Add an adapt method for SectorVector

src/tensors/sectorvector.jl

@@ -41,6 +41,8 @@ Base.similar(v::SectorVector, ::Type{T}, V::ElementarySpace) where {T} = SectorV
 
 Base.copy(v::SectorVector) = SectorVector(copy(v.data), v.structure)
 
+Adapt.adapt_structure(to, v::SectorVector) = SectorVector(Adapt.adapt(to, parent(v)), v.structure)
+
 # AbstractDict interface
 # ----------------------
 Base.keytype(v::SectorVector) = keytype(typeof(v))

test/amd/tensors.jl

@@ -97,6 +97,23 @@ for V in spacelist
                 @test domain(t2) == one(W)
             end
         end
+        @timedtestset "Adapt SectorVector" begin
+            for T in (Float32, ComplexF64)
+                v = TensorKit.SectorVector{T}(undef, V1)
+                rand!(parent(v))
+                v_gpu = @constinferred adapt(ROCArray, v)
+                @test v_gpu isa TensorKit.SectorVector{T, I, <:ROCArray{T}}
+                @test v_gpu.structure == v.structure
+                v_cpu = @constinferred adapt(Array, v_gpu)
+                @test v_cpu isa TensorKit.SectorVector{T, I, Vector{T}}
+                @test parent(v_cpu) == parent(v)
+                t = AMDGPU.randn(T, V1 ⊗ V2 ← V3)
+                s = svd_vals(t)
+                s_cpu = adapt(Array, s)
+                @test parent(s_cpu) == collect(parent(s))
+                @test all(c -> block(s_cpu, c) == collect(block(s, c)), blocksectors(s))
+            end
+        end
         @timedtestset "Tensor Dict conversion" begin
             W = V1 ⊗ V2 ← (V3 ⊗ V4 ⊗ V5)'
             for T in (Int, Float32, ComplexF64)

test/cuda/tensors.jl

@@ -115,6 +115,23 @@ for V in spacelist
                 @test storagetype(t_cpu) <: Array{T}
             end
         end
+        @timedtestset "Adapt SectorVector" begin
+            for T in (Float32, ComplexF64)
+                v = TensorKit.SectorVector{T}(undef, V1)
+                rand!(parent(v))
+                v_gpu = @constinferred adapt(CuArray, v)
+                @test v_gpu isa TensorKit.SectorVector{T, I, <:CuArray{T}}
+                @test v_gpu.structure == v.structure
+                v_cpu = @constinferred adapt(Array, v_gpu)
+                @test v_cpu isa TensorKit.SectorVector{T, I, Vector{T}}
+                @test parent(v_cpu) == parent(v)
+                t = CUDA.randn(T, V1 ⊗ V2 ← V3)
+                s = svd_vals(t)
+                s_cpu = adapt(Array, s)
+                @test parent(s_cpu) == collect(parent(s))
+                @test all(c -> block(s_cpu, c) == collect(block(s, c)), blocksectors(s))
+            end
+        end
         @timedtestset "Tensor Dict conversion" begin
             W = V1 ⊗ V2 ← (V3 ⊗ V4 ⊗ V5)'
             for T in (Int, Float32, ComplexF64)

test/tensors/sectorvector.jl

@@ -1,6 +1,7 @@
 using Test, TestExtras
 using TensorKit
 using TensorKit: SectorVector, diagonalblockstructure
+using Adapt: adapt
 
 spacelist = (
     (ℂ^4)',
@@ -29,6 +30,19 @@ spacelist = (
             @test length(v3) == reduceddim(V)
         end
 
+        @timedtestset "Adapt ($T)" begin
+            v = SectorVector{T}(undef, V)
+            rand!(parent(v))
+            w = @testinferred adapt(Array, v)
+            @test w isa SectorVector{T, I, Vector{T}}
+            @test parent(w) == parent(v)
+            @test w.structure == v.structure
+            T′ = T <: Complex ? ComplexF64 : Float64
+            w′ = @testinferred adapt(Array{T′}, v)
+            @test w′ isa SectorVector{T′, I, Vector{T′}}
+            @test parent(w′) ≈ parent(v)
+        end
+
         @timedtestset "AbstractVector interface ($T)" begin
             v = SectorVector{T}(undef, V)
             rand!(parent(v))