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Small fixes to let BlockTensorMaps work with GPU arrays #44

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Merged
lkdvos merged 7 commits into from
Feb 13, 2026
Merged

Small fixes to let BlockTensorMaps work with GPU arrays #44

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0c16631
Small fixes to let BlockTensorMaps work with GPU arrays
kshyatt Feb 13, 2026
9ba6e72
Indexing horror
kshyatt Feb 13, 2026
3a8f8bc
Update src/linalg/factorizations.jl
kshyatt Feb 13, 2026
ac30196
Use views
kshyatt Feb 13, 2026
d88a5d8
Add a check for blocksquarity
kshyatt Feb 13, 2026
a20c3f4
Update src/linalg/factorizations.jl
kshyatt Feb 13, 2026
3bfe9c6
No checks full gas
kshyatt Feb 13, 2026
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14 changes: 11 additions & 3 deletions src/linalg/factorizations.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -7,10 +7,18 @@ import MatrixAlgebraKit as MAK

const BlockBlasMat{T <: MAK.BlasFloat} = BlockMatrix{T}

function MatrixAlgebraKit.zero!(A::BlockBlasMat)
for bj in blockaxes(A, 2), bi in blockaxes(A, 1)
a = view(A, bi, bj)
MAK.zero!(a)
end
return A
end

function MatrixAlgebraKit.one!(A::BlockBlasMat)
_one, _zero = one(eltype(A)), zero(eltype(A))
@inbounds for j in axes(A, 2), i in axes(A, 1)
A[i, j] = ifelse(i == j, _one, _zero)
for bj in blockaxes(A, 2), bi in blockaxes(A, 1)
a = view(A, bi, bj)
bi == bj ? MAK.one!(a) : MAK.zero!(a)
end
return A
end
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12 changes: 6 additions & 6 deletions src/tensors/blocktensor.jl
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Expand Up @@ -123,10 +123,10 @@ end
# ------------------------
for (fname, felt) in ((:zeros, :zero), (:ones, :one))
@eval begin
function Base.$fname(::Type{T}, V::TensorMapSumSpace) where {T}
TT = blocktensormaptype(spacetype(V), numout(V), numin(V), T)
function Base.$fname(::Type{TorA}, V::TensorMapSumSpace) where {TorA}
TT = blocktensormaptype(spacetype(V), numout(V), numin(V), TorA)
t = TT(undef, V)
fill!(t, $felt(T))
fill!(t, $felt(scalartype(t)))
return t
end
end
Expand All @@ -136,9 +136,9 @@ for randfun in (:rand, :randn, :randexp)
randfun! = Symbol(randfun, :!)
@eval begin
function Random.$randfun(
rng::Random.AbstractRNG, ::Type{T}, V::TensorMapSumSpace
) where {T}
TT = blocktensormaptype(spacetype(V), numout(V), numin(V), T)
rng::Random.AbstractRNG, ::Type{TorA}, V::TensorMapSumSpace
) where {TorA}
TT = blocktensormaptype(spacetype(V), numout(V), numin(V), TorA)
t = TT(undef, V)
Random.$randfun!(rng, t)
return t
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