[NDTensors] Get more Array storage functionality working

NDTensors/src/NDTensors.jl

@@ -132,11 +132,32 @@ include("empty/adapt.jl")
 
 #####################################
 # Array Tensor (experimental)
-# TODO: Move to `Experimental` module.
 #
-include("arraytensor/arraytensor.jl")
-include("arraytensor/array.jl")
-include("arraytensor/blocksparsearray.jl")
+include("arraystorage/arraystorage/storage/arraystorage.jl")
+include("arraystorage/arraystorage/storage/conj.jl")
+include("arraystorage/arraystorage/storage/permutedims.jl")
+include("arraystorage/arraystorage/storage/contract.jl")
+
+include("arraystorage/arraystorage/tensor/arraystorage.jl")
+include("arraystorage/arraystorage/tensor/zeros.jl")
+include("arraystorage/arraystorage/tensor/indexing.jl")
+include("arraystorage/arraystorage/tensor/permutedims.jl")
+include("arraystorage/arraystorage/tensor/mul.jl")
+include("arraystorage/arraystorage/tensor/contract.jl")
+include("arraystorage/arraystorage/tensor/qr.jl")
+include("arraystorage/arraystorage/tensor/eigen.jl")
+include("arraystorage/arraystorage/tensor/svd.jl")
+
+# DiagonalArray storage
+include("arraystorage/diagonalarray/tensor/contract.jl")
+
+# BlockSparseArray storage
+include("arraystorage/blocksparsearray/storage/contract.jl")
+
+# Combiner storage
+include("arraystorage/combiner/storage/contract.jl")
+
+include("arraystorage/combiner/tensor/contract.jl")
 
 #####################################
 # Deprecations

NDTensors/src/abstractarray/fill.jl

@@ -8,10 +8,10 @@ function generic_randn(
   return randn!(rng, data)
 end
 
-function generic_zeros(arraytype::Type{<:AbstractArray}, dim::Integer=0)
+function generic_zeros(arraytype::Type{<:AbstractArray}, dims...)
   arraytype_specified = set_unspecified_parameters(
     leaf_parenttype(arraytype), DefaultParameters()
   )
   ElT = eltype(arraytype_specified)
-  return fill!(similar(arraytype_specified, dim), zero(ElT))
+  return fill!(similar(arraytype_specified, dims...), zero(ElT))
 end

NDTensors/src/abstractarray/similar.jl

@@ -77,6 +77,11 @@ function similar(array::AbstractArray, eltype::Type, dims::Tuple)
   return NDTensors.similar(similartype(typeof(array), eltype), dims)
 end
 
+# NDTensors.similar
+function similar(array::AbstractArray, eltype::Type, dims::Int)
+  return NDTensors.similar(similartype(typeof(array), eltype), dims)
+end
+
 # NDTensors.similar
 similar(array::AbstractArray, dims::Tuple) = NDTensors.similar(typeof(array), dims)
 

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

@@ -0,0 +1,30 @@
+# Used for dispatch to distinguish from Tensors wrapping TensorStorage.
+# Remove once TensorStorage is removed.
+const ArrayStorage{T,N} = Union{
+  Array{T,N},
+  ReshapedArray{T,N},
+  SubArray{T,N},
+  PermutedDimsArray{T,N},
+  StridedView{T,N},
+  BlockSparseArray{T,N},
+}
+
+const MatrixStorage{T} = Union{
+  ArrayStorage{T,2},
+  Transpose{T},
+  Adjoint{T},
+  Symmetric{T},
+  Hermitian{T},
+  UpperTriangular{T},
+  LowerTriangular{T},
+  UnitUpperTriangular{T},
+  UnitLowerTriangular{T},
+  Diagonal{T},
+}
+
+const MatrixOrArrayStorage{T} = Union{MatrixStorage{T},ArrayStorage{T}}
+
+# TODO: Delete once `Dense` is removed.
+function to_arraystorage(x::DenseTensor)
+  return tensor(reshape(data(x), size(x)), inds(x))
+end

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

@@ -0,0 +1,2 @@
+conj(as::AliasStyle, A::AbstractArray) = conj(A)
+conj(as::AllowAlias, A::Array{<:Real}) = A

NDTensors/src/arraytensor/array.jl → NDTensors/src/arraystorage/arraystorage/storage/contract.jl

@@ -1,6 +1,3 @@
-# Combiner
-promote_rule(::Type{<:Combiner}, arraytype::Type{<:MatrixOrArrayStorage}) = arraytype
-
 # Generic AbstractArray code
 function contract(
   array1::MatrixOrArrayStorage,
@@ -43,26 +40,21 @@ function contraction_output(
 end
 
 # Required interface for specific AbstractArray types
+# TODO: Define `default_α` and `default_β`.
+# TODO: Define this as a `ttgt` or `matricize` backend.
 function contract!(
-  arrayR::MatrixOrArrayStorage,
-  labelsR,
+  array_dest::MatrixOrArrayStorage,
+  labels_dest,
   array1::MatrixOrArrayStorage,
   labels1,
   array2::MatrixOrArrayStorage,
   labels2,
+  α=one(eltype(array_dest)),
+  β=zero(eltype(array_dest));
 )
-  props = ContractionProperties(labels1, labels2, labelsR)
-  compute_contraction_properties!(props, array1, array2, arrayR)
+  props = ContractionProperties(labels1, labels2, labels_dest)
+  compute_contraction_properties!(props, array1, array2, array_dest)
   # TODO: Change this to just `contract!`, or maybe `contract_ttgt!`?
-  _contract!(arrayR, array1, array2, props)
-  return arrayR
-end
-
-function permutedims!(
-  output_array::MatrixOrArrayStorage, array::MatrixOrArrayStorage, perm, f::Function
-)
-  output_array = permutedims!!(
-    leaf_parenttype(output_array), output_array, leaf_parenttype(array), array, perm, f
-  )
-  return output_array
+  _contract!(array_dest, array1, array2, props, α, β)
+  return array_dest
 end

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

@@ -0,0 +1,8 @@
+function permutedims!(
+  output_array::MatrixOrArrayStorage, array::MatrixOrArrayStorage, perm, f::Function
+)
+  output_array = permutedims!!(
+    leaf_parenttype(output_array), output_array, leaf_parenttype(array), array, perm, f
+  )
+  return output_array
+end

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

@@ -0,0 +1,27 @@
+const ArrayStorageTensor{T,N,S,I} = Tensor{T,N,S,I} where {S<:ArrayStorage{T,N}}
+const MatrixStorageTensor{T,S,I} = Tensor{T,2,S,I} where {S<:MatrixStorage{T}}
+const MatrixOrArrayStorageTensor{T,S,I} =
+  Tensor{T,N,S,I} where {N,S<:MatrixOrArrayStorage{T}}
+
+function Tensor(storage::MatrixOrArrayStorageTensor, inds::Tuple)
+  return Tensor(NeverAlias(), storage, inds)
+end
+
+function Tensor(as::AliasStyle, storage::MatrixOrArrayStorage, inds::Tuple)
+  return Tensor{eltype(storage),length(inds),typeof(storage),typeof(inds)}(
+    as, storage, inds
+  )
+end
+
+array(tensor::MatrixOrArrayStorageTensor) = storage(tensor)
+
+# Linear algebra (matrix algebra)
+function Base.adjoint(tens::MatrixStorageTensor)
+  return tensor(adjoint(storage(tens)), reverse(inds(tens)))
+end
+
+# Conversion from a tensor with TensorStorage storage
+# to AbstractArray storage,
+function to_arraytensor(x::DenseTensor)
+  return tensor(reshape(data(x), size(x)), inds(x))
+end

NDTensors/src/arraystorage/arraystorage/tensor/contract.jl

@@ -0,0 +1,31 @@
+# TODO: Just call `contraction_output(storage(tensor1), storage(tensor2), indsR)`
+function contraction_output(
+  tensor1::MatrixOrArrayStorageTensor, tensor2::MatrixOrArrayStorageTensor, indsR
+)
+  tensortypeR = contraction_output_type(typeof(tensor1), typeof(tensor2), indsR)
+  return NDTensors.similar(tensortypeR, indsR)
+end
+
+# TODO: Define `default_α` and `default_β`.
+function contract!(
+  tensor_dest::MatrixOrArrayStorageTensor,
+  labels_dest,
+  tensor1::MatrixOrArrayStorageTensor,
+  labels1,
+  tensor2::MatrixOrArrayStorageTensor,
+  labels2,
+  α=one(eltype(tensor_dest)),
+  β=zero(eltype(tensor_dest));
+)
+  contract!(
+    storage(tensor_dest),
+    labels_dest,
+    storage(tensor1),
+    labels1,
+    storage(tensor2),
+    labels2,
+    α,
+    β,
+  )
+  return tensor_dest
+end

NDTensors/src/arraystorage/arraystorage/tensor/eigen.jl

@@ -0,0 +1,74 @@
+# TODO: Rewrite this function to be more modern:
+# 1. List keyword arguments in function signature.
+# 2. Output `Spectrum` as a keyword argument that gets overwritten.
+# 3. Make this into two layers, one that handles indices and one that works with `AbstractMatrix`.
+function eigen(
+  T::Hermitian{<:Any,<:ArrayStorageTensor};
+  maxdim=nothing,
+  mindim=1,
+  cutoff=nothing,
+  use_absolute_cutoff=false,
+  use_relative_cutoff=true,
+  # These are getting passed erroneously.
+  # TODO: Make sure they don't get passed down
+  # to here.
+  which_decomp=nothing,
+  tags=nothing,
+  eigen_perturbation=nothing,
+  normalize=nothing,
+  ishermitian=nothing,
+  ortho=nothing,
+  svd_alg=nothing,
+)
+  truncate = !isnothing(maxdim) || !isnothing(cutoff)
+  # TODO: Define `default_maxdim(T)`.
+  maxdim = isnothing(maxdim) ? minimum(dims(T)) : maxdim
+  # TODO: Define `default_cutoff(T)`.
+  cutoff = isnothing(cutoff) ? zero(eltype(T)) : cutoff
+
+  matrixT = matrix(T)
+  ## TODO Here I am calling parent to ensure that the correct `any` function
+  ## is envoked for non-cpu matrices
+  if any(!isfinite, parent(matrixT))
+    throw(
+      ArgumentError(
+        "Trying to perform the eigendecomposition of a matrix containing NaNs or Infs"
+      ),
+    )
+  end
+
+  DM, VM = eigen(matrixT)
+
+  # Sort by largest to smallest eigenvalues
+  # TODO: Replace `cpu` with `leaf_parenttype` dispatch.
+  p = sortperm(cpu(DM); rev=true, by=abs)
+  DM = DM[p]
+  VM = VM[:, p]
+
+  if truncate
+    DM, truncerr, _ = truncate!!(
+      DM; mindim, maxdim, cutoff, use_absolute_cutoff, use_relative_cutoff
+    )
+    dD = length(DM)
+    if dD < size(VM, 2)
+      VM = VM[:, 1:dD]
+    end
+  else
+    dD = length(DM)
+    truncerr = 0.0
+  end
+  spec = Spectrum(DM, truncerr)
+
+  # Make the new indices to go onto V
+  # TODO: Put in a separate function, such as
+  # `rewrap_inds` or something like that.
+  indstype = typeof(inds(T))
+  l = eltype(indstype)(dD)
+  r = eltype(indstype)(dD)
+  Vinds = indstype((dag(ind(T, 2)), dag(r)))
+  Dinds = indstype((l, dag(r)))
+  V = tensor(VM, Vinds)
+  # TODO: Replace with `DiagonalArray`.
+  D = tensor(Diag(DM), Dinds)
+  return D, V, spec
+end

NDTensors/src/arraystorage/arraystorage/tensor/indexing.jl

@@ -0,0 +1,8 @@
+function getindex(tensor::MatrixOrArrayStorageTensor, I::Integer...)
+  return storage(tensor)[I...]
+end
+
+function setindex!(tensor::MatrixOrArrayStorageTensor, v, I::Integer...)
+  storage(tensor)[I...] = v
+  return tensor
+end

NDTensors/src/arraystorage/arraystorage/tensor/mul.jl

@@ -0,0 +1,6 @@
+function LinearAlgebra.mul!(
+  C::MatrixStorageTensor, A::MatrixStorageTensor, B::MatrixStorageTensor
+)
+  mul!(storage(C), storage(A), storage(B))
+  return C
+end

NDTensors/src/arraystorage/arraystorage/tensor/permutedims.jl

@@ -0,0 +1,9 @@
+function permutedims!(
+  output_tensor::MatrixOrArrayStorageTensor,
+  tensor::MatrixOrArrayStorageTensor,
+  perm,
+  f::Function,
+)
+  permutedims!(storage(output_tensor), storage(tensor), perm, f)
+  return output_tensor
+end

NDTensors/src/arraystorage/arraystorage/tensor/qr.jl

@@ -0,0 +1,10 @@
+function qr(A::ArrayStorageTensor)
+  Q, R = qr(storage(A))
+  Q = convert(typeof(R), Q)
+  i, j = inds(A)
+  q = size(A, 1) < size(A, 2) ? i : j
+  q = sim(q)
+  Qₜ = tensor(Q, (i, q))
+  Rₜ = tensor(R, (dag(q), j))
+  return Qₜ, Rₜ
+end