Remove batched and non-batched bisection for now

Author: kshyatt

ext/MatrixAlgebraKitAMDGPUExt/MatrixAlgebraKitAMDGPUExt.jl

@@ -46,7 +46,7 @@ for f in (:geqrf!, :ungqr!, :unmqr!)
     @eval $f(::ROCSOLVER, args...) = YArocSOLVER.$f(args...)
 end
 
-MatrixAlgebraKit.supports_svd_full(::ROCSOLVER, f::Symbol) = f in (:qr_iteration, :jacobi, :divide_and_conquer, :bisection)
+MatrixAlgebraKit.supports_svd_full(::ROCSOLVER, f::Symbol) = f in (:qr_iteration, :jacobi, :divide_and_conquer)
 
 # rocSOLVER's `gesvd*_batched` functions take the batch as an array
 # of device pointers, so a group of equally sized matrices
@@ -93,22 +93,6 @@ gesvdj_batched!(::ROCSOLVER, As::AbstractVector{<:StridedROCMatrix}, Ss::Strided
 gesvdj_batched!(::ROCSOLVER, As::StridedROCArray{T, 3}, Ss::StridedROCMatrix, Us::StridedROCArray{T, 3}, Vᴴs::StridedROCArray{T, 3}; kwargs...) where {T <: BlasFloat} =
     YArocSOLVER.gesvdj_strided_batched!(As, Ss, Us, Vᴴs; kwargs...)
 
-function gesvdx_batched!(::ROCSOLVER, As::AbstractVector{<:StridedROCMatrix}, Ss::StridedROCMatrix, Us::StridedROCArray{T, 3}, Vᴴs::StridedROCArray{T, 3}; kwargs...) where {T <: BlasFloat}
-    YArocSOLVER.gesvdx_batched!(As, Ss, Us, Vᴴs; kwargs...)
-    _complete_svd_basis!(Us, Vᴴs, size(Ss, 1))
-    return Ss, Us, Vᴴs
-end
-function gesvdx_batched!(::ROCSOLVER, As::StridedROCArray{T, 3}, Ss::StridedROCMatrix, Us::StridedROCArray{T, 3}, Vᴴs::StridedROCArray{T, 3}; kwargs...) where {T <: BlasFloat}
-    YArocSOLVER.gesvdx_strided_batched!(As, Ss, Us, Vᴴs; kwargs...)
-    _complete_svd_basis!(Us, Vᴴs, size(Ss, 1))
-    return Ss, Us, Vᴴs
-end
-
-function gesvdx!(::ROCSOLVER, A::StridedROCMatrix, S::StridedROCVector, U::StridedROCMatrix, Vᴴ::StridedROCMatrix; kwargs...)
-    YArocSOLVER.gesvdx!(A, S, U, Vᴴ; kwargs...)
-    _complete_svd_basis!(U, Vᴴ, length(S))
-    return S, U, Vᴴ
-end
 gesdd!(::ROCSOLVER, A::StridedROCMatrix, S::StridedROCVector, U::StridedROCMatrix, Vᴴ::StridedROCMatrix; kwargs...) =
     YArocSOLVER.gesdd!(A, S, U, Vᴴ; kwargs...)
 

src/implementations/svd.jl

@@ -249,31 +249,6 @@ function complete_svd_basis!(U::AbstractMatrix, Vᴴ::AbstractMatrix, minmn::Int
     return U, Vᴴ
 end
 
-# Some methods (e.g. `gesvdx`) only compute the leading `min(m, n)` singular vectors.
-# If `U` or `Vᴴ` is square (`(batched_)svd_full!`), the remaining columns (row) of
-# `U` (`Vᴴ`) need to be filled with an orthonormal basis for the complement of the
-# computed singular vectors.
-function _complete_svd_basis!(U::AbstractMatrix, Vᴴ::AbstractMatrix, minmn::Int)
-    if size(U, 2) > minmn
-        N = qr_null!(copy(view(U, :, 1:minmn)))
-        copyto!(view(U, :, (minmn + 1):size(U, 2)), N)
-    end
-    if size(Vᴴ, 1) > minmn
-        V = view(Vᴴ, 1:minmn, :)
-        N = qr_null!(adjoint!(similar(V, reverse(size(V))), V))
-        adjoint!(view(Vᴴ, (minmn + 1):size(Vᴴ, 1), :), N)
-    end
-    return U, Vᴴ
-end
-function _complete_svd_basis!(U::AbstractArray{<:Any, 3}, Vᴴ::AbstractArray{<:Any, 3}, minmn::Int)
-    (size(U, 2) > minmn || size(Vᴴ, 1) > minmn) || return U, Vᴴ
-    for (u, vᴴ) in zip(eachslice(U, dims = 3), eachslice(Vᴴ, dims = 3))
-        _complete_svd_basis!(u, vᴴ, minmn)
-    end
-    return U, Vᴴ
-end
-
-
 """
     requires_tall(alg) -> Bool
 

test/decompositions/svd.jl

@@ -87,7 +87,7 @@ if AMDGPU.functional()
     for T in BLASFloats, m in (0, 23), n in (0, 17, m, 27)
         TestSuite.seed_rng!(123)
         TestSuite.test_svd(ROCMatrix{T}, (m, n))
-        AMD_SVD_ALGS = (QRIteration(), Jacobi(), DivideAndConquer(), Bisection())
+        AMD_SVD_ALGS = (QRIteration(), Jacobi(), DivideAndConquer())
         TestSuite.test_svd_algs(ROCMatrix{T}, (m, n), AMD_SVD_ALGS)
         TestSuite.test_svd_batched(ROCMatrix{T}, (m, n), batch_size)
         TestSuite.test_svd_batched_algs(ROCMatrix{T}, (m, n), batch_size, AMD_SVD_ALGS)