Merge c5b8ff4 into fbf4a1d

Author: mtfishman

NDTensors/src/NDTensors.jl

@@ -19,33 +19,26 @@ using Strided
 using TimerOutputs
 using TupleTools
 
-# TODO: List types, macros, and functions being used.
-include("lib/AlgorithmSelection/src/AlgorithmSelection.jl")
-using .AlgorithmSelection: AlgorithmSelection
-include("lib/BaseExtensions/src/BaseExtensions.jl")
-using .BaseExtensions: BaseExtensions
-include("lib/SetParameters/src/SetParameters.jl")
-using .SetParameters
-include("lib/BroadcastMapConversion/src/BroadcastMapConversion.jl")
-using .BroadcastMapConversion: BroadcastMapConversion
-include("lib/Unwrap/src/Unwrap.jl")
-using .Unwrap
-include("lib/RankFactorization/src/RankFactorization.jl")
-using .RankFactorization: RankFactorization
-include("lib/TensorAlgebra/src/TensorAlgebra.jl")
-using .TensorAlgebra: TensorAlgebra
-include("lib/DiagonalArrays/src/DiagonalArrays.jl")
-using .DiagonalArrays
-include("lib/BlockSparseArrays/src/BlockSparseArrays.jl")
-using .BlockSparseArrays
-include("lib/NamedDimsArrays/src/NamedDimsArrays.jl")
-using .NamedDimsArrays: NamedDimsArrays
-include("lib/SmallVectors/src/SmallVectors.jl")
-using .SmallVectors
-include("lib/SortedSets/src/SortedSets.jl")
-using .SortedSets
-include("lib/TagSets/src/TagSets.jl")
-using .TagSets
+for lib in [
+  :AlgorithmSelection,
+  :BaseExtensions,
+  :SetParameters,
+  :BroadcastMapConversion,
+  :Unwrap,
+  :RankFactorization,
+  :TensorAlgebra,
+  :SparseArrayInterface,
+  :SparseArrayDOKs,
+  :DiagonalArrays,
+  :BlockSparseArrays,
+  :NamedDimsArrays,
+  :SmallVectors,
+  :SortedSets,
+  :TagSets,
+]
+  include("lib/$(lib)/src/$(lib).jl")
+  @eval using .$lib: $lib
+end
 
 using Base: @propagate_inbounds, ReshapedArray, DimOrInd, OneTo
 

NDTensors/src/abstractarray/fill.jl

@@ -1,3 +1,6 @@
+using .SetParameters: DefaultParameters, set_unspecified_parameters
+using .Unwrap: unwrap_type
+
 function generic_randn(
   arraytype::Type{<:AbstractArray}, dim::Integer=0; rng=Random.default_rng()
 )

NDTensors/src/abstractarray/similar.jl

@@ -1,3 +1,5 @@
+using .Unwrap: IsWrappedArray
+
 ## Custom `NDTensors.similar` implementation.
 ## More extensive than `Base.similar`.
 

NDTensors/src/abstractarray/tensoralgebra/contract.jl

@@ -1,4 +1,7 @@
 using LinearAlgebra: BlasFloat
+using .Unwrap: expose
+
+# TODO: Delete these exports
 export backend_auto, backend_blas, backend_generic
 
 @eval struct GemmBackend{T}

NDTensors/src/array/permutedims.jl

@@ -1,4 +1,7 @@
-## Create the Exposed version of Base.permutedims
+using .Unwrap: Exposed, unexpose
+
+# TODO: Move to `Unwrap` module.
+# Create the Exposed version of Base.permutedims
 function permutedims(E::Exposed{<:Array}, perm)
   ## Creating Mperm here to evaluate the permutation and
   ## avoid returning a Stridedview

NDTensors/src/array/set_types.jl

@@ -1,3 +1,5 @@
+using .SetParameters: Position, get_parameter, set_parameters
+
 """
 TODO: Use `Accessors.jl` notation:
 ```julia

NDTensors/src/arraystorage/arraystorage/storage/arraystorage.jl

@@ -1,3 +1,6 @@
+using .BlockSparseArrays: BlockSparseArray
+using .DiagonalArrays: DiagonalArray
+
 # Used for dispatch to distinguish from Tensors wrapping TensorStorage.
 # Remove once TensorStorage is removed.
 const ArrayStorage{T,N} = Union{

NDTensors/src/arraystorage/arraystorage/tensor/svd.jl

@@ -1,3 +1,5 @@
+using .DiagonalArrays: DiagIndices, DiagonalMatrix
+
 backup_svd_alg(::Algorithm"divide_and_conquer") = Algorithm"qr_iteration"()
 backup_svd_alg(::Algorithm"qr_iteration") = Algorithm"recursive"()
 
@@ -111,7 +113,7 @@ function svd(
   # Make the new indices to go onto U and V
   # TODO: Put in a separate function, such as
   # `rewrap_inds` or something like that.
-  dS = length(S[DiagIndices()])
+  dS = length(S[DiagIndices(:)])
   indstype = typeof(inds(T))
   u = eltype(indstype)(dS)
   v = eltype(indstype)(dS)

NDTensors/src/arraystorage/blocksparsearray/storage/contract.jl

@@ -1,3 +1,7 @@
+# TODO: Change to:
+# using .SparseArrayDOKs: SparseArrayDOK
+using .BlockSparseArrays: SparseArray
+
 # TODO: This is inefficient, need to optimize.
 # Look at `contract_labels`, `contract_blocks` and `maybe_contract_blocks!` in:
 # src/blocksparse/contract_utilities.jl

NDTensors/src/imports.jl

@@ -1,3 +1,10 @@
+# Makes `cpu` available as `NDTensors.cpu`.
+# TODO: Define `cpu`, `cu`, etc. in a module `DeviceAbstractions`,
+# similar to:
+# https://github.com/JuliaGPU/KernelAbstractions.jl
+# https://github.com/oschulz/HeterogeneousComputing.jl
+using .Unwrap: cpu
+
 import Base:
   # Types
   AbstractFloat,