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A few more small fixes for upstream + CUDA #373

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Merged
kshyatt merged 6 commits into from
Feb 12, 2026
Merged

A few more small fixes for upstream + CUDA #373

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c51a744
Small fixes for upstream + CUDA
kshyatt Jan 30, 2026
f99e931
Suggestion
kshyatt Feb 11, 2026
0f345f4
Use default memory
kshyatt Feb 11, 2026
51fea05
Have Base.ones and zeros accept CuArray
kshyatt Feb 11, 2026
76c3a0c
Try to finagle ones and zeros again
kshyatt Feb 12, 2026
b618988
Fix CUDA test
kshyatt Feb 12, 2026
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4 changes: 4 additions & 0 deletions ext/TensorKitCUDAExt/cutensormap.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -138,6 +138,10 @@ function Base.promote_rule(
return CuTensorMap{T, S, N₁, N₂}
end

TensorKit.promote_storage_rule(::Type{CuArray{T, N}}, ::Type{<:CuArray{T, N}}) where {T, N} =
CuArray{T, N, CUDA.default_memory}


# CuTensorMap exponentation:
function TensorKit.exp!(t::CuTensorMap)
domain(t) == codomain(t) ||
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8 changes: 8 additions & 0 deletions test/cuda/tensors.jl
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Expand Up @@ -55,6 +55,14 @@ for V in spacelist
@test domain(t) == one(W)
@test typeof(t) == TensorMap{Float64, spacetype(t), 5, 0, CuVector{Float64, CUDA.DeviceMemory}}
end
for f in (Base.ones, Base.zeros)
t = @constinferred f(CuVector{Float64, CUDA.DeviceMemory}, W)
@test scalartype(t) == Float64
@test codomain(t) == W
@test space(t) == (W ← one(W))
@test domain(t) == one(W)
@test typeof(t) == TensorMap{Float64, spacetype(t), 5, 0, CuVector{Float64, CUDA.DeviceMemory}}
end
for f in (rand, randn)
t = @constinferred f(CuVector{Float64, CUDA.DeviceMemory}, W)
@test scalartype(t) == Float64
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9 changes: 9 additions & 0 deletions test/tensors/tensors.jl
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Expand Up @@ -44,6 +44,15 @@ for V in spacelist
@test space(t) == (W ← one(W))
@test domain(t) == one(W)
@test typeof(t) == TensorMap{T, spacetype(t), 5, 0, Vector{T}}
# Array type input
t = @constinferred zeros(Vector{T}, W)
@test @constinferred(hash(t)) == hash(deepcopy(t))
@test scalartype(t) == T
@test norm(t) == 0
@test codomain(t) == W
@test space(t) == (W ← one(W))
@test domain(t) == one(W)
@test typeof(t) == TensorMap{T, spacetype(t), 5, 0, Vector{T}}
# blocks
bs = @constinferred blocks(t)
if !isempty(blocksectors(t)) # multifusion space ending on module gives empty data
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