Revert the SciMLLogging (#754)

* Revert SciMLLogging

* also revert CUDA changes

* Revert the fixes

* More removals

Author: ChrisRackauckas

Project.toml

@@ -23,7 +23,6 @@ Preferences = "21216c6a-2e73-6563-6e65-726566657250"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
-SciMLLogging = "a6db7da4-7206-11f0-1eab-35f2a5dbe1d1"
 SciMLOperators = "c0aeaf25-5076-4817-a8d5-81caf7dfa961"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 StaticArraysCore = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
@@ -124,7 +123,6 @@ RecursiveFactorization = "0.2.23"
 Reexport = "1.2.2"
 SafeTestsets = "0.1"
 SciMLBase = "2.70"
-SciMLLogging = "1"
 SciMLOperators = "1"
 Setfield = "1.1.1"
 SparseArrays = "1.10"

docs/src/advanced/developing.md

@@ -19,7 +19,7 @@ struct MyLUFactorization{P} <: LinearSolve.SciMLLinearSolveAlgorithm end
 
 function LinearSolve.init_cacheval(
         alg::MyLUFactorization, A, b, u, Pl, Pr, maxiters::Int, abstol, reltol,
-        verbose::LinearVerbosity, assump::LinearSolve.OperatorAssumptions)
+        verbose::Bool, assump::LinearSolve.OperatorAssumptions)
     lu!(convert(AbstractMatrix, A))
 end
 

docs/src/basics/common_solver_opts.md

@@ -26,92 +26,3 @@ solve completely. Error controls only apply to iterative solvers.
   - `maxiters`: The number of iterations allowed. Defaults to `length(prob.b)`
   - `Pl,Pr`: The left and right preconditioners, respectively. For more information,
     see [the Preconditioners page](@ref prec).
-
-## Verbosity Controls
-
-The verbosity system in LinearSolve.jl provides fine-grained control over the diagnostic messages, warnings, and errors that are displayed during the solution of linear systems.
-
-The verbosity system is organized hierarchically into three main categories:
-
-1. Error Control - Messages related to fallbacks and error handling
-2. Performance - Messages related to performance considerations
-3. Numerical - Messages related to numerical solvers and iterations
-
-Each category can be configured independently, and individual settings can be adjusted to suit your needs.
-
-### Verbosity Levels
-The following verbosity levels are available:
-
-#### Individual Settings
-These settings are meant for individual settings within a category. These can also be used to set all of the individual settings in a group to the same value.
-- Verbosity.None() - Suppress all messages
-- Verbosity.Info() - Show message as log message at info level
-- Verbosity.Warn() - Show warnings (default for most settings)
-- Verbosity.Error() - Throw errors instead of warnings
-- Verbosity.Level(n) - Show messages with a log level setting of n
-
-#### Group Settings
-These settings are meant for controlling a group of settings. 
-- Verbosity.Default() - Use the default settings
-- Verbosity.All() - Show all possible messages
-
-### Basic Usage 
-
-#### Global Verbosity Control
-
-```julia 
-using LinearSolve
-
-# Suppress all messages
-verbose = LinearVerbosity(Verbosity.None())
-prob = LinearProblem(A, b)
-sol = solve(prob; verbose=verbose)
-
-# Show all messages
-verbose = LinearVerbosity(Verbosity.All())
-sol = solve(prob; verbose=verbose)
-
-# Use default settings
-verbose = LinearVerbosity(Verbosity.Default())
-sol = solve(prob; verbose=verbose)
-```
-
-#### Group Level Control 
-
-```julia 
-# Customize by category
-verbose = LinearVerbosity(
-    error_control = Verbosity.Warn(),   # Show warnings for error control related issues
-    performance = Verbosity.None(),     # Suppress performance messages
-    numerical = Verbosity.Info()        # Show all numerical related log messages at info level
-)
-
-sol = solve(prob; verbose=verbose)
-```
-
-#### Fine-grained Control
-The constructor for `LinearVerbosity` allows you to set verbosity for each specific message toggle, giving you fine-grained control. 
-The verbosity settings for the toggles are automatically passed to the group objects. 
-```julia
-# Set specific message types
-verbose = LinearVerbosity(
-    default_lu_fallback = Verbosity.Info(),                     # Show info when LU fallback is used
-    KrylovJL_verbosity = Verbosity.Warn(),                      # Show warnings from KrylovJL
-    no_right_preconditioning = Verbosity.None(),                # Suppress right preconditioning messages
-    KrylovKit_verbosity = Verbosity.Level(KrylovKit.WARN_LEVEL) # Set KrylovKit verbosity level using KrylovKit's own verbosity levels
-)
-
-sol = solve(prob; verbose=verbose)
-
-```
-
-#### Verbosity Levels
-##### Error Control Settings
-- default_lu_fallback: Controls messages when falling back to LU factorization (default: Warn)
-##### Performance Settings
-- no_right_preconditioning: Controls messages when right preconditioning is not used (default: Warn)
-##### Numerical Settings
-- using_IterativeSolvers: Controls messages when using the IterativeSolvers.jl package (default: Warn)
-- IterativeSolvers_iterations: Controls messages about iteration counts from IterativeSolvers.jl (default: Warn)
-- KrylovKit_verbosity: Controls messages from the KrylovKit.jl package (default: Warn)
-- KrylovJL_verbosity: Controls verbosity of the KrylovJL.jl package (default: None)

ext/LinearSolveAMDGPUExt.jl

@@ -2,8 +2,7 @@ module LinearSolveAMDGPUExt
 
 using AMDGPU
 using LinearSolve: LinearSolve, LinearCache, AMDGPUOffloadLUFactorization,
-                   AMDGPUOffloadQRFactorization, init_cacheval, OperatorAssumptions,
-                   LinearVerbosity
+                   AMDGPUOffloadQRFactorization, init_cacheval, OperatorAssumptions
 using LinearSolve.LinearAlgebra, LinearSolve.SciMLBase
 
 # LU Factorization
@@ -26,7 +25,7 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::AMDGPUOffloadLUFa
 end
 
 function LinearSolve.init_cacheval(alg::AMDGPUOffloadLUFactorization, A, b, u, Pl, Pr,
-        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+        maxiters::Int, abstol, reltol, verbose::Bool,
         assumptions::OperatorAssumptions)
     AMDGPU.rocSOLVER.getrf!(AMDGPU.ROCArray(A))
 end
@@ -58,7 +57,7 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::AMDGPUOffloadQRFa
 end
 
 function LinearSolve.init_cacheval(alg::AMDGPUOffloadQRFactorization, A, b, u, Pl, Pr,
-        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+        maxiters::Int, abstol, reltol, verbose::Bool,
         assumptions::OperatorAssumptions)
     A_gpu = AMDGPU.ROCArray(A)
     tau = AMDGPU.ROCVector{eltype(A_gpu)}(undef, min(size(A_gpu)...))

ext/LinearSolveBLISExt.jl

@@ -9,7 +9,7 @@ using LinearSolve
 using LinearAlgebra: BlasInt, LU
 using LinearAlgebra.LAPACK: require_one_based_indexing, chkfinite, chkstride1, 
                             @blasfunc, chkargsok
-using LinearSolve: ArrayInterface, BLISLUFactorization, @get_cacheval, LinearCache, SciMLBase, LinearVerbosity
+using LinearSolve: ArrayInterface, BLISLUFactorization, @get_cacheval, LinearCache, SciMLBase
 using SciMLBase: ReturnCode
 
 const global libblis = blis_jll.blis
@@ -204,13 +204,13 @@ const PREALLOCATED_BLIS_LU = begin
 end
 
 function LinearSolve.init_cacheval(alg::BLISLUFactorization, A, b, u, Pl, Pr,
-    maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+    maxiters::Int, abstol, reltol, verbose::Bool,
     assumptions::OperatorAssumptions)
     PREALLOCATED_BLIS_LU
 end
 
 function LinearSolve.init_cacheval(alg::BLISLUFactorization, A::AbstractMatrix{<:Union{Float32,ComplexF32,ComplexF64}}, b, u, Pl, Pr,
-    maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+    maxiters::Int, abstol, reltol, verbose::Bool,
     assumptions::OperatorAssumptions)
     A = rand(eltype(A), 0, 0)
     ArrayInterface.lu_instance(A), Ref{BlasInt}()

ext/LinearSolveBandedMatricesExt.jl

@@ -3,7 +3,7 @@ module LinearSolveBandedMatricesExt
 using BandedMatrices, LinearAlgebra, LinearSolve
 import LinearSolve: defaultalg,
                     do_factorization, init_cacheval, DefaultLinearSolver,
-                    DefaultAlgorithmChoice, LinearVerbosity
+                    DefaultAlgorithmChoice
 
 # Defaults for BandedMatrices
 function defaultalg(A::BandedMatrix, b, oa::OperatorAssumptions{Bool})
@@ -41,14 +41,14 @@ for alg in (:SVDFactorization, :MKLLUFactorization, :DiagonalFactorization,
     :AppleAccelerateLUFactorization, :CholeskyFactorization)
     @eval begin
         function init_cacheval(::$(alg), ::BandedMatrix, b, u, Pl, Pr, maxiters::Int,
-                abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+                abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
             return nothing
         end
     end
 end
 
 function init_cacheval(::LUFactorization, A::BandedMatrix{T}, b, u, Pl, Pr, maxiters::Int,
-        abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions) where {T}
+        abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions) where {T}
     (T <: BigFloat) && return qr(similar(A, 0, 0))
     return lu(similar(A, 0, 0))
 end
@@ -61,7 +61,7 @@ for alg in (:SVDFactorization, :MKLLUFactorization, :DiagonalFactorization,
     :AppleAccelerateLUFactorization, :QRFactorization, :LUFactorization)
     @eval begin
         function init_cacheval(::$(alg), ::Symmetric{<:Number, <:BandedMatrix}, b, u, Pl,
-                Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+                Pr, maxiters::Int, abstol, reltol, verbose::Bool,
                 assumptions::OperatorAssumptions)
             return nothing
         end

ext/LinearSolveCUDAExt.jl

@@ -1,17 +1,14 @@
 module LinearSolveCUDAExt
 
 using CUDA
-using CUDA: CuVector, CuMatrix
 using LinearSolve: LinearSolve, is_cusparse, defaultalg, cudss_loaded, DefaultLinearSolver,
                    DefaultAlgorithmChoice, ALREADY_WARNED_CUDSS, LinearCache,
                    needs_concrete_A,
                    error_no_cudss_lu, init_cacheval, OperatorAssumptions,
                    CudaOffloadFactorization, CudaOffloadLUFactorization, CudaOffloadQRFactorization,
                    CUDAOffload32MixedLUFactorization,
-                   SparspakFactorization, KLUFactorization, UMFPACKFactorization,
-                   LinearVerbosity
+                   SparspakFactorization, KLUFactorization, UMFPACKFactorization
 using LinearSolve.LinearAlgebra, LinearSolve.SciMLBase, LinearSolve.ArrayInterface
-using LinearAlgebra: LU
 using SciMLBase: AbstractSciMLOperator
 
 function LinearSolve.is_cusparse(A::Union{
@@ -54,7 +51,7 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::CudaOffloadLUFact
 end
 
 function LinearSolve.init_cacheval(alg::CudaOffloadLUFactorization, A::AbstractArray, b, u, Pl, Pr,
-        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+        maxiters::Int, abstol, reltol, verbose::Bool,
         assumptions::OperatorAssumptions)
     T = eltype(A)
     noUnitT = typeof(zero(T))
@@ -77,7 +74,7 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::CudaOffloadQRFact
 end
 
 function LinearSolve.init_cacheval(alg::CudaOffloadQRFactorization, A, b, u, Pl, Pr,
-        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+        maxiters::Int, abstol, reltol, verbose::Bool,
         assumptions::OperatorAssumptions)
     qr(CUDA.CuArray(A))
 end
@@ -96,26 +93,26 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::CudaOffloadFactor
 end
 
 function LinearSolve.init_cacheval(alg::CudaOffloadFactorization, A::AbstractArray, b, u, Pl, Pr,
-        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+        maxiters::Int, abstol, reltol, verbose::Bool,
         assumptions::OperatorAssumptions)
     qr(CUDA.CuArray(A))
 end
 
 function LinearSolve.init_cacheval(
         ::SparspakFactorization, A::CUDA.CUSPARSE.CuSparseMatrixCSR, b, u,
-        Pl, Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+        Pl, Pr, maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
     nothing
 end
 
 function LinearSolve.init_cacheval(
         ::KLUFactorization, A::CUDA.CUSPARSE.CuSparseMatrixCSR, b, u,
-        Pl, Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+        Pl, Pr, maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
     nothing
 end
 
 function LinearSolve.init_cacheval(
         ::UMFPACKFactorization, A::CUDA.CUSPARSE.CuSparseMatrixCSR, b, u,
-        Pl, Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+        Pl, Pr, maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
     nothing
 end
 
@@ -143,7 +140,7 @@ function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::CUDAOffload32Mixe
 end
 
 function LinearSolve.init_cacheval(alg::CUDAOffload32MixedLUFactorization, A, b, u, Pl, Pr,
-        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
+        maxiters::Int, abstol, reltol, verbose::Bool,
         assumptions::OperatorAssumptions)
     # Pre-allocate with Float32 arrays
     A_f32 = Float32.(A)

ext/LinearSolveCUSOLVERRFExt.jl

@@ -1,6 +1,6 @@
 module LinearSolveCUSOLVERRFExt
 
-using LinearSolve: LinearSolve, @get_cacheval, pattern_changed, OperatorAssumptions, LinearVerbosity
+using LinearSolve: LinearSolve, @get_cacheval, pattern_changed, OperatorAssumptions
 using CUSOLVERRF: CUSOLVERRF, RFLU, CUDA
 using SparseArrays: SparseArrays, SparseMatrixCSC, nnz
 using CUSOLVERRF.CUDA.CUSPARSE: CuSparseMatrixCSR
@@ -10,15 +10,15 @@ using SciMLBase: SciMLBase, LinearProblem, ReturnCode
 function LinearSolve.init_cacheval(alg::LinearSolve.CUSOLVERRFFactorization,
         A, b, u, Pl, Pr,
         maxiters::Int, abstol, reltol,
-        verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+        verbose::Bool, assumptions::OperatorAssumptions)
     nothing
 end
 
 function LinearSolve.init_cacheval(alg::LinearSolve.CUSOLVERRFFactorization,
         A::Union{CuSparseMatrixCSR{Float64, Int32}, SparseMatrixCSC{Float64, <:Integer}}, 
         b, u, Pl, Pr,
         maxiters::Int, abstol, reltol,
-        verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+        verbose::Bool, assumptions::OperatorAssumptions)
     # Create initial factorization with appropriate options
     nrhs = b isa AbstractMatrix ? size(b, 2) : 1
     symbolic = alg.symbolic

ext/LinearSolveCliqueTreesExt.jl

@@ -2,7 +2,6 @@ module LinearSolveCliqueTreesExt
 
 using CliqueTrees: symbolic, cholinit, lininit, cholesky!, linsolve!
 using LinearSolve
-using LinearSolve: LinearVerbosity
 using SparseArrays
 
 function _symbolic(A::AbstractMatrix, alg::CliqueTreesFactorization)
@@ -23,7 +22,7 @@ end
 
 function LinearSolve.init_cacheval(
     alg::CliqueTreesFactorization, A::AbstractMatrix, b, u, Pl, Pr, maxiters::Int, abstol,
-    reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+    reltol, verbose::Bool, assumptions::OperatorAssumptions)
     symbfact = _symbolic(A, alg)
     cholfact, cholwork = cholinit(A, symbfact)
     linwork = lininit(1, cholfact)

ext/LinearSolveFastAlmostBandedMatricesExt.jl

@@ -3,7 +3,7 @@ module LinearSolveFastAlmostBandedMatricesExt
 using FastAlmostBandedMatrices, LinearAlgebra, LinearSolve
 import LinearSolve: defaultalg,
                     do_factorization, init_cacheval, DefaultLinearSolver,
-                    DefaultAlgorithmChoice, LinearVerbosity
+                    DefaultAlgorithmChoice
 
 function defaultalg(A::AlmostBandedMatrix, b, oa::OperatorAssumptions{Bool})
     if oa.issq
@@ -21,7 +21,7 @@ for alg in (:SVDFactorization, :MKLLUFactorization, :DiagonalFactorization,
     :AppleAccelerateLUFactorization, :CholeskyFactorization, :LUFactorization)
     @eval begin
         function init_cacheval(::$(alg), ::AlmostBandedMatrix, b, u, Pl, Pr, maxiters::Int,
-                abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
+                abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
             return nothing
         end
     end