Even more fixes

Author: kshyatt

ext/TensorKitCUDAExt/TensorKitCUDAExt.jl

@@ -1,5 +1,7 @@
 module TensorKitCUDAExt
 
+using LinearAlgebra
+
 using CUDA
 using CUDA: @allowscalar
 using CUDA.CUBLAS # for LinearAlgebra tie-ins
@@ -13,7 +15,6 @@ using TensorKit: SectorDict, tensormaptype, scalar, similarstoragetype
 using TensorKit.MatrixAlgebraKit
 
 using Random
-using LinearAlgebra
 
 include("cutensormap.jl")
 

ext/TensorKitCUDAExt/cutensormap.jl

@@ -3,7 +3,7 @@ const CuTensor{T, S, N, A<:CuVector{T}} = CuTensorMap{T, S, N, 0, A}
 
 function TensorKit.tensormaptype(S::Type{<:IndexSpace}, N₁, N₂, TorA::Type{<:StridedCuArray})
     if TorA <: CuArray
-        return TensorMap{eltype(TorA),S,N₁,N₂,TorA}
+        return TensorMap{eltype(TorA),S,N₁,N₂,CuVector{eltype(TorA)}}
     else
         throw(ArgumentError("argument $TorA should specify a scalar type (`<:Number`) or a storage type `<:CuVector{<:Number}`"))
     end

src/tensors/linalg.jl

@@ -277,7 +277,7 @@ function _norm(blockiter, p::Real, init::Real)
         end
     elseif p > 0
         nᵖ = mapreduce(+, blockiter; init=init) do (c, b)
-            return isempty(b) ? init : oftype(init, dim(c) * LinearAlgebra.normp(b, p)^p)
+            return isempty(b) ? init : oftype(init, dim(c) * norm(b, p)^p)
         end
         return (nᵖ)^inv(oftype(nᵖ, p))
     else