Use TestSuite for projections tests

Author: kshyatt

test/amd/projections.jl

@@ -1,106 +1,35 @@
 using MatrixAlgebraKit
-using MatrixAlgebraKit: check_hermitian, default_hermitian_tol
 using Test
 using TestExtras
 using StableRNGs
 using LinearAlgebra: LinearAlgebra, Diagonal, norm, normalize!
+using CUDA, AMDGPU
 
-const BLASFloats = (Float32, Float64, ComplexF32, ComplexF64)
+BLASFloats = (Float32, Float64, ComplexF32, ComplexF64)
+GenericFloats = (Float16, BigFloat, Complex{BigFloat})
 
-@testset "project_(anti)hermitian! for T = $T" for T in BLASFloats
-    rng = StableRNG(123)
-    m = 54
-    noisefactor = eps(real(T))^(3 / 4)
+@isdefined(TestSuite) || include("testsuite/TestSuite.jl")
+using .TestSuite
 
-    mat0 = zeros(T, (1, 1))
-    @test ishermitian(mat0)
-    @test ishermitian(mat0; atol = default_hermitian_tol(mat0))
-    @test isnothing(check_hermitian(mat0))
+is_buildkite = get(ENV, "BUILDKITE", "false") == "true"
 
-    for alg in (NativeBlocked(blocksize = 16), NativeBlocked(blocksize = 32), NativeBlocked(blocksize = 64))
-        for A in (randn(rng, T, m, m), Diagonal(randn(rng, T, m)))
-            Ah = (A + A') / 2
-            Aa = (A - A') / 2
-            Ac = copy(A)
 
-            Bh = project_hermitian(A, alg)
-            @test ishermitian(Bh)
-            @test Bh ≈ Ah
-            @test A == Ac
-            Bh_approx = Bh + noisefactor * Aa
-            # this is still hermitian for real Diagonal: |A - A'| == 0
-            @test !ishermitian(Bh_approx) || norm(Aa) == 0
-            @test ishermitian(Bh_approx; rtol = 10 * noisefactor)
-
-            Ba = project_antihermitian(A, alg)
-            @test isantihermitian(Ba)
-            @test Ba ≈ Aa
-            @test A == Ac
-            Ba_approx = Ba + noisefactor * Ah
-            @test !isantihermitian(Ba_approx)
-            # this is never anti-hermitian for real Diagonal: |A - A'| == 0
-            @test isantihermitian(Ba_approx; rtol = 10 * noisefactor) || norm(Aa) == 0
-
-            Bh = project_hermitian!(Ac, alg)
-            @test Bh === Ac
-            @test ishermitian(Bh)
-            @test Bh ≈ Ah
-
-            copy!(Ac, A)
-            Ba = project_antihermitian!(Ac, alg)
-            @test Ba === Ac
-            @test isantihermitian(Ba)
-            @test Ba ≈ Aa
+m = 54
+for T in (BLASFloats..., GenericFloats...)
+    TestSuite.seed_rng!(123)
+    if T ∈ BLASFloats
+        if CUDA.functional()
+            TestSuite.test_projections(CuMatrix{T}, (m, m); test_blocksize = false)
+            TestSuite.test_projections(Diagonal{T, CuVector{T}}, m; test_blocksize = false)
         end
-    end
-
-    # test approximate error calculation
-    A = normalize!(randn(rng, T, m, m))
-    Ah = project_hermitian(A)
-    Aa = project_antihermitian(A)
-
-    Ah_approx = Ah + noisefactor * Aa
-    ϵ = norm(project_antihermitian(Ah_approx))
-    @test !ishermitian(Ah_approx; atol = (999 // 1000) * ϵ)
-    @test ishermitian(Ah_approx; atol = (1001 // 1000) * ϵ)
-
-    Aa_approx = Aa + noisefactor * Ah
-    ϵ = norm(project_hermitian(Aa_approx))
-    @test !isantihermitian(Aa_approx; atol = (999 // 1000) * ϵ)
-    @test isantihermitian(Aa_approx; atol = (1001 // 1000) * ϵ)
-end
-
-@testset "project_isometric! for T = $T" for T in BLASFloats
-    rng = StableRNG(123)
-    m = 54
-    @testset "size ($m, $n)" for n in (37, m)
-        k = min(m, n)
-        if LinearAlgebra.LAPACK.version() < v"3.12.0"
-            svdalgs = (LAPACK_DivideAndConquer(), LAPACK_QRIteration(), LAPACK_Bisection())
-        else
-            svdalgs = (LAPACK_DivideAndConquer(), LAPACK_QRIteration(), LAPACK_Bisection(), LAPACK_Jacobi())
-        end
-        algs = (PolarViaSVD.(svdalgs)..., PolarNewton())
-        @testset "algorithm $alg" for alg in algs
-            A = randn(rng, T, m, n)
-            W = project_isometric(A, alg)
-            @test isisometric(W)
-            W2 = project_isometric(W, alg)
-            @test W2 ≈ W # stability of the projection
-            @test W * (W' * A) ≈ A
-
-            Ac = similar(A)
-            W2 = @constinferred project_isometric!(copy!(Ac, A), W, alg)
-            @test W2 === W
-            @test isisometric(W)
-
-            # test that W is closer to A then any other isometry
-            for k in 1:10
-                δA = randn(rng, T, m, n)
-                W = project_isometric(A, alg)
-                W2 = project_isometric(A + δA / 100, alg)
-                @test norm(A - W2) > norm(A - W)
-            end
+        if AMDGPU.functional()
+            TestSuite.test_projections(ROCMatrix{T}, (m, m); test_blocksize = false)
+            TestSuite.test_projections(Diagonal{T, ROCVector{T}}, m; test_blocksize = false)
         end
     end
+    if !is_buildkite
+        TestSuite.test_projections(T, (m, m))
+        AT = Diagonal{T, Vector{T}}
+        TestSuite.test_projections(AT, m)
+    end
 end

test/cuda/projections.jl

@@ -7,9 +7,6 @@ if !is_buildkite
     @safetestset "Algorithms" begin
         include("algorithms.jl")
     end
-    @safetestset "Projections" begin
-        include("projections.jl")
-    end
     @safetestset "Truncate" begin
         include("truncate.jl")
     end
@@ -71,12 +68,12 @@ end
     include("qr.jl")
     include("lq.jl")
 end
+@safetestset "Projections" begin
+    include("projections.jl")
+end
 
 using CUDA
 if CUDA.functional()
-    @safetestset "CUDA Projections" begin
-        include("cuda/projections.jl")
-    end
     @safetestset "CUDA SVD" begin
         include("cuda/svd.jl")
     end
@@ -96,9 +93,6 @@ end
 
 using AMDGPU
 if AMDGPU.functional()
-    @safetestset "AMDGPU Projections" begin
-        include("amd/projections.jl")
-    end
     @safetestset "AMDGPU SVD" begin
         include("amd/svd.jl")
     end

test/projections.jl

@@ -71,5 +71,6 @@ is_pivoted(alg::MatrixAlgebraKit.LQViaTransposedQR) = is_pivoted(alg.qr_alg)
 
 include("qr.jl")
 include("lq.jl")
+include("projections.jl")
 
 end