Make cuda conversion more general

Author: albertomercurio

ext/QuantumToolboxCUDAExt.jl

@@ -6,6 +6,7 @@ import QuantumToolbox: _sparse_similar, _convert_eltype_wordsize
 import CUDA: cu, CuArray, allowscalar
 import CUDA.CUSPARSE: CuSparseVector, CuSparseMatrixCSC, CuSparseMatrixCSR, AbstractCuSparseArray
 import SparseArrays: SparseVector, SparseMatrixCSC
+import CUDA.Adapt: adapt
 
 allowscalar(false)
 
@@ -81,7 +82,7 @@ function cu(A::QuantumObject; word_size::Union{Val,Int} = Val(64))
 
     return cu(A, makeVal(word_size))
 end
-cu(A::QuantumObject, word_size::Union{Val{32},Val{64}}) = CuArray{_convert_eltype_wordsize(eltype(A), word_size)}(A)
+cu(A::QuantumObject, word_size::Union{Val{32},Val{64}}) = QuantumObject(adapt(CuArray{_convert_eltype_wordsize(eltype(A), word_size)}, A.data), A.type, A.dimensions)
 function cu(
     A::QuantumObject{ObjType,DimsType,<:SparseVector},
     word_size::Union{Val{32},Val{64}},

test/ext-test/gpu/cuda_ext.jl

@@ -66,6 +66,10 @@
     @test typeof(CuSparseMatrixCSR(Xsc).data) == CuSparseMatrixCSR{ComplexF64,Int32}
     @test typeof(CuSparseMatrixCSR{ComplexF32}(Xsc).data) == CuSparseMatrixCSR{ComplexF32,Int32}
 
+    # type conversion of CUDA Diagonal arrays
+    @test cu(qeye(10), word_size=Val(32)).data isa Diagonal{ComplexF32, <:CuVector{ComplexF32}}
+    @test cu(qeye(10), word_size=Val(64)).data isa Diagonal{ComplexF64, <:CuVector{ComplexF64}}
+
     # Sparse To Dense
     # @test to_dense(cu(ψsi; word_size = 64)).data isa CuVector{Int64} # TODO: Fix this in CUDA.jl
     @test to_dense(cu(ψsf; word_size = 64)).data isa CuVector{Float64}