Fix the tests with complex numbers

lib/cusolver/linalg.jl

@@ -65,20 +65,15 @@ function Base.:\(_A::CuMatOrAdj, _B::CuOrAdj)
  return X
 end
 
-for (wrapper, blas_types) in ((:Symmetric, :BlasReal),
- (:Hermitian, :BlasFloat))
- @eval begin
- function Base.:\(A::$wrapper{<:$blas_types,<:CuMatOrAdj}, _B::CuOrAdj)
- uplo = A.uplo
- A, B = copy_cublasfloat(_A.data, _B)
-
- # LDLᴴ decomposition with partial pivoting
- factors, ipiv, info = sytrf!(uplo, F)
- ipiv = CuVector{Int64}(ipiv)
- X = sytrs!(uplo, factors, ipiv, B)
- return X
- end
- end
+function Base.:\(_A::Symmetric{<:Any,<:CuMatOrAdj}, _B::CuOrAdj)
+ uplo = A.uplo
+ A, B = copy_cublasfloat(_A.data, _B)
+
+ # LDLᴴ decomposition with partial pivoting
+ factors, ipiv, info = sytrf!(uplo, A)
+ ipiv = CuVector{Int64}(ipiv)
+ X = sytrs!(uplo, factors, ipiv, B)
+ return X
 end
 
 # patch JuliaLang/julia#40899 to create a CuArray
@@ -370,19 +365,14 @@ function LinearAlgebra.inv(A::StridedCuMatrix{T}) where T <: BlasFloat
  return B
 end
 
-for (wrapper, blas_types) in ((:Symmetric, :BlasReal),
- (:Hermitian, :BlasFloat))
- @eval begin
- function LinearAlgebra.inv(A::$wrapper{T,<:StridedCuMatrix{T}}) where T <: $blas_types
- n = checksquare(A)
- F = copy(A.data)
- factors, ipiv, info = sytrf!(A.uplo, F)
- ipiv = CuVector{Int64}(ipiv)
- B = CuMatrix{T}(I, n, n)
- sytrs!(A.uplo, factors, ipiv, B)
- return B
- end
- end
+function LinearAlgebra.inv(A::Symmetric{T,<:StridedCuMatrix{T}}) where T <: BlasFloat
+ n = checksquare(A)
+ F = copy(A.data)
+ factors, ipiv, info = sytrf!(A.uplo, F)
+ ipiv = CuVector{Int64}(ipiv)
+ B = CuMatrix{T}(I, n, n)
+ sytrs!(A.uplo, factors, ipiv, B)
+ return B
 end
 
 for (triangle, uplo, diag) in ((:LowerTriangular, 'L', 'N'),

test/libraries/cusolver/dense.jl

@@ -17,20 +17,14 @@ k = 1
  @test Array(dI) ≈ I
  end
 
- @testset "inv -- symmetric -- hermitian" begin
+ @testset "inv -- symmetric" begin
  A = rand(elty,n,n)
- A = A + A'
- dA = Hermitian(CuArray(A))
+ A = A + tranpose(A)
+ dA = Symmetic(CuArray(A))
  dA⁻¹ = inv(dA)
  dI = dA.data * dA⁻¹
+ display(dI)
  @test Array(dI) ≈ I
-
- if elty <: Real
- dA = Symmetric(CuArray(A))
- dA⁻¹ = inv(dA)
- dI = dA.data * dA⁻¹
- @test Array(dI) ≈ I
- end
  end
 
  @testset "inv -- triangular" begin
@@ -39,7 +33,7 @@ k = 1
  A = rand(elty,n,n)
  A = uplo == 'L' ? tril(A) : triu(A)
  A = diag == 'N' ? A : A - Diagonal(A) + I
- dA = CuArray(A)
+ dA = triangle(CuArray(A))
  dA⁻¹ = inv(dA)
  dI = dA.data * dA⁻¹
  @test Array(dI) ≈ I
@@ -712,28 +706,25 @@ end
 ], elty2 in [
  Float16, Float32, Float64, ComplexF16, ComplexF32, ComplexF64, Int32, Int64, Complex{Int32}, Complex{Int64}
 ]
- @testset "Square symmetric and hermitian linear systems" begin
+ @testset "Symmetric linear systems" begin
  A = rand(elty1,n,n)
- A = A + A'
+ A = A + transpose(A)
  B = rand(elty2,n,5)
  b = rand(elty2,n)
  d_A = CuArray(A)
  d_B = CuArray(B)
  d_b = CuArray(b)
  cublasfloat = promote_type(Float32, promote_type(elty1, elty2))
- for wrapper in (Symmetric, Hermitian)
- (wrapper == Symmetric) && !(cublasfloat <: Real) && continue
- Af = wrapper(cublasfloat.(A))
- Bf = cublasfloat.(B)
- bf = cublasfloat.(b)
- @test Array(d_A \ d_B) ≈ (Af \ Bf)
- @test Array(d_A \ d_b) ≈ (Af \ bf)
- @inferred d_A \ d_B
- @inferred d_A \ d_b
- end
+ Af = Symmetric(cublasfloat.(A))
+ Bf = cublasfloat.(B)
+ bf = cublasfloat.(b)
+ @test Array(d_A \ d_B) ≈ (Af \ Bf)
+ @test Array(d_A \ d_b) ≈ (Af \ bf)
+ @inferred d_A \ d_B
+ @inferred d_A \ d_b
  end
 
- @testset "Square unsymmetric linear systems" begin
+ @testset "Square and unsymmetric linear systems" begin
  A = rand(elty1,n,n)
  B = rand(elty2,n,5)
  b = rand(elty2,n)

test/libraries/cusolver/dense_generic.jl

@@ -10,7 +10,7 @@ p = 5
  for uplo in ('L', 'U')
  A = rand(elty,n,n)
  B = rand(elty,n,p)
- A = A + A'
+ A = A + transpose(A)
  d_A = CuMatrix(A)
  d_B = CuMatrix(B)
  d_A, d_ipiv, _ = CUSOLVER.sytrf!(uplo, d_A)