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LinearAlgebra traited matrix operations #48861

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LinearAlgebra traited matrix operations #48861

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36 changes: 36 additions & 0 deletions stdlib/LinearAlgebra/src/LinearAlgebra.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -415,6 +415,30 @@ See also: `copymutable_oftype`.
"""
copy_similar(A::AbstractArray, ::Type{T}) where {T} = copyto!(similar(A, T, size(A)), A)

"""
AbstractStorageTrait

Supertype for all matrix traits.
The concrete subtypes shall always contain a field named `data` keeping the
attributed object.
"""
abstract type AbstractStorageTrait{T} end
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Suggested change
abstract type AbstractStorageTrait{T} end
abstract type AbstractStorageTrait{T} end

"""
DenseStorage

Concrete type for all types of matrix related traits.
"""
struct DenseStorage{T} <: AbstractStorageTrait{T}
data::T
DenseStorage(x::T) where T = new{T}(x)
end

"""
Storage(a::T) -> AbstractStorageTrait

Create a trait type object related to `a`.
"""
Storage(a::T) where T = storage_trait(T)(a)

include("adjtrans.jl")
include("transpose.jl")
Expand Down Expand Up @@ -453,6 +477,18 @@ include("schur.jl")
include("structuredbroadcast.jl")
include("deprecated.jl")

const WrapperArrayTypes{T,MT} = Union{
SubArray{T,N,MT} where N,
Adjoint{T,MT},
Transpose{T,MT},
AbstractTriangular{T,MT},
UpperHessenberg{T,MT},
Symmetric{T,MT},
Hermitian{T,MT},
}
storage_trait(::Type{<:AbstractArray}) = DenseStorage
storage_trait(::Type{<:WrapperArrayTypes{T,MT}}) where {T,MT} = storage_trait(MT)

const ⋅ = dot
const × = cross
export ⋅, ×
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5 changes: 5 additions & 0 deletions stdlib/LinearAlgebra/src/generic.jl
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Expand Up @@ -1108,6 +1108,11 @@ true
```
"""
function (\)(A::AbstractMatrix, B::AbstractVecOrMat)
Storage(A) \ B
end

function (\)(ta::DenseStorage, B::AbstractVecOrMat)
A = ta.data
require_one_based_indexing(A, B)
m, n = size(A)
if m == n
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8 changes: 8 additions & 0 deletions stdlib/LinearAlgebra/src/matmul.jl
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Expand Up @@ -137,9 +137,17 @@ julia> [1 1; 0 1] * [1 0; 1 1]
```
"""
function (*)(A::AbstractMatrix, B::AbstractMatrix)
(*)(Storage(A), Storage(B))
end

# implementation for the general case (getindex should be fast operation)
function (*)(ta::DenseStorage, tb::DenseStorage)
A = ta.data
B = tb.data
TS = promote_op(matprod, eltype(A), eltype(B))
mul!(similar(B, TS, (size(A, 1), size(B, 2))), A, B)
end

# optimization for dispatching to BLAS, e.g. *(::Matrix{Float32}, ::Matrix{Float64})
# but avoiding the case *(::Matrix{<:BlasComplex}, ::Matrix{<:BlasReal})
# which is better handled by reinterpreting rather than promotion
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