Revert "Revert LDLFactorizations package extension (#2972)"

This reverts commit def69e1.

Author: odow

Project.toml

@@ -19,9 +19,11 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [weakdeps]
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b"
 
 [extensions]
 MathOptInterfaceBenchmarkToolsExt = "BenchmarkTools"
+MathOptInterfaceLDLFactorizationsExt = "LDLFactorizations"
 
 [compat]
 BenchmarkTools = "1"
@@ -30,6 +32,7 @@ CodecZlib = "0.6, 0.7"
 ForwardDiff = "1"
 JSON = "0.21, 1"
 JSONSchema = "1"
+LDLFactorizations = "0.10"
 LinearAlgebra = "1"
 MutableArithmetics = "1"
 NaNMath = "0.3, 1"
@@ -44,8 +47,9 @@ julia = "1.10"
 
 [extras]
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b"
 JSONSchema = "7d188eb4-7ad8-530c-ae41-71a32a6d4692"
 ParallelTestRunner = "d3525ed8-44d0-4b2c-a655-542cee43accc"
 
 [targets]
-test = ["BenchmarkTools", "JSONSchema", "ParallelTestRunner"]
+test = ["BenchmarkTools", "LDLFactorizations", "JSONSchema", "ParallelTestRunner"]

ext/MathOptInterfaceLDLFactorizationsExt.jl

@@ -0,0 +1,50 @@
+# Copyright (c) 2017: Miles Lubin and contributors
+# Copyright (c) 2017: Google Inc.
+#
+# Use of this source code is governed by an MIT-style license that can be found
+# in the LICENSE.md file or at https://opensource.org/licenses/MIT.
+
+module MathOptInterfaceLDLFactorizationsExt
+
+import LDLFactorizations
+import LinearAlgebra
+import MathOptInterface as MOI
+import SparseArrays
+
+# The type signature of this function is not important, so long as it is more
+# specific than the (untyped) generic fallback with the error pointing to
+# LDLFactorizations.jl
+function MOI.Bridges.Constraint.compute_sparse_sqrt_fallback(
+    Q::AbstractMatrix,
+    ::F,
+    ::S,
+) where {F<:MOI.ScalarQuadraticFunction,S<:MOI.AbstractSet}
+    n = LinearAlgebra.checksquare(Q)
+    factor = LDLFactorizations.ldl(Q)
+    # Ideally we should use `LDLFactorizations.factorized(factor)` here, but it
+    # has some false negatives. Instead we check that the factorization appeared
+    # to work. This is a heuristic. There might be other cases where check is
+    # insufficient.
+    if minimum(factor.D) < 0 || any(issubnormal, factor.D)
+        msg = """
+        Unable to transform a quadratic constraint into a SecondOrderCone
+        constraint because the quadratic constraint is not convex.
+        """
+        throw(MOI.UnsupportedConstraint{F,S}(msg))
+    end
+    # We have Q = P' * L * D * L' * P. We want to find Q = U' * U, so
+    # U = sqrt(D) * L' * P. First, compute L'. Note I and J are reversed:
+    J, I, V = SparseArrays.findnz(factor.L)
+    # Except L doesn't include the identity along the diagonal. Add it back.
+    append!(J, 1:n)
+    append!(I, 1:n)
+    append!(V, ones(n))
+    # Now scale by sqrt(D)
+    for (k, i) in enumerate(I)
+        V[k] *= sqrt(factor.D[i, i])
+    end
+    # Finally, permute the columns of L'. The rows stay in the same order.
+    return I, factor.P[J], V
+end
+
+end  # module

src/Bridges/Constraint/bridges/QuadtoSOCBridge.jl

@@ -60,6 +60,25 @@ end
 const QuadtoSOC{T,OT<:MOI.ModelLike} =
     SingleBridgeOptimizer{QuadtoSOCBridge{T},OT}
 
+function compute_sparse_sqrt_fallback(Q, ::F, ::S) where {F,S}
+    msg = """
+    Unable to transform a quadratic constraint into a SecondOrderCone
+    constraint because the quadratic constraint is not strongly convex and
+    our Cholesky decomposition failed.
+
+    If the constraint is convex but not strongly convex, you can work-around
+    this issue by manually installing and loading `LDLFactorizations.jl`:
+    ```julia
+    import Pkg; Pkg.add("LDLFactorizations")
+    using LDLFactorizations
+    ```
+
+    LDLFactorizations.jl is not included by default because it is licensed
+    under the LGPL.
+    """
+    return throw(MOI.AddConstraintNotAllowed{F,S}(msg))
+end
+
 function compute_sparse_sqrt(Q, func, set)
     # There's a big try-catch here because Cholesky can fail even if
     # `check = false`. As one example, it currently (v1.12) fails with
@@ -69,20 +88,22 @@ function compute_sparse_sqrt(Q, func, set)
     # The try-catch isn't a performance concern because the alternative is not
     # being able to reformulate the problem.
     try
-        factor = LinearAlgebra.cholesky(Q)
+        factor = LinearAlgebra.cholesky(Q; check = false)
+        if !LinearAlgebra.issuccess(factor)
+            return compute_sparse_sqrt_fallback(Q, func, set)
+        end
         L, p = SparseArrays.sparse(factor.L), factor.p
         # We have Q = P' * L * L' * P. We want to find Q = U' * U, so U = L' * P
         # First, compute L'. Note I and J are reversed
         J, I, V = SparseArrays.findnz(L)
         # Then, we want to permute the columns of L'. The rows stay in the same
         # order.
         return I, p[J], V
-    catch
-        msg = """
-        Unable to transform a quadratic constraint into a SecondOrderCone
-        constraint because the quadratic constraint is not strongly convex and
-        our Cholesky decomposition failed.
-        """
+    catch err
+        if err isa MOI.AddConstraintNotAllowed
+            rethrow(err)
+        end
+        msg = "There was an error computing a matrix square root"
         throw(MOI.UnsupportedConstraint{typeof(func),typeof(set)}(msg))
     end
 end

test/Bridges/Constraint/test_QuadtoSOCBridge.jl

@@ -10,6 +10,7 @@ import LinearAlgebra
 import SparseArrays
 using Test
 
+import LDLFactorizations
 import MathOptInterface as MOI
 
 function runtests()
@@ -344,16 +345,13 @@ function test_semidefinite_cholesky_fail()
     model = MOI.Bridges.Constraint.QuadtoSOC{Float64}(inner)
     x = MOI.add_variables(model, 2)
     f = 0.5 * x[1] * x[1] + 1.0 * x[1] * x[2] + 0.5 * x[2] * x[2]
-    @test_throws(
-        MOI.UnsupportedConstraint,
-        MOI.add_constraint(model, f, MOI.LessThan(1.0)),
-    )
-    # F, S = MOI.VectorAffineFunction{Float64}, MOI.RotatedSecondOrderCone
-    # ci = only(MOI.get(inner, MOI.ListOfConstraintIndices{F,S}()))
-    # g = MOI.get(inner, MOI.ConstraintFunction(), ci)
-    # y = MOI.get(inner, MOI.ListOfVariableIndices())
-    # sum_y = 1.0 * y[1] + 1.0 * y[2]
-    # @test isapprox(g, MOI.Utilities.vectorize([1.0, 1.0, sum_y, 0.0]))
+    c = MOI.add_constraint(model, f, MOI.LessThan(1.0))
+    F, S = MOI.VectorAffineFunction{Float64}, MOI.RotatedSecondOrderCone
+    ci = only(MOI.get(inner, MOI.ListOfConstraintIndices{F,S}()))
+    g = MOI.get(inner, MOI.ConstraintFunction(), ci)
+    y = MOI.get(inner, MOI.ListOfVariableIndices())
+    sum_y = 1.0 * y[1] + 1.0 * y[2]
+    @test isapprox(g, MOI.Utilities.vectorize([1.0, 1.0, sum_y, 0.0]))
     return
 end
 
@@ -363,8 +361,12 @@ function test_compute_sparse_sqrt_edge_cases()
         [1.0 0.0; 0.0 2.0],
         # Cholesky works, with pivoting
         [1.0 0.0 1.0; 0.0 1.0 1.0; 1.0 1.0 3.0],
+        # Cholesky fails due to 0 eigen value. LDL works
+        [1.0 1.0; 1.0 1.0],
         # Cholesky succeeds, even though 0 eigen value
         [2.0 2.0; 2.0 2.0],
+        # Cholesky fails because of 0 column/row. LDL works
+        [2.0 0.0; 0.0 0.0],
     ]
         B = SparseArrays.sparse(A)
         f = zero(MOI.ScalarQuadraticFunction{eltype(A)})
@@ -379,8 +381,6 @@ function test_compute_sparse_sqrt_edge_cases()
     # Test failures
     for A in Any[
         [-1.0 0.0; 0.0 1.0],
-        [1.0 1.0; 1.0 1.0],
-        [2.0 0.0; 0.0 0.0],
         # Found from test_quadratic_nonconvex_constraint_basic
         [0.0 -1.0; -1.0 0.0],
         # Different element type. We could potentially make this work in future,
@@ -399,6 +399,20 @@ function test_compute_sparse_sqrt_edge_cases()
     return
 end
 
+function test_compute_sparse_sqrt_fallback()
+    # Test the default fallback that is hit when LDLFactorizations isn't loaded.
+    # We could put the test somewhere else so it runs before this file is
+    # loaded, but that's pretty flakey for a long-term solution. Instead, we're
+    # going to abuse the lack of a strong type signature to hit it:
+    f = zero(MOI.ScalarAffineFunction{Float64})
+    A = SparseArrays.sparse([-1.0 0.0; 0.0 1.0])
+    @test_throws(
+        MOI.AddConstraintNotAllowed{typeof(f),MOI.GreaterThan{Float64}},
+        MOI.Bridges.Constraint.compute_sparse_sqrt(A, f, MOI.GreaterThan(0.0)),
+    )
+    return
+end
+
 end  # module
 
 TestConstraintQuadToSOC.runtests()