Merge branch 'main' into ITensors_qnindex_docs

mtfishman · web-flow · commit d1dd84c2ed2b · 2025-03-20T17:42:28.000-04:00
diff --git a/NDTensors/Project.toml b/NDTensors/Project.toml
@@ -1,7 +1,7 @@
 name = "NDTensors"
 uuid = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 authors = ["Matthew Fishman <mfishman@flatironinstitute.org>"]
-version = "0.4.0"
+version = "0.4.4"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -90,7 +90,7 @@ StridedViews = "0.2.2, 0.3"
 TBLIS = "0.2"
 TimerOutputs = "0.5.5"
 TupleTools = "1.2.0"
-TypeParameterAccessors = "0.2"
+TypeParameterAccessors = "0.3"
 VectorInterface = "0.4.2, 0.5"
 cuTENSOR = "2"
 julia = "1.10"
diff --git a/NDTensors/ext/NDTensorsAMDGPUExt/set_types.jl b/NDTensors/ext/NDTensorsAMDGPUExt/set_types.jl
@@ -1,11 +1,5 @@
-# TypeParameterAccessors definitions
-using NDTensors.TypeParameterAccessors:
-  TypeParameterAccessors, Position, default_type_parameters
+using AMDGPU: ROCArray
 using NDTensors.GPUArraysCoreExtensions: storagemode
-using AMDGPU: AMDGPU, ROCArray
-
-function TypeParameterAccessors.default_type_parameters(::Type{<:ROCArray})
-  return (default_type_parameters(AbstractArray)..., AMDGPU.Mem.HIPBuffer)
-end
+using NDTensors.TypeParameterAccessors: TypeParameterAccessors, Position
 
 TypeParameterAccessors.position(::Type{<:ROCArray}, ::typeof(storagemode)) = Position(3)
diff --git a/NDTensors/ext/NDTensorsCUDAExt/set_types.jl b/NDTensors/ext/NDTensorsCUDAExt/set_types.jl
@@ -1,13 +1,7 @@
-# TypeParameterAccessors definitions
-using CUDA: CUDA, CuArray
-using NDTensors.TypeParameterAccessors:
-  TypeParameterAccessors, Position, default_type_parameters
+using CUDA: CuArray
 using NDTensors.GPUArraysCoreExtensions: storagemode
+using NDTensors.TypeParameterAccessors: TypeParameterAccessors, Position
 
 function TypeParameterAccessors.position(::Type{<:CuArray}, ::typeof(storagemode))
   return Position(3)
 end
-
-function TypeParameterAccessors.default_type_parameters(::Type{<:CuArray})
-  return (default_type_parameters(AbstractArray)..., CUDA.Mem.DeviceBuffer)
-end
diff --git a/NDTensors/ext/NDTensorsMetalExt/set_types.jl b/NDTensors/ext/NDTensorsMetalExt/set_types.jl
@@ -1,13 +1,7 @@
-using Metal: Metal, MtlArray
-# `TypeParameterAccessors.jl` definitions.
-
-using NDTensors.TypeParameterAccessors: TypeParameterAccessors, Position
+using Metal: MtlArray
 using NDTensors.GPUArraysCoreExtensions: storagemode
+using NDTensors.TypeParameterAccessors: TypeParameterAccessors, Position
 
 function TypeParameterAccessors.position(::Type{<:MtlArray}, ::typeof(storagemode))
   return Position(3)
 end
-
-function TypeParameterAccessors.default_type_parameters(::Type{<:MtlArray})
-  return (Float32, 1, Metal.DefaultStorageMode)
-end
diff --git a/NDTensors/src/blocksparse/block.jl b/NDTensors/src/blocksparse/block.jl
@@ -75,6 +75,7 @@ sethash!(b::Block, h::UInt) = (b.hash[] = h; return b)
 #
 
 length(::Block{N}) where {N} = N
+length(::Type{<:Block{N}}) where {N} = N
 
 isless(b1::Block, b2::Block) = isless(Tuple(b1), Tuple(b2))
 
diff --git a/NDTensors/src/blocksparse/blockoffsets.jl b/NDTensors/src/blocksparse/blockoffsets.jl
@@ -12,10 +12,6 @@ const BlockOffsets{N} = Dictionary{Block{N},Int}
 
 BlockOffset(block::Block{N}, offset::Int) where {N} = BlockOffset{N}(block, offset)
 
-Base.ndims(::Blocks{N}) where {N} = N
-Base.ndims(::BlockOffset{N}) where {N} = N
-Base.ndims(::BlockOffsets{N}) where {N} = N
-
 blocktype(bofs::BlockOffsets) = keytype(bofs)
 
 nzblock(bof::BlockOffset) = first(bof)
diff --git a/NDTensors/src/blocksparse/contract_generic.jl b/NDTensors/src/blocksparse/contract_generic.jl
@@ -11,8 +11,8 @@ function contract_blockoffsets(
   indsR,
   labelsR,
 )
-  N1 = ndims(boffs1)
-  N2 = ndims(boffs2)
+  N1 = length(blocktype(boffs1))
+  N2 = length(blocktype(boffs2))
   NR = length(labelsR)
   ValNR = ValLength(labelsR)
   labels1_to_labels2, labels1_to_labelsR, labels2_to_labelsR = contract_labels(
diff --git a/NDTensors/src/blocksparse/contract_sequential.jl b/NDTensors/src/blocksparse/contract_sequential.jl
@@ -9,8 +9,8 @@ function contract_blockoffsets(
   indsR,
   labelsR,
 )
-  N1 = ndims(boffs1)
-  N2 = ndims(boffs2)
+  N1 = length(blocktype(boffs1))
+  N2 = length(blocktype(boffs2))
   NR = length(labelsR)
   ValNR = ValLength(labelsR)
   labels1_to_labels2, labels1_to_labelsR, labels2_to_labelsR = contract_labels(
diff --git a/NDTensors/src/blocksparse/diagblocksparse.jl b/NDTensors/src/blocksparse/diagblocksparse.jl
@@ -1,3 +1,4 @@
+using LinearAlgebra: LinearAlgebra
 using TypeParameterAccessors: similartype
 
 export DiagBlockSparse, DiagBlockSparseTensor
@@ -448,22 +449,16 @@ function dense(
 end
 
 # convert to Dense
-function dense(T::TensorT) where {TensorT<:DiagBlockSparseTensor}
-  R = zeros(dense(TensorT), inds(T))
-  for i in 1:diaglength(T)
-    setdiagindex!(R, getdiagindex(T, i), i)
-  end
-  return R
+function dense(T::DiagBlockSparseTensor)
+  return dense(denseblocks(T))
 end
 
 # convert to BlockSparse
 function denseblocks(D::Tensor)
   nzblocksD = nzblocks(D)
-  T = BlockSparseTensor(eltype(D), nzblocksD, inds(D))
+  T = BlockSparseTensor(datatype(D), nzblocksD, inds(D))
   for b in nzblocksD
-    for n in 1:diaglength(D)
-      setdiagindex!(T, getdiagindex(D, n), n)
-    end
+    T[b] = D[b]
   end
   return T
 end
@@ -588,8 +583,13 @@ function _contract!!(
   return R
 end
 
-# TODO: Improve this with FillArrays.jl
-norm(S::UniformDiagBlockSparseTensor) = sqrt(mindim(S) * abs2(data(S)))
+function LinearAlgebra.norm(D::UniformDiagBlockSparseTensor)
+  normD² = zero(eltype(D))
+  for b in nzblocks(D)
+    normD² += norm(D[b])^2
+  end
+  return √(abs(normD²))
+end
 
 function contraction_output(
   T1::TensorT1, labelsT1, T2::TensorT2, labelsT2, labelsR
diff --git a/NDTensors/src/dense/dense.jl b/NDTensors/src/dense/dense.jl
@@ -105,6 +105,11 @@ function copy(D::Dense)
   return Dense(copy(expose(data(D))))
 end
 
+function Base.copyto!(R::Dense, T::Dense)
+  copyto!(expose(data(R)), expose(data(T)))
+  return R
+end
+
 function Base.real(T::Type{<:Dense})
   return set_datatype(T, similartype(datatype(T), real(eltype(T))))
 end
diff --git a/NDTensors/src/dense/densetensor.jl b/NDTensors/src/dense/densetensor.jl
@@ -66,6 +66,11 @@ end
 
 convert(::Type{Array}, T::DenseTensor) = reshape(data(storage(T)), dims(inds(T)))
 
+function Base.copyto!(R::DenseTensor, T::DenseTensor)
+  copyto!(storage(R), storage(T))
+  return R
+end
+
 # Create an Array that is a view of the Dense Tensor
 # Useful for using Base Array functions
 array(T::DenseTensor) = convert(Array, T)
diff --git a/NDTensors/src/diag/diagtensor.jl b/NDTensors/src/diag/diagtensor.jl
@@ -70,6 +70,11 @@ Set the entire diagonal of a uniform DiagTensor.
 """
 setdiag(T::UniformDiagTensor, val) = tensor(Diag(val), inds(T))
 
+function Base.copyto!(R::DenseTensor, T::DiagTensor)
+  diagview(R) .= diagview(T)
+  return R
+end
+
 @propagate_inbounds function getindex(
   T::DiagTensor{ElT,N}, inds::Vararg{Int,N}
 ) where {ElT,N}
diff --git a/NDTensors/src/tensor/tensor.jl b/NDTensors/src/tensor/tensor.jl
@@ -204,7 +204,9 @@ end
 
 copy(T::Tensor) = setstorage(T, copy(storage(T)))
 
-copyto!(R::Tensor, T::Tensor) = (copyto!(storage(R), storage(T)); R)
+function copyto!(R::Tensor, T::Tensor)
+  return error("Not implemented.")
+end
 
 complex(T::Tensor) = setstorage(T, complex(storage(T)))
 
diff --git a/NDTensors/src/tensorstorage/tensorstorage.jl b/NDTensors/src/tensorstorage/tensorstorage.jl
@@ -62,9 +62,8 @@ Base.real(S::TensorStorage) = setdata(S, real(data(S)))
 
 Base.imag(S::TensorStorage) = setdata(S, imag(data(S)))
 
-function copyto!(S1::TensorStorage, S2::TensorStorage)
-  copyto!(expose(data(S1)), expose(data(S2)))
-  return S1
+function Base.copyto!(S1::TensorStorage, S2::TensorStorage)
+  return error("Not implemented.")
 end
 
 Random.randn!(S::TensorStorage) = randn!(Random.default_rng(), S)
diff --git a/NDTensors/test/test_diagblocksparse.jl b/NDTensors/test/test_diagblocksparse.jl
@@ -1,6 +1,7 @@
 @eval module $(gensym())
 using Dictionaries: Dictionary
 using GPUArraysCore: @allowscalar
+using LinearAlgebra: norm
 using NDTensors:
   NDTensors,
   Block,
@@ -11,6 +12,7 @@ using NDTensors:
   blockoffsets,
   contract,
   dense,
+  denseblocks,
   inds,
   nzblocks
 using Random: randn!
@@ -78,11 +80,44 @@ using .NDTensorsTestUtils: devices_list
   A = BlockSparseTensor{elt}([(1, 1), (2, 2)], [3, 2, 3], [2, 2])
   randn!(A)
   t = Tensor(DiagBlockSparse(one(elt), blockoffsets(A)), inds(A))
-  @test_broken dense(contract(A, (1, -2), (t), (3, -2))) ≈
+  @test dense(contract(A, (1, -2), (t), (3, -2))) ≈
     contract(dense(A), (1, -2), dense(t), (3, -2))
-  @test_broken dense(contract(A, (-2, 1), t, (-2, 3))) ≈
+  @test dense(contract(A, (-2, 1), t, (-2, 3))) ≈
     contract(dense(A), (-2, 1), dense(t), (-2, 3))
-  @test_broken contract(dev(A), (-1, -2), dev(t), (-1, -2))[] ≈
+  @test contract(dev(A), (-1, -2), dev(t), (-1, -2))[] ≈
     contract(dense(A), (-1, -2), dense(t), (-1, -2))[]
 end
+
+@testset "UniformDiagBlockSparse norm" begin
+  elt = Float64
+  storage = DiagBlockSparse(one(elt), Dictionary([Block(1, 1), Block(2, 2)], [0, 2]))
+  tensor = Tensor(storage, ([2, 2], [2, 2]))
+  @test norm(tensor) ≈ norm(dense(tensor))
+
+  elt = Float64
+  storage = DiagBlockSparse(one(elt), Dictionary([Block(1, 1)], [0]))
+  tensor = Tensor(storage, ([2], [1, 1]))
+  @test norm(tensor) ≈ norm(dense(tensor))
+end
+
+@testset "DiagBlockSparse denseblocks" begin
+  elt = Float64
+  blockoffsets_a = Dictionary([Block(1, 1), Block(2, 2)], [0, 2])
+  inds_a = ([2, 2], [2, 2])
+  a = Tensor(DiagBlockSparse(elt, blockoffsets_a, 4), inds_a)
+  a[Block(1, 1)][1, 1] = 1
+  a[Block(1, 1)][2, 2] = 2
+  a[Block(2, 2)][1, 1] = 3
+  a[Block(2, 2)][2, 2] = 4
+  a′ = denseblocks(a)
+  @test dense(a) == dense(a′)
+
+  elt = Float64
+  blockoffsets_a = Dictionary([Block(1, 1)], [0])
+  inds_a = ([2], [1, 1])
+  a = Tensor(DiagBlockSparse(one(elt), blockoffsets_a), inds_a)
+  a′ = denseblocks(a)
+  @test dense(a) == dense(a′)
+end
+
 end
diff --git a/docs/src/IncludedSiteTypes.md b/docs/src/IncludedSiteTypes.md
@@ -149,7 +149,7 @@ sites = siteinds("S=1",N; conserve_sz=true, qnname_sz="TotalSz")
 The available state names for "S=1" sites are:
 - `"Up"` (aliases: `"Z+"`, `"↑"`) spin in the up state
 - `"Z0"` (aliases: `"0"`) spin in the Sz=0 state
-- `"Dn"` (aliases: `"Z-"`, `"↓"`) spin in the Sz=0 state
+- `"Dn"` (aliases: `"Z-"`, `"↓"`) spin in the down state
 
 #### "S=1" Operators
 
diff --git a/docs/src/index.md b/docs/src/index.md
@@ -29,7 +29,9 @@ Development of ITensor is supported by the Flatiron Institute, a division of the
 
 ## News
 
-- February 3, 2025: ITensors.jl v0.8 has been released. This release should not be breaking to the average user using documented features of the library. This removes internal submodules that held experimental code for rewriting the internals of NDTensors.jl/ITensors.jl, which have now been turned into separate packages for future development. It is marked as breaking since ITensorMPS.jl was making use of some of that experimental code, and will be updated accordingly. Also note that it fixes an issue that existed in some more recent versions of NDTensors.jl v0.3/ITensors.jl v0.7 where loading ITensors.jl in combination with some packages like LinearMaps.jl caused very long load/compile times (https://itensor.discourse.group/t/linearmaps-and-itensors-incompatibility/2216), so if you are seeing that issue when using ITensors.jl v0.7 you should upgrade to this version.
+- February 22, 2025: Please note that there were issues installing the latest version of ITensors.jl (ITensors.jl v0.8) in older versions of Julia v1.10 and v1.11 ([https://github.com/ITensor/ITensors.jl/issues/1618](https://github.com/ITensor/ITensors.jl/issues/1618), [https://itensor.discourse.group/t/typeparameteraccessors-not-found-error-on-julia-v-1-10-0/2260](https://itensor.discourse.group/t/typeparameteraccessors-not-found-error-on-julia-v-1-10-0/2260)). This issue has been fixed in [NDTensors.jl v0.4.4](https://github.com/ITensor/ITensors.jl/pull/1623), so please try updating your packages if you are using older versions of Julia v1.10 or v1.11 and running into issues installing ITensors.jl.
+
+- February 3, 2025: ITensors.jl v0.8 has been released. This release should not be breaking to the average user using documented features of the library. This removes internal submodules that held experimental code for rewriting the internals of NDTensors.jl/ITensors.jl, which have now been turned into separate packages for future development. It is marked as breaking since ITensorMPS.jl was making use of some of that experimental code, and will be updated accordingly. Also note that it fixes an issue that existed in some more recent versions of NDTensors.jl v0.3/ITensors.jl v0.7 where loading ITensors.jl in combination with some packages like LinearMaps.jl caused very long load/compile times ([https://itensor.discourse.group/t/linearmaps-and-itensors-incompatibility/2216](https://itensor.discourse.group/t/linearmaps-and-itensors-incompatibility/2216)), so if you are seeing that issue when using ITensors.jl v0.7 you should upgrade to this version.
 
 - October 25, 2024: ITensors.jl v0.7 has been released. This is a major breaking change, since all of the MPS/MPO functionality from this package has been moved to [ITensorMPS.jl](https://github.com/ITensor/ITensorMPS.jl), along with all of the functionality of [ITensorTDVP.jl](https://github.com/ITensor/ITensorTDVP.jl). If you want to use MPS/MPO types and related functionality, such as `MPS`, `MPO`, `dmrg`, `siteinds`, `OpSum`, `op`, etc. you now must install and load the ITensorMPS.jl package. Additionally, if you are using ITensorTDVP.jl in your code, please change `using ITensorTDVP` to `using ITensorMPS`. ITensorMPS.jl has all of the same functionality as ITensorTDVP.jl, and ITensorTDVP.jl will be deprecated in favor of ITensorMPS.jl. **Note:** If you are using `ITensors.compile`, you must now install and load the ITensorMPS.jl package in order to trigger it to load properly, since it relies on running MPS/MPO functionality as example code for Julia to compile.
 
diff --git a/src/lib/SiteTypes/src/sitetype.jl b/src/lib/SiteTypes/src/sitetype.jl
@@ -34,7 +34,7 @@ There are currently a few built-in site types
 recognized by `jl`. The system is easily extensible
 by users. To add new operators to an existing site type,
 or to create new site types, you can follow the instructions
-[here](https://itensor.github.io/jl/stable/examples/Physics.html).
+[here](https://itensor.github.io/ITensors.jl/stable/examples/Physics.html).
 
 The current built-in site types are:
 
@@ -106,8 +106,8 @@ Many operators are available, for example:
    `"Cdagup"`, `"Cdn"`, `"Cdagdn"`, `"Sz"`, `"Sx"`, `"Sy"`, `"S+"`, `"S-"`, ...
 - ...
 
-You can view the source code for the internal SiteType definitions
-and operators that are defined [here](https://github.com/ITensor/jl/tree/main/src/physics/site_types).
+You can view the internal SiteType definitions and operators
+[here](https://itensor.github.io/ITensors.jl/stable/IncludedSiteTypes.html).
 """
 SiteType(s::AbstractString) = SiteType{SmallString(s)}()
 
@@ -228,9 +228,9 @@ s = Index(2, "Site,S=1/2")
 Sz = op("Sz", s)
 ```
 
-To see all of the operator names defined for the site types included with
-ITensor, please view the [source code](https://github.com/ITensor/jl/tree/main/src/physics/site_types)
-for each site type. Note that some site types such as "S=1/2" and "Qubit"
+You can see all of the operator names defined for the site types included
+with ITensor [here](https://itensor.github.io/ITensors.jl/dev/IncludedSiteTypes.html).
+Note that some site types such as "S=1/2" and "Qubit"
 are aliases for each other and share operator definitions.
 """
 function op(name::AbstractString, s::Index...; adjoint::Bool=false, kwargs...)

Original file line number	Diff line number	Diff line change
`@@ -75,6 +75,7 @@ sethash!(b::Block, h::UInt) = (b.hash[] = h; return b)`
`75`	`75`	`#`
`76`	`76`
`77`	`77`	`length(::Block{N}) where {N} = N`
	`78`	`+length(::Type{<:Block{N}}) where {N} = N`
`78`	`79`
`79`	`80`	`isless(b1::Block, b2::Block) = isless(Tuple(b1), Tuple(b2))`
`80`	`81`