Change rrule verbosity behaviour

Project.toml

@@ -22,12 +22,13 @@ ChainRulesCore = "1"
 ChainRulesTestUtils = "1"
 FiniteDifferences = "0.12"
 LinearAlgebra = "1"
+Logging = "1"
 PackageExtensionCompat = "1"
 Printf = "1"
 Random = "1"
 Test = "1"
 TestExtras = "0.2,0.3"
-VectorInterface = "0.4,0.5"
+VectorInterface = "0.5"
 Zygote = "0.6"
 julia = "1.6"
 
@@ -36,9 +37,10 @@ Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
+Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 TestExtras = "5ed8adda-3752-4e41-b88a-e8b09835ee3a"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["Test", "Aqua", "TestExtras", "ChainRulesTestUtils", "ChainRulesCore", "FiniteDifferences", "Zygote"]
+test = ["Test", "Aqua", "Logging", "TestExtras", "ChainRulesTestUtils", "ChainRulesCore", "FiniteDifferences", "Zygote"]

ext/KrylovKitChainRulesCoreExt/KrylovKitChainRulesCoreExt.jl

@@ -6,6 +6,7 @@ using LinearAlgebra
 using VectorInterface
 
 using KrylovKit: apply_normal, apply_adjoint
+using KrylovKit: WARN_LEVEL, STARTSTOP_LEVEL, EACHITERATION_LEVEL
 
 include("utilities.jl")
 include("linsolve.jl")

ext/KrylovKitChainRulesCoreExt/eigsolve.jl

@@ -135,7 +135,7 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
             b = (zerovector(v), convert(T, Δλ))
         else
             vdΔv = inner(v, Δv)
-            if alg_rrule.verbosity >= 0
+            if alg_rrule.verbosity >= WARN_LEVEL
                 gauge = abs(imag(vdΔv))
                 gauge > alg_primal.tol &&
                     @warn "`eigsolve` cotangent for eigenvector $i is sensitive to gauge choice: (|gauge| = $gauge)"
@@ -152,9 +152,11 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
                 return (y1, y2)
             end
         end
-        if info.converged >= i && reverse_info.converged == 0 && alg_rrule.verbosity >= 0
+        if info.converged >= i && reverse_info.converged == 0 &&
+           alg_primal.verbosity >= WARN_LEVEL
             @warn "`eigsolve` cotangent linear problem ($i) did not converge, whereas the primal eigenvalue problem did: normres = $(reverse_info.normres)"
-        elseif abs(w[2]) > alg_rrule.tol && alg_rrule.verbosity >= 0
+        elseif abs(w[2]) > (alg_rrule.tol * norm(w[1])) &&
+               alg_primal.verbosity >= WARN_LEVEL
             @warn "`eigsolve` cotangent linear problem ($i) returns unexpected result: error = $(w[2])"
         end
         ws[i] = w[1]
@@ -185,7 +187,7 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
 
     # components along subspace spanned by current eigenvectors
     tol = alg_primal.tol
-    if alg_rrule.verbosity >= 0
+    if alg_rrule.verbosity >= WARN_LEVEL
         mask = abs.(transpose(vals) .- vals) .< tol
         gaugepart = VdΔV[mask] - Diagonal(real(diag(VdΔV)))[mask]
         Δgauge = norm(gaugepart, Inf)
@@ -263,7 +265,8 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
             return (w′, conj.(vals) .* x)
         end
     end
-    if info.converged >= n && reverse_info.converged < n && alg_rrule.verbosity >= 0
+    if info.converged >= n && reverse_info.converged < n &&
+       alg_primal.verbosity >= WARN_LEVEL
         @warn "`eigsolve` cotangent problem did not converge, whereas the primal eigenvalue problem did"
     end
     # cleanup and construct final result by renormalising the eigenvectors and explicitly
@@ -276,7 +279,7 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
         w, x = Ws[ic]
         factor = 1 / x[i]
         x[i] = zero(x[i])
-        if alg_rrule.verbosity >= 0
+        if alg_primal.verbosity >= WARN_LEVEL
             error = max(norm(x, Inf), abs(rvals[ic] - conj(vals[i])))
             error > 10 * tol &&
                 @warn "`eigsolve` cotangent linear problem ($i) returns unexpected result: error = $error"
@@ -308,7 +311,7 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
     # components along subspace spanned by current eigenvectors
     tol = alg_primal.tol
     aVdΔV = rmul!(VdΔV - VdΔV', 1 / 2)
-    if alg_rrule.verbosity >= 0
+    if alg_rrule.verbosity >= WARN_LEVEL
         mask = abs.(transpose(vals) .- vals) .< tol
         gaugepart = view(aVdΔV, mask)
         gauge = norm(gaugepart, Inf)
@@ -366,7 +369,8 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
             return (w′, vals .* x)
         end
     end
-    if info.converged >= n && reverse_info.converged < n && alg_rrule.verbosity >= 0
+    if info.converged >= n && reverse_info.converged < n &&
+       alg_primal.verbosity >= WARN_LEVEL
         @warn "`eigsolve` cotangent problem did not converge, whereas the primal eigenvalue problem did"
     end
 
@@ -380,7 +384,7 @@ function compute_eigsolve_pullback_data(Δvals, Δvecs, vals, vecs, info, which,
         factor = 1 / x[ic]
         x[ic] = zero(x[ic])
         error = max(norm(x, Inf), abs(rvals[i] - conj(vals[ic])))
-        if error > 5 * tol && alg_rrule.verbosity >= 0
+        if error > 10 * tol && alg_primal.verbosity >= WARN_LEVEL
             @warn "`eigsolve` cotangent linear problem ($ic) returns unexpected result: error = $error"
         end
         ws[ic] = VectorInterface.add!!(zs[ic], Q(w), -factor)

ext/KrylovKitChainRulesCoreExt/linsolve.jl

@@ -34,7 +34,8 @@ function make_linsolve_pullback(fᴴ, b, a₀, a₁, alg_rrule, construct∂f, x
                                                                                      a₁)))
         ∂b, reverse_info = linsolve(fᴴ, x̄, x̄₀, alg_rrule, conj(a₀),
                                     conj(a₁))
-        if info.converged > 0 && reverse_info.converged == 0 && alg_rrule.verbosity >= 0
+        if info.converged > 0 && reverse_info.converged == 0 &&
+           alg_primal.verbosity >= WARN_LEVEL
             @warn "`linsolve` cotangent problem did not converge, whereas the primal linear problem did: normres = $(reverse_info.normres)"
         end
         x∂b = inner(x, ∂b)

ext/KrylovKitChainRulesCoreExt/svdsolve.jl

@@ -112,7 +112,7 @@ function compute_svdsolve_pullback_data(Δvals, Δlvecs, Δrvecs, vals, lvecs, r
         udΔu = inner(u, Δu)
         vdΔv = inner(v, Δv)
         if (udΔu isa Complex) || (vdΔv isa Complex)
-            if alg_rrule.verbosity >= 0
+            if alg_rrule.verbosity >= WARN_LEVEL
                 gauge = abs(imag(udΔu + vdΔv))
                 gauge > alg_primal.tol &&
                     @warn "`svdsolve` cotangents for singular vectors $i are sensitive to gauge choice: (|gauge| = $gauge)"
@@ -131,7 +131,8 @@ function compute_svdsolve_pullback_data(Δvals, Δlvecs, Δrvecs, vals, lvecs, r
                 return (x′, y′)
             end
         end
-        if info.converged >= i && reverse_info.converged == 0 && alg_rrule.verbosity >= 0
+        if info.converged >= i && reverse_info.converged == 0 &&
+           alg_primal.verbosity >= WARN_LEVEL
             @warn "`svdsolve` cotangent linear problem ($i) did not converge, whereas the primal eigenvalue problem did: normres = $(reverse_info.normres)"
         end
         x = VectorInterface.add!!(x, u, Δs / 2)
@@ -162,7 +163,7 @@ function compute_svdsolve_pullback_data(Δvals, Δlvecs, Δrvecs, vals, lvecs, r
     aVdΔV = rmul!(VdΔV - VdΔV', 1 / 2)
 
     tol = alg_primal.tol
-    if alg_rrule.verbosity >= 0
+    if alg_rrule.verbosity >= WARN_LEVEL
         mask = abs.(vals' .- vals) .< tol
         gaugepart = view(aUdΔU, mask) + view(aVdΔV, mask)
         gauge = norm(gaugepart, Inf)
@@ -227,7 +228,8 @@ function compute_svdsolve_pullback_data(Δvals, Δlvecs, Δrvecs, vals, lvecs, r
             return (x′, y′, vals .* z)
         end
     end
-    if info.converged >= n && reverse_info.converged < n && alg_rrule.verbosity >= 0
+    if info.converged >= n && reverse_info.converged < n &&
+       alg_primal.verbosity >= WARN_LEVEL
         @warn "`svdsolve` cotangent problem did not converge, whereas the primal singular value problem did"
     end
 
@@ -236,13 +238,13 @@ function compute_svdsolve_pullback_data(Δvals, Δlvecs, Δrvecs, vals, lvecs, r
     for i in 1:n
         x, y, z = Ws[i]
         _, ic = findmax(abs, z)
-        if ic != i
+        if ic != i && alg_primal.verbosity >= WARN_LEVEL
             @warn "`svdsolve` cotangent linear problem ($ic) returns unexpected result"
         end
         factor = 1 / z[ic]
         z[ic] = zero(z[ic])
         error = max(norm(z, Inf), abs(rvals[i] - vals[ic]))
-        if error > 5 * tol && alg_rrule.verbosity >= 0
+        if error > 10 * tol && alg_primal.verbosity >= WARN_LEVEL
             @warn "`svdsolve` cotangent linear problem ($ic) returns unexpected result: error = $error vs tol = $tol"
         end
         xs[ic] = VectorInterface.add!!(xs[ic], x, -factor)

src/KrylovKit.jl

@@ -102,9 +102,6 @@
 end
 Base.length(r::SplitRange) = r.outerlength
 
-# Algorithm types
-include("algorithms.jl")
-
 # Structures to store a list of basis vectors
 """
     abstract type Basis{T} end
@@ -122,14 +119,6 @@
 """
 abstract type Basis{T} end
 
-include("orthonormal.jl")
-
-# Dense linear algebra structures and functions used in the algorithms below
-include("dense/givens.jl")
-include("dense/linalg.jl")
-include("dense/packedhessenberg.jl")
-include("dense/reflector.jl")
-
 # Simple coordinate basis vector, i.e. a vector of all zeros and a single one on position `k`:
 """
     SimpleBasisVector(m, k)
@@ -164,6 +153,23 @@
 # apply operators
 include("apply.jl")
 
+# Verbosity levels
+const WARN_LEVEL = 1
+const STARTSTOP_LEVEL = 2
+const EACHITERATION_LEVEL = 3
+
+# Algorithm types
+include("algorithms.jl")
+
+# OrthonormalBasis, orthogonalization and orthonormalization methods
+include("orthonormal.jl")
+
+# Dense linear algebra structures and functions used in the algorithms below
+include("dense/givens.jl")
+include("dense/linalg.jl")
+include("dense/packedhessenberg.jl")
+include("dense/reflector.jl")
+
 # Krylov and related factorizations and their iterators
 include("factorizations/krylov.jl")
 include("factorizations/lanczos.jl")
@@ -217,7 +223,19 @@
             " iterations and ",
             info.numops,
             " applications of the linear map;")
-    return println(io, "norms of residuals are given by $((info.normres...,)).")
+    return print(io, "norms of residuals are given by ", normres2string(info.normres), ".")
+end
+
+# Convert residual norms into strings for info and warning printing
+normres2string(β::Number) = @sprintf("%.2e", β)
+function normres2string(β)
+    s = "("
+    for i in 1:length(β)
+        s *= normres2string(β[i])
+        i < length(β) && (s *= ", ")
+    end
+    s *= ")"
+    return s
 end
 
 # vectors with modified inner product