More tweaks by kshyatt · Pull Request #375 · QuantumKitHub/TensorKit.jl

kshyatt · 2026-02-18T12:42:45Z

Needed to get more MPSKit examples working

codecov · 2026-02-26T13:01:03Z

Codecov Report

❌ Patch coverage is 45.83333% with 13 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
src/tensors/abstracttensor.jl	25.00%	6 Missing ⚠️
ext/TensorKitCUDAExt/cutensormap.jl	0.00%	3 Missing ⚠️
src/tensors/braidingtensor.jl	60.00%	2 Missing ⚠️
src/tensors/adjoint.jl	50.00%	1 Missing ⚠️
src/tensors/indexmanipulations.jl	75.00%	1 Missing ⚠️

Files with missing lines	Coverage Δ
src/tensors/diagonal.jl	`86.97% <100.00%> (-2.80%)`	⬇️
src/tensors/tensor.jl	`82.75% <100.00%> (-1.73%)`	⬇️
src/tensors/adjoint.jl	`87.50% <50.00%> (-2.50%)`	⬇️
src/tensors/indexmanipulations.jl	`73.41% <75.00%> (-0.53%)`	⬇️
src/tensors/braidingtensor.jl	`68.78% <60.00%> (-1.61%)`	⬇️
ext/TensorKitCUDAExt/cutensormap.jl	`70.83% <0.00%> (-3.84%)`	⬇️
src/tensors/abstracttensor.jl	`53.73% <25.00%> (-1.58%)`	⬇️

... and 19 files with indirect coverage changes

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kshyatt · 2026-02-27T11:14:43Z

Let's make this a draft too to cut down on CI thrash

lkdvos

Left some comment throughout, there are some things that I am not entirely convinced by but the rest looks great, thanks for working through all of this!

For the similarstoragetype(tensor, storagetype) calls that you added, this seems like something we should probably discuss over a separate PR, and it would be great if we could consolidate this one to get the remainder of the fixes in.
Would you be up for splitting these two things, and then getting this merged?

The same kind of holds for some of the comments I made too, if we can just postpone the things that are not obvious, but already get the other parts in, that would probably be helpful.

(Note that I am very much aware that none of this is your fault and this PR has lived for too long so the design shifts a bit, for which I do apologize!)

kshyatt · 2026-03-31T16:05:16Z

It's completely fine!! This has stayed open as I work through adding more tests for MPSKit, so I think we can pare off the simpler stuff we agree on, and then discuss things that are more contentious.

github-actions · 2026-03-31T17:55:16Z

Your PR no longer requires formatting changes. Thank you for your contribution!

lkdvos · 2026-04-27T13:26:42Z

I guess the changes here are no longer necessary since BraidingTensor now knows its own storagetype?

I'm checking this now with MPSKit!

lkdvos · 2026-04-27T13:28:10Z

    W = insertleftunit(space(t), Val(i); conj, dual)
    if t isa TensorMap
-        return TensorMap{scalartype(t)}(copy ? Base.copy(t.data) : t.data, W)
+        return TensorMapWithStorage{scalartype(t), storagetype(t)}(copy ? Base.copy(t.data) : t.data, W)


This doesn't look necessary, isn't the storagetype automatically deduced from the provided data vector?

lkdvos · 2026-04-27T13:28:20Z

    W = insertrightunit(space(t), Val(i); conj, dual)
    if t isa TensorMap
-        return TensorMap{scalartype(t)}(copy ? Base.copy(t.data) : t.data, W)
+        return TensorMapWithStorage{scalartype(t), storagetype(t)}(copy ? Base.copy(t.data) : t.data, W)


Same comment here

lkdvos · 2026-04-27T13:28:26Z

    W = removeunit(space(t), Val(i))
    if t isa TensorMap
-        return TensorMap{scalartype(t)}(copy ? Base.copy(t.data) : t.data, W)
+        return TensorMapWithStorage{scalartype(t), storagetype(t)}(copy ? Base.copy(t.data) : t.data, W)


Same comment here

lkdvos · 2026-04-27T13:38:28Z

+function similarstoragetype(::Type{<:AbstractTensorMap{T, S, N₁, N₂}}, ::Type{TA}) where {T <: Number, TA <: DenseVector, S, N₁, N₂}
+    return similarstoragetype(TA, T)
+end
+function similarstoragetype(t::AbstractTensorMap{T, S, N₁, N₂}, ::Type{TA}) where {T <: Number, TA <: DenseVector, S, N₁, N₂}
+    return similarstoragetype(typeof(t), TA)
+end

 # implement on arrays
 similarstoragetype(::Type{A}) where {A <: DenseVector{<:Number}} = A
+similarstoragetype(::Type{A}, ::Type{A}) where {A <: DenseVector{<:Number}} = A


Are we using these somewhere? I'm slightly confused about the meaning of these functions with last argument A <: DenseVector. In general, I thought this function mostly meant: for given tensor T1 (and possibly T2), create a new storagetype that is compatible with T1 but has scalartype T. In the case where we pass in a storagetype to begin with, doesn't that mean we already know that the answer has to be A?.

lkdvos · 2026-04-27T13:39:47Z

 space(t::AdjointTensorMap) = adjoint(space(parent(t)))
 dim(t::AdjointTensorMap) = dim(parent(t))
 storagetype(::Type{AdjointTensorMap{T, S, N₁, N₂, TT}}) where {T, S, N₁, N₂, TT} = storagetype(TT)
+similarstoragetype(::AdjointTensorMap{T, S, N₁, N₂, TT}, ::Type{T′}) where {T, S, N₁, N₂, TT, T′ <: Number} = similarstoragetype(TT, T′)


Isn't this also automatic from the definition of similarstoragetype(t::AbstractTensorMap, T) = similarstoragetype(storagetype(t), T) along with storagetype the line above?

lkdvos · 2026-04-27T13:40:11Z

 dim(t::AdjointTensorMap) = dim(parent(t))
 storagetype(::Type{AdjointTensorMap{T, S, N₁, N₂, TT}}) where {T, S, N₁, N₂, TT} = storagetype(TT)
+similarstoragetype(::AdjointTensorMap{T, S, N₁, N₂, TT}, ::Type{T′}) where {T, S, N₁, N₂, TT, T′ <: Number} = similarstoragetype(TT, T′)
+similarstoragetype(::AdjointTensorMap{T, S, N₁, N₂, TT}, ::Type{TA}) where {T, S, N₁, N₂, TT, TA <: DenseVector} = similarstoragetype(TT, TA)


Same comment here about why the second argument would already be a <:DenseVector.

lkdvos · 2026-04-27T13:40:42Z

+        $promote_op(::Type{TA}, ::Type{I}) where {TA <: DenseVector, I <: Sector} =
+            similarstoragetype(TA, $promote_op(eltype(TA), I))


This is also not really used I guess?

kshyatt force-pushed the ksh/cuda_tweaks branch from 3bed38d to 8665c4a Compare February 18, 2026 13:35

lkdvos reviewed Feb 18, 2026

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kshyatt mentioned this pull request Feb 20, 2026

Add a disamgiguating conversion lkdvos/BlockTensorKit.jl#47

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kshyatt force-pushed the ksh/cuda_tweaks branch from eabfce9 to 0c903ac Compare February 25, 2026 15:47

kshyatt marked this pull request as draft February 27, 2026 11:14

kshyatt force-pushed the ksh/cuda_tweaks branch 2 times, most recently from f5857b3 to 32e182d Compare March 12, 2026 12:36

kshyatt force-pushed the ksh/cuda_tweaks branch 2 times, most recently from f5faaf6 to 2359d28 Compare March 23, 2026 14:24

lkdvos mentioned this pull request Mar 26, 2026

MAK v0.6.5 updates #390

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lkdvos reviewed Mar 31, 2026

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kshyatt force-pushed the ksh/cuda_tweaks branch from d0afb2d to 8a12178 Compare April 8, 2026 06:55

kshyatt force-pushed the ksh/cuda_tweaks branch from 8a12178 to ad62dad Compare April 22, 2026 10:17

kshyatt mentioned this pull request Apr 23, 2026

Some more small changes for GPU support lkdvos/BlockTensorKit.jl#48

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kshyatt force-pushed the ksh/cuda_tweaks branch 2 times, most recently from a3f4bfc to 5259ba2 Compare April 27, 2026 08:42

More tweaks for GPU support

3c5a575

kshyatt force-pushed the ksh/cuda_tweaks branch from d29251a to 3c5a575 Compare April 27, 2026 10:21

fix typo

4c599c2

lkdvos reviewed Apr 27, 2026

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		$promote_op(::Type{TA}, ::Type{I}) where {TA <: DenseVector, I <: Sector} =
		similarstoragetype(TA, $promote_op(eltype(TA), I))

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