.Fix2(norm, 2) :
+              Base.Fix2(norm, Inf)
+    idx = findfirst(Base.Fix2(!==, nothing), caches)
+    # This is an internal function so we assume that inputs are consistent and there is
+    # atleast one non-`nothing` value
+    fx_idx = norm_fn(caches[idx])
+    idx == length(caches) && return fx_idx, idx
+    fmin = @closure xᵢ -> begin
+        xᵢ === nothing && return oftype(fx_idx, Inf)
+        fx = norm_fn(xᵢ)
+        return ifelse(isnan(fx), oftype(fx, Inf), fx)
+    end
+    x_min, x_min_idx = findmin(fmin, caches[(idx + 1):length(caches)])
+    x_min < fx_idx && return x_min, x_min_idx + idx
+    return fx_idx, idx
+end