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[codex] Fix ComplexF64 SimpleTT site tensor regression #25

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Merged
shinaoka merged 2 commits into from
Apr 6, 2026
Merged

[codex] Fix ComplexF64 SimpleTT site tensor regression #25

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a965b78
test: cover ComplexF64 Tensor to TreeTN roundtrip
shinaoka Apr 6, 2026
6656674
fix: pass c64 site tensor buffer length in doubles
shinaoka Apr 6, 2026
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2 changes: 1 addition & 1 deletion src/C_API.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -1455,7 +1455,7 @@ function t4a_simplett_c64_site_tensor(
ptr,
Csize_t(site),
out_data,
Csize_t(length(out_data) ÷ 2),
Csize_t(length(out_data)),
out_left_dim,
out_site_dim,
out_right_dim
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105 changes: 105 additions & 0 deletions test/test_conversions.jl
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Original file line number Diff line number Diff line change
@@ -0,0 +1,105 @@
using Test
using Tensor4all
using Tensor4all.SimpleTT
using Tensor4all.TreeTN

import Tensor4all.SimpleTT: sitedims, linkdims, evaluate, sitetensor, fulltensor
import Tensor4all.TreeTN: MPS, nv, inner, linkdims as ttn_linkdims
using LinearAlgebra: norm

@testset "SimpleTT <-> TreeTN Conversions" begin
@testset "SimpleTT -> MPS -> SimpleTT round-trip" begin
@testset "rank-1 constant" begin
tt = SimpleTensorTrain([2, 3, 4], 1.5)
mps = MPS(tt)
@test nv(mps) == 3

tt2 = SimpleTensorTrain(mps)
@test length(tt2) == 3
@test sitedims(tt2) == [2, 3, 4]

# Check values match
arr1 = fulltensor(tt)
arr2 = fulltensor(tt2)
@test arr1 ≈ arr2
end

@testset "higher rank" begin
t1 = randn(1, 2, 3)
t2 = randn(3, 4, 2)
t3 = randn(2, 3, 1)
tt = SimpleTensorTrain([t1, t2, t3])
mps = MPS(tt)
@test nv(mps) == 3

tt2 = SimpleTensorTrain(mps)
@test length(tt2) == 3
@test sitedims(tt2) == [2, 4, 3]
@test linkdims(tt2) == [3, 2]

arr1 = fulltensor(tt)
arr2 = fulltensor(tt2)
@test arr1 ≈ arr2
end

@testset "single site" begin
tt = SimpleTensorTrain([3], 2.0)
mps = MPS(tt)
@test nv(mps) == 1

tt2 = SimpleTensorTrain(mps)
@test length(tt2) == 1
@test sitedims(tt2) == [3]

arr1 = fulltensor(tt)
arr2 = fulltensor(tt2)
@test arr1 ≈ arr2
end

@testset "two sites" begin
tt = SimpleTensorTrain([2, 5], 3.0)
mps = MPS(tt)
@test nv(mps) == 2

tt2 = SimpleTensorTrain(mps)
@test length(tt2) == 2
@test sitedims(tt2) == [2, 5]

arr1 = fulltensor(tt)
arr2 = fulltensor(tt2)
@test arr1 ≈ arr2
end
end

@testset "ComplexF64 round-trip" begin
tt = SimpleTensorTrain([2, 3, 4], 1.0 + 2.0im)
mps = MPS(tt)
@test nv(mps) == 3

tt2 = SimpleTensorTrain(mps)
@test length(tt2) == 3
@test sitedims(tt2) == [2, 3, 4]

arr1 = fulltensor(tt)
arr2 = fulltensor(tt2)
@test arr1 ≈ arr2
end

@testset "MPS -> SimpleTT -> MPS" begin
sites = [Tensor4all.Index(2) for _ in 1:4]
mps = TreeTN.random_mps(sites; linkdims=3)

tt = SimpleTensorTrain(mps)
@test length(tt) == 4
@test sitedims(tt) == [2, 2, 2, 2]

mps2 = MPS(tt)
@test nv(mps2) == 4

# Check that the dense tensor representation matches
dense1 = TreeTN.to_dense(mps)
arr1 = data(dense1)
arr2 = fulltensor(tt)
@test arr1 ≈ arr2
end
end
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