Fixed Verbosity System

Project.toml

@@ -23,6 +23,7 @@ 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"
@@ -124,6 +125,7 @@ Reexport = "1.2.2"
 SafeTestsets = "0.1"
 SciMLBase = "2.70"
 SciMLOperators = "1.7.1"
+SciMLLogging = "1.1.0"
 Setfield = "1.1.1"
 SparseArrays = "1.10"
 Sparspak = "0.3.9"

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::Bool, assump::LinearSolve.OperatorAssumptions)
+        verbose::LinearVerbosity, assump::LinearSolve.OperatorAssumptions)
     lu!(convert(AbstractMatrix, A))
 end
 

docs/src/basics/common_solver_opts.md

@@ -26,3 +26,92 @@ 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.
+- SciMLLogging.None() - Suppress all messages
+- SciMLLogging.Info() - Show message as log message at info level
+- SciMLLogging.Warn() - Show warnings (default for most settings)
+- SciMLLogging.Error() - Throw errors instead of warnings
+- SciMLLogging.Level(n) - Show messages with a log level setting of n
+
+#### Group Settings
+These settings are meant for controlling a group of settings. 
+- SciMLLogging.Default() - Use the default settings
+- SciMLLogging.All() - Show all possible messages
+
+### Basic Usage 
+
+#### Global Verbosity Control
+
+```julia 
+using LinearSolve
+
+# Suppress all messages
+verbose = LinearVerbosity(SciMLLogging.None())
+prob = LinearProblem(A, b)
+sol = solve(prob; verbose=verbose)
+
+# Show all messages
+verbose = LinearVerbosity(SciMLLogging.All())
+sol = solve(prob; verbose=verbose)
+
+# Use default settings
+verbose = LinearVerbosity(SciMLLogging.Default())
+sol = solve(prob; verbose=verbose)
+```
+
+#### Group Level Control 
+
+```julia 
+# Customize by category
+verbose = LinearVerbosity(
+    error_control = SciMLLogging.Warn(),   # Show warnings for error control related issues
+    performance = SciMLLogging.None(),     # Suppress performance messages
+    numerical = SciMLLogging.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 = SciMLLogging.Info(),                     # Show info when LU fallback is used
+    KrylovJL_verbosity = SciMLLogging.Warn(),                      # Show warnings from KrylovJL
+    no_right_preconditioning = SciMLLogging.None(),                # Suppress right preconditioning messages
+    KrylovKit_verbosity = SciMLLogging.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

@@ -2,7 +2,7 @@ module LinearSolveAMDGPUExt
 
 using AMDGPU
 using LinearSolve: LinearSolve, LinearCache, AMDGPUOffloadLUFactorization,
-                   AMDGPUOffloadQRFactorization, init_cacheval, OperatorAssumptions
+                   AMDGPUOffloadQRFactorization, init_cacheval, OperatorAssumptions, LinearVerbosity
 using LinearSolve.LinearAlgebra, LinearSolve.SciMLBase
 
 # LU Factorization
@@ -25,7 +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::Bool,
+        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
         assumptions::OperatorAssumptions)
     AMDGPU.rocSOLVER.getrf!(AMDGPU.ROCArray(A))
 end
@@ -57,7 +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::Bool,
+        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
         assumptions::OperatorAssumptions)
     A_gpu = AMDGPU.ROCArray(A)
     tau = AMDGPU.ROCVector{eltype(A_gpu)}(undef, min(size(A_gpu)...))

ext/LinearSolveBLISExt.jl

@@ -9,7 +9,8 @@ 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
+using LinearSolve: ArrayInterface, BLISLUFactorization, @get_cacheval, LinearCache, SciMLBase, LinearVerbosity, get_blas_operation_info, blas_info_msg
+using SciMLLogging: SciMLLogging, @SciMLMessage
 using SciMLBase: ReturnCode
 
 const global libblis = blis_jll.blis
@@ -204,13 +205,13 @@ const PREALLOCATED_BLIS_LU = begin
 end
 
 function LinearSolve.init_cacheval(alg::BLISLUFactorization, A::Matrix{Float64}, b, u, Pl, Pr,
-    maxiters::Int, abstol, reltol, verbose::Bool,
+    maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
     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::Bool,
+    maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
     assumptions::OperatorAssumptions)
     A = rand(eltype(A), 0, 0)
     ArrayInterface.lu_instance(A), Ref{BlasInt}()
@@ -220,12 +221,45 @@ function SciMLBase.solve!(cache::LinearCache, alg::BLISLUFactorization;
     kwargs...)
     A = cache.A
     A = convert(AbstractMatrix, A)
+    verbose = cache.verbose
     if cache.isfresh
         cacheval = @get_cacheval(cache, :BLISLUFactorization)
         res = getrf!(A; ipiv = cacheval[1].ipiv, info = cacheval[2])
         fact = LU(res[1:3]...), res[4]
         cache.cacheval = fact
 
+        info_value = res[3]
+
+        if info_value != 0
+            if !isa(verbose.blas_info, SciMLLogging.Silent) || !isa(verbose.blas_errors, SciMLLogging.Silent) ||
+                !isa(verbose.blas_invalid_args, SciMLLogging.Silent) 
+                op_info = get_blas_operation_info(:dgetrf, A, cache.b, condition = !isa(verbose.condition_number, SciMLLogging.Silent))
+                @SciMLMessage(cache.verbose, :condition_number) do 
+                    if op_info[:condition_number] === nothing
+                        return "Matrix condition number calculation failed."
+                    else 
+                        return "Matrix condition number: $(round(op_info[:condition_number], sigdigits=4)) for $(size(A, 1))×$(size(A, 2)) matrix in dgetrf"
+                    end
+                end
+                verb_option, message = blas_info_msg(
+                    :dgetrf, info_value; extra_context = op_info)
+                @SciMLMessage(message, verbose, verb_option)
+            end
+        else
+            @SciMLMessage(cache.verbose, :blas_success) do 
+                op_info = get_blas_operation_info(:dgetrf, A, cache.b,
+                    condition = !isa(verbose.condition_number, SciMLLogging.Silent))
+                @SciMLMessage(cache.verbose, :condition_number) do
+                    if op_info[:condition_number] === nothing
+                        return "Matrix condition number calculation failed."
+                    else
+                        return "Matrix condition number: $(round(op_info[:condition_number], sigdigits=4)) for $(size(A, 1))×$(size(A, 2)) matrix in dgetrf"
+                    end
+                end
+                return "BLAS LU factorization (dgetrf) completed successfully for $(op_info[:matrix_size]) matrix"
+            end 
+        end
+
         if !LinearAlgebra.issuccess(fact[1])
             return SciMLBase.build_linear_solution(
                 alg, cache.u, nothing, cache; retcode = ReturnCode.Failure)

ext/LinearSolveBandedMatricesExt.jl

@@ -3,7 +3,7 @@ module LinearSolveBandedMatricesExt
 using BandedMatrices, LinearAlgebra, LinearSolve
 import LinearSolve: defaultalg,
                     do_factorization, init_cacheval, DefaultLinearSolver,
-                    DefaultAlgorithmChoice
+                    DefaultAlgorithmChoice, LinearVerbosity
 
 # 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::Bool, assumptions::OperatorAssumptions)
+                abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
             return nothing
         end
     end
 end
 
 function init_cacheval(::LUFactorization, A::BandedMatrix{T}, b, u, Pl, Pr, maxiters::Int,
-        abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions) where {T}
+        abstol, reltol, verbose::LinearVerbosity, 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::Bool,
+                Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
                 assumptions::OperatorAssumptions)
             return nothing
         end

ext/LinearSolveCUDAExt.jl

@@ -7,7 +7,7 @@ using LinearSolve: LinearSolve, is_cusparse, defaultalg, cudss_loaded, DefaultLi
                    error_no_cudss_lu, init_cacheval, OperatorAssumptions,
                    CudaOffloadFactorization, CudaOffloadLUFactorization, CudaOffloadQRFactorization,
                    CUDAOffload32MixedLUFactorization,
-                   SparspakFactorization, KLUFactorization, UMFPACKFactorization
+                   SparspakFactorization, KLUFactorization, UMFPACKFactorization, LinearVerbosity
 using LinearSolve.LinearAlgebra, LinearSolve.SciMLBase, LinearSolve.ArrayInterface
 using SciMLBase: AbstractSciMLOperator
 
@@ -51,7 +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::Bool,
+        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
         assumptions::OperatorAssumptions)
     # Check if CUDA is functional before creating CUDA arrays
     if !CUDA.functional()
@@ -79,7 +79,7 @@ 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::Bool,
+        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
         assumptions::OperatorAssumptions)
     # Check if CUDA is functional before creating CUDA arrays
     if !CUDA.functional()
@@ -103,26 +103,26 @@ 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::Bool,
+        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
         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::Bool, assumptions::OperatorAssumptions)
+        Pl, Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
     nothing
 end
 
 function LinearSolve.init_cacheval(
         ::KLUFactorization, A::CUDA.CUSPARSE.CuSparseMatrixCSR, b, u,
-        Pl, Pr, maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
+        Pl, Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
     nothing
 end
 
 function LinearSolve.init_cacheval(
         ::UMFPACKFactorization, A::CUDA.CUSPARSE.CuSparseMatrixCSR, b, u,
-        Pl, Pr, maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
+        Pl, Pr, maxiters::Int, abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
     nothing
 end
 
@@ -156,7 +156,7 @@ 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::Bool,
+        maxiters::Int, abstol, reltol, verbose::LinearVerbosity,
         assumptions::OperatorAssumptions)
     # Pre-allocate with Float32 arrays
     m, n = size(A)

ext/LinearSolveCUSOLVERRFExt.jl

@@ -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::Bool, assumptions::OperatorAssumptions)
+        verbose::LinearVerbosity, 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::Bool, assumptions::OperatorAssumptions)
+        verbose::LinearVerbosity, assumptions::OperatorAssumptions)
     # Create initial factorization with appropriate options
     nrhs = b isa AbstractMatrix ? size(b, 2) : 1
     symbolic = alg.symbolic

ext/LinearSolveCliqueTreesExt.jl

@@ -22,7 +22,7 @@ end
 
 function LinearSolve.init_cacheval(
     alg::CliqueTreesFactorization, A::AbstractMatrix, b, u, Pl, Pr, maxiters::Int, abstol,
-    reltol, verbose::Bool, assumptions::OperatorAssumptions)
+    reltol, verbose::LinearVerbosity, 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
+                    DefaultAlgorithmChoice, LinearVerbosity
 
 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::Bool, assumptions::OperatorAssumptions)
+                abstol, reltol, verbose::LinearVerbosity, assumptions::OperatorAssumptions)
             return nothing
         end
     end