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Jf/unstick juliaformatter #557

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2 changes: 1 addition & 1 deletion docs/src/basics/FAQ.md
Original file line number Diff line number Diff line change
Expand Up @@ -83,5 +83,5 @@ Pl = LinearSolve.ComposePreconditioner(LinearSolve.InvPreconditioner(Diagonal(we
Pr = Diagonal(weights)

prob = LinearProblem(A, b)
sol = solve(prob, KrylovJL_GMRES(precs=Returns((Pl,Pr))))
sol = solve(prob, KrylovJL_GMRES(precs = Returns((Pl, Pr))))
```
7 changes: 5 additions & 2 deletions ext/LinearSolvePardisoExt.jl
Original file line number Diff line number Diff line change
Expand Up @@ -134,11 +134,14 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::PardisoJL; kwargs
if cache.isfresh
phase = alg.cache_analysis ? Pardiso.NUM_FACT : Pardiso.ANALYSIS_NUM_FACT
Pardiso.set_phase!(cache.cacheval, phase)
Pardiso.pardiso(cache.cacheval, SparseMatrixCSC(size(A)..., getcolptr(A), rowvals(A), nonzeros(A)), eltype(A)[])
Pardiso.pardiso(cache.cacheval,
SparseMatrixCSC(size(A)..., getcolptr(A), rowvals(A), nonzeros(A)),
eltype(A)[])
cache.isfresh = false
end
Pardiso.set_phase!(cache.cacheval, Pardiso.SOLVE_ITERATIVE_REFINE)
Pardiso.pardiso(cache.cacheval, u, SparseMatrixCSC(size(A)..., getcolptr(A), rowvals(A), nonzeros(A)), b)
Pardiso.pardiso(cache.cacheval, u,
SparseMatrixCSC(size(A)..., getcolptr(A), rowvals(A), nonzeros(A)), b)
return SciMLBase.build_linear_solution(alg, cache.u, nothing, cache)
end

Expand Down
75 changes: 38 additions & 37 deletions src/LinearSolve.jl
Original file line number Diff line number Diff line change
Expand Up @@ -5,47 +5,48 @@ if isdefined(Base, :Experimental) &&
end

import PrecompileTools
using ArrayInterface
using RecursiveFactorization
using Base: cache_dependencies, Bool
using LinearAlgebra
using SparseArrays
using SparseArrays: AbstractSparseMatrixCSC, nonzeros, rowvals, getcolptr
using LazyArrays: @~, BroadcastArray
using SciMLBase: AbstractLinearAlgorithm
using SciMLOperators
using SciMLOperators: AbstractSciMLOperator, IdentityOperator
using Setfield
using UnPack
using KLU
using Sparspak
using FastLapackInterface
using DocStringExtensions
using EnumX
using Markdown
using ChainRulesCore
import InteractiveUtils

import StaticArraysCore: StaticArray, SVector, MVector, SMatrix, MMatrix

using LinearAlgebra: BlasInt, LU
using LinearAlgebra.LAPACK: require_one_based_indexing,
chkfinite, chkstride1,
@blasfunc, chkargsok

import GPUArraysCore
import Preferences
import ConcreteStructs: @concrete

# wrap
import Krylov
using SciMLBase
import Preferences
using ArrayInterface
using RecursiveFactorization
using Base: cache_dependencies, Bool
using LinearAlgebra
using SparseArrays
using SparseArrays: AbstractSparseMatrixCSC, nonzeros, rowvals, getcolptr
using LazyArrays: @~, BroadcastArray
using SciMLBase: AbstractLinearAlgorithm
using SciMLOperators
using SciMLOperators: AbstractSciMLOperator, IdentityOperator
using Setfield
using UnPack
using KLU
using Sparspak
using FastLapackInterface
using DocStringExtensions
using EnumX
using Markdown
using ChainRulesCore
import InteractiveUtils

import StaticArraysCore: StaticArray, SVector, MVector, SMatrix, MMatrix

using LinearAlgebra: BlasInt, LU
using LinearAlgebra.LAPACK: require_one_based_indexing,
chkfinite, chkstride1,
@blasfunc, chkargsok

import GPUArraysCore
import Preferences
import ConcreteStructs: @concrete

# wrap
import Krylov
using SciMLBase
import Preferences

const CRC = ChainRulesCore

@static if Sys.ARCH === :x86_64 || Sys.ARCH === :i686
if Preferences.@load_preference("LoadMKL_JLL", !occursin("EPYC", Sys.cpu_info()[1].model))
if Preferences.@load_preference("LoadMKL_JLL",
!occursin("EPYC", Sys.cpu_info()[1].model))
using MKL_jll
const usemkl = MKL_jll.is_available()
else
Expand Down
25 changes: 13 additions & 12 deletions src/common.jl
Original file line number Diff line number Diff line change
Expand Up @@ -150,7 +150,7 @@ function SciMLBase.init(prob::LinearProblem, alg::SciMLLinearSolveAlgorithm,
assumptions = OperatorAssumptions(issquare(prob.A)),
sensealg = LinearSolveAdjoint(),
kwargs...)
(;A, b, u0, p) = prob
(; A, b, u0, p) = prob

A = if alias_A || A isa SMatrix
A
Expand Down Expand Up @@ -206,22 +206,21 @@ function SciMLBase.init(prob::LinearProblem, alg::SciMLLinearSolveAlgorithm,

cache = LinearCache{typeof(A), typeof(b), typeof(u0_), typeof(p), typeof(alg), Tc,
typeof(Pl), typeof(Pr), typeof(reltol), typeof(assumptions.issq),
typeof(sensealg)}(A, b, u0_, p, alg, cacheval, isfresh, precsisfresh, Pl, Pr, abstol, reltol,
typeof(sensealg)}(
A, b, u0_, p, alg, cacheval, isfresh, precsisfresh, Pl, Pr, abstol, reltol,
maxiters, verbose, assumptions, sensealg)
return cache
end


function SciMLBase.reinit!(cache::LinearCache;
A = nothing,
b = cache.b,
u = cache.u,
p = nothing,
reinit_cache = false,
reuse_precs = false)
A = nothing,
b = cache.b,
u = cache.u,
p = nothing,
reinit_cache = false,
reuse_precs = false)
(; alg, cacheval, abstol, reltol, maxiters, verbose, assumptions, sensealg) = cache


isfresh = !isnothing(A)
precsisfresh = !reuse_precs && (isfresh || !isnothing(p))
isfresh |= cache.isfresh
Expand All @@ -234,9 +233,11 @@ function SciMLBase.reinit!(cache::LinearCache;
Pl = cache.Pl
Pr = cache.Pr
if reinit_cache
return LinearCache{typeof(A), typeof(b), typeof(u), typeof(p), typeof(alg), typeof(cacheval),
return LinearCache{
typeof(A), typeof(b), typeof(u), typeof(p), typeof(alg), typeof(cacheval),
typeof(Pl), typeof(Pr), typeof(reltol), typeof(assumptions.issq),
typeof(sensealg)}(A, b, u, p, alg, cacheval, precsisfresh, isfresh, Pl, Pr, abstol, reltol,
typeof(sensealg)}(
A, b, u, p, alg, cacheval, precsisfresh, isfresh, Pl, Pr, abstol, reltol,
maxiters, verbose, assumptions, sensealg)
else
cache.A = A
Expand Down
8 changes: 4 additions & 4 deletions src/default.jl
Original file line number Diff line number Diff line change
Expand Up @@ -179,8 +179,8 @@ function defaultalg(A, b, assump::OperatorAssumptions{Bool})
__conditioning(assump) === OperatorCondition.WellConditioned)
if length(b) <= 10
DefaultAlgorithmChoice.RFLUFactorization
elseif appleaccelerate_isavailable() && b isa Array &&
eltype(b) <: Union{Float32, Float64, ComplexF32, ComplexF64}
elseif appleaccelerate_isavailable() && b isa Array &&
eltype(b) <: Union{Float32, Float64, ComplexF32, ComplexF64}
DefaultAlgorithmChoice.AppleAccelerateLUFactorization
elseif (length(b) <= 100 || (isopenblas() && length(b) <= 500) ||
(usemkl && length(b) <= 200)) &&
Expand All @@ -189,8 +189,8 @@ function defaultalg(A, b, assump::OperatorAssumptions{Bool})
DefaultAlgorithmChoice.RFLUFactorization
#elseif A === nothing || A isa Matrix
# alg = FastLUFactorization()
elseif usemkl && b isa Array &&
eltype(b) <: Union{Float32, Float64, ComplexF32, ComplexF64}
elseif usemkl && b isa Array &&
eltype(b) <: Union{Float32, Float64, ComplexF32, ComplexF64}
DefaultAlgorithmChoice.MKLLUFactorization
else
DefaultAlgorithmChoice.LUFactorization
Expand Down
2 changes: 1 addition & 1 deletion src/extension_algs.jl
Original file line number Diff line number Diff line change
Expand Up @@ -217,7 +217,7 @@ All values default to `nothing` and the solver internally determines the values
given the input types, and these keyword arguments are only for overriding the
default handling process. This should not be required by most users.
"""
struct PardisoJL{T1, T2} <: AbstractSparseFactorization
struct PardisoJL{T1, T2} <: AbstractSparseFactorization
nprocs::Union{Int, Nothing}
solver_type::T1
matrix_type::T2
Expand Down
33 changes: 16 additions & 17 deletions test/basictests.jl
Original file line number Diff line number Diff line change
Expand Up @@ -267,12 +267,12 @@ end

@testset "KrylovJL" begin
kwargs = (; gmres_restart = 5)
precs = (A,p=nothing) -> (BlockJacobiPreconditioner(A, 2), I)
precs = (A, p = nothing) -> (BlockJacobiPreconditioner(A, 2), I)
algorithms = (
("Default", KrylovJL(kwargs...)),
("CG", KrylovJL_CG(kwargs...)),
("GMRES", KrylovJL_GMRES(kwargs...)),
("GMRES_prec", KrylovJL_GMRES(;precs, ldiv=false, kwargs...)),
("GMRES_prec", KrylovJL_GMRES(; precs, ldiv = false, kwargs...)),
# ("BICGSTAB",KrylovJL_BICGSTAB(kwargs...)),
("MINRES", KrylovJL_MINRES(kwargs...))
)
Expand Down Expand Up @@ -579,28 +579,27 @@ end
# test default algorithn
@time "solve MySparseMatrixCSC" u=solve(pr)
@test norm(u - u0, Inf) < 1.0e-13

# test Krylov algorithm with reinit!
pr = LinearProblem(B, b)
solver=KrylovJL_CG()
cache=init(pr,solver,maxiters=1000,reltol=1.0e-10)
u=solve!(cache)
solver = KrylovJL_CG()
cache = init(pr, solver, maxiters = 1000, reltol = 1.0e-10)
u = solve!(cache)
A1 = spdiagm(1 => -ones(N - 1), 0 => fill(100.0, N), -1 => -ones(N - 1))
b1=A1*u0
B1= MySparseMatrixCSC(A1)
b1 = A1 * u0
B1 = MySparseMatrixCSC(A1)
@test norm(u - u0, Inf) < 1.0e-8
reinit!(cache; A=B1, b=b1)
u=solve!(cache)
reinit!(cache; A = B1, b = b1)
u = solve!(cache)
@test norm(u - u0, Inf) < 1.0e-8

# test factorization with reinit!
pr = LinearProblem(B, b)
solver=SparspakFactorization()
cache=init(pr,solver)
u=solve!(cache)
solver = SparspakFactorization()
cache = init(pr, solver)
u = solve!(cache)
@test norm(u - u0, Inf) < 1.0e-8
reinit!(cache; A=B1, b=b1)
u=solve!(cache)
reinit!(cache; A = B1, b = b1)
u = solve!(cache)
@test norm(u - u0, Inf) < 1.0e-8

end
6 changes: 3 additions & 3 deletions test/enzyme.jl
Original file line number Diff line number Diff line change
Expand Up @@ -207,9 +207,9 @@ end
@show fd_jac

en_jac = map(onehot(A)) do dA
return only(Enzyme.autodiff(set_runtime_activity(Forward), fnice,
Duplicated(A, dA), Const(b1), Const(alg)))
end |> collect
return only(Enzyme.autodiff(set_runtime_activity(Forward), fnice,
Duplicated(A, dA), Const(b1), Const(alg)))
end |> collect
@show en_jac

@test en_jac≈fd_jac rtol=1e-4
Expand Down
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