Update usings

mtfishman · mtfishman · commit 40dc0a348cd5 · 2025-10-10T21:12:23.000-04:00
diff --git a/NDTensors/Project.toml b/NDTensors/Project.toml
@@ -28,7 +28,6 @@ Strided = "5e0ebb24-38b0-5f93-81fe-25c709ecae67"
 StridedViews = "4db3bf67-4bd7-4b4e-b153-31dc3fb37143"
 TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 TupleTools = "9d95972d-f1c8-5527-a6e0-b4b365fa01f6"
-TypeParameterAccessors = "7e5a90cf-f82e-492e-a09b-e3e26432c138"
 VectorInterface = "409d34a3-91d5-4945-b6ec-7529ddf182d8"
 
 [weakdeps]
@@ -88,7 +87,6 @@ StridedViews = "0.2.2, 0.3, 0.4"
 TBLIS = "0.2"
 TimerOutputs = "0.5.5"
 TupleTools = "1.2.0"
-TypeParameterAccessors = "0.3"
 VectorInterface = "0.4.2, 0.5"
 cuTENSOR = "2"
 julia = "1.10"
diff --git a/NDTensors/src/abstractarray/generic_array_constructors.jl b/NDTensors/src/abstractarray/generic_array_constructors.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors:
+using .Vendored.TypeParameterAccessors:
     unwrap_array_type,
     specify_default_type_parameters,
     specify_type_parameters,
diff --git a/NDTensors/src/abstractarray/iscu.jl b/NDTensors/src/abstractarray/iscu.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 # TODO: Make `isgpu`, `ismtl`, etc.
 # For `isgpu`, will require a `NDTensorsGPUArrayCoreExt`.
 iscu(A::AbstractArray) = iscu(typeof(A))
diff --git a/NDTensors/src/abstractarray/set_types.jl b/NDTensors/src/abstractarray/set_types.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 
 """
 # Do we still want to define things like this?
diff --git a/NDTensors/src/abstractarray/similar.jl b/NDTensors/src/abstractarray/similar.jl
@@ -1,5 +1,5 @@
 using Base: DimOrInd, Dims, OneTo
-using TypeParameterAccessors: IsWrappedArray, unwrap_array_type, set_eltype, similartype
+using .Vendored.TypeParameterAccessors: IsWrappedArray, unwrap_array_type, set_eltype, similartype
 
 ## Custom `NDTensors.similar` implementation.
 ## More extensive than `Base.similar`.
diff --git a/NDTensors/src/adapt.jl b/NDTensors/src/adapt.jl
@@ -27,7 +27,7 @@ double_precision(x) = fmap(x -> adapt(double_precision(eltype(x)), x), x)
 # Used to adapt `EmptyStorage` types
 #
 
-using TypeParameterAccessors: specify_type_parameters
+using .Vendored.TypeParameterAccessors: specify_type_parameters
 function adapt_storagetype(to::Type{<:AbstractVector}, x::Type{<:TensorStorage})
     return set_datatype(x, specify_type_parameters(to, eltype, eltype(x)))
 end
diff --git a/NDTensors/src/blocksparse/blockdims.jl b/NDTensors/src/blocksparse/blockdims.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 
 """
     BlockDim
diff --git a/NDTensors/src/blocksparse/blocksparsetensor.jl b/NDTensors/src/blocksparse/blocksparsetensor.jl
@@ -1,5 +1,5 @@
 using SparseArrays: nnz
-using TypeParameterAccessors: similartype
+using .Vendored.TypeParameterAccessors: similartype
 
 #
 # BlockSparseTensor (Tensor using BlockSparse storage)
@@ -258,7 +258,7 @@ end
 # Defaults to adding zeros.
 # Returns the offset of the new block added.
 # XXX rename to insertblock!, no need to return offset
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 using .Expose: Exposed, expose, unexpose
 function insertblock_offset!(T::BlockSparseTensor{ElT, N}, newblock::Block{N}) where {ElT, N}
     newdim = blockdim(T, newblock)
@@ -792,7 +792,7 @@ end
 # <fermions>
 permfactor(perm, block, inds) = 1
 
-using TypeParameterAccessors: set_type_parameters, parenttype
+using .Vendored.TypeParameterAccessors: set_type_parameters, parenttype
 function permutedims!(
         R::BlockSparseTensor{<:Number, N},
         T::BlockSparseTensor{<:Number, N},
diff --git a/NDTensors/src/blocksparse/diagblocksparse.jl b/NDTensors/src/blocksparse/diagblocksparse.jl
@@ -1,5 +1,5 @@
 using LinearAlgebra: LinearAlgebra
-using TypeParameterAccessors: similartype
+using .Vendored.TypeParameterAccessors: similartype
 
 export DiagBlockSparse, DiagBlockSparseTensor
 
diff --git a/NDTensors/src/blocksparse/linearalgebra.jl b/NDTensors/src/blocksparse/linearalgebra.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 using .Expose: expose
 const BlockSparseMatrix{ElT, StoreT, IndsT} = BlockSparseTensor{ElT, 2, StoreT, IndsT}
 const DiagBlockSparseMatrix{ElT, StoreT, IndsT} = DiagBlockSparseTensor{ElT, 2, StoreT, IndsT}
diff --git a/NDTensors/src/blocksparse/similar.jl b/NDTensors/src/blocksparse/similar.jl
@@ -1,5 +1,5 @@
 using SparseArrays: nnz
-using TypeParameterAccessors: similartype
+using .Vendored.TypeParameterAccessors: similartype
 
 # NDTensors.similar
 function similar(storagetype::Type{<:BlockSparse}, blockoffsets::BlockOffsets, dims::Tuple)
diff --git a/NDTensors/src/default_kwargs.jl b/NDTensors/src/default_kwargs.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 replace_nothing(::Nothing, replacement) = replacement
 replace_nothing(value, replacement) = value
 
diff --git a/NDTensors/src/dense/dense.jl b/NDTensors/src/dense/dense.jl
@@ -124,7 +124,7 @@ dense(storagetype::Type{<:Dense}) = storagetype
 # TODO: make these more general, move to tensorstorage.jl
 datatype(storetype::Type{<:Dense{<:Any, DataT}}) where {DataT} = DataT
 
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 function promote_rule(
         ::Type{<:Dense{ElT1, DataT1}}, ::Type{<:Dense{ElT2, DataT2}}
     ) where {ElT1, DataT1, ElT2, DataT2}
diff --git a/NDTensors/src/dense/generic_array_constructors.jl b/NDTensors/src/dense/generic_array_constructors.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors:
+using .Vendored.TypeParameterAccessors:
     default_type_parameters,
     parenttype,
     set_eltype,
diff --git a/NDTensors/src/dense/set_types.jl b/NDTensors/src/dense/set_types.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, Position, parenttype
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, Position, parenttype
 
 function set_datatype(storagetype::Type{<:Dense}, datatype::Type{<:AbstractVector})
     return Dense{eltype(datatype), datatype}
diff --git a/NDTensors/src/diag/diagtensor.jl b/NDTensors/src/diag/diagtensor.jl
@@ -113,7 +113,7 @@ function dense(::Type{<:Tensor{ElT, N, StoreT, IndsT}}) where {ElT, N, StoreT <:
     return Tensor{ElT, N, dense(StoreT), IndsT}
 end
 
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 # convert to Dense
 function dense(T::DiagTensor)
     R = zeros(dense(typeof(T)), inds(T))
diff --git a/NDTensors/src/diag/set_types.jl b/NDTensors/src/diag/set_types.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 
 function TypeParameterAccessors.set_eltype(storagetype::Type{<:UniformDiag}, eltype::Type)
     return Diag{eltype, eltype}
diff --git a/NDTensors/src/diag/similar.jl b/NDTensors/src/diag/similar.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 
 # NDTensors.similar
 function similar(storagetype::Type{<:Diag}, dims::Dims)
diff --git a/NDTensors/src/dims.jl b/NDTensors/src/dims.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 
 export dense, dims, dim, mindim, diaglength
 
diff --git a/NDTensors/src/empty/empty.jl b/NDTensors/src/empty/empty.jl
@@ -1,5 +1,5 @@
 using SparseArrays: SparseArrays
-using TypeParameterAccessors: TypeParameterAccessors, set_eltype, similartype
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, set_eltype, similartype
 
 #
 # Represents a tensor order that could be set to any order.
@@ -95,6 +95,6 @@ function Base.show(io::IO, mime::MIME"text/plain", S::EmptyStorage)
     return println(io, typeof(S))
 end
 
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 TypeParameterAccessors.parenttype(empty::Type{<:EmptyStorage}) = storagetype(empty)
 zero(empty::EmptyStorage) = empty
diff --git a/NDTensors/src/lib/AMDGPUExtensions/src/roc.jl b/NDTensors/src/lib/AMDGPUExtensions/src/roc.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, Position
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, Position
 using ..GPUArraysCoreExtensions: storagemode
 # Implemented in NDTensorsAMDGPUExt
 function roc end
diff --git a/NDTensors/src/lib/CUDAExtensions/src/cuda.jl b/NDTensors/src/lib/CUDAExtensions/src/cuda.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, Position
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, Position
 using ..GPUArraysCoreExtensions: storagemode
 # Implemented in NDTensorsCUDAExt
 function cu end
diff --git a/NDTensors/src/lib/Expose/src/exposed.jl b/NDTensors/src/lib/Expose/src/exposed.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors:
+using .Vendored.TypeParameterAccessors:
     TypeParameterAccessors, unwrap_array_type, parenttype, type_parameters
 struct Exposed{Unwrapped, Object}
     object::Object
diff --git a/NDTensors/src/lib/GPUArraysCoreExtensions/src/gpuarrayscore.jl b/NDTensors/src/lib/GPUArraysCoreExtensions/src/gpuarrayscore.jl
@@ -1,5 +1,5 @@
 using ..Expose: Exposed, unexpose
-using TypeParameterAccessors: TypeParameterAccessors, type_parameters, set_type_parameters
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, type_parameters, set_type_parameters
 
 function storagemode(object)
     return storagemode(typeof(object))
diff --git a/NDTensors/src/lib/MetalExtensions/src/metal.jl b/NDTensors/src/lib/MetalExtensions/src/metal.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, Position
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, Position
 using ..GPUArraysCoreExtensions: storagemode
 # Implemented in NDTensorsMetalExt
 function mtl end
diff --git a/NDTensors/src/lib/RankFactorization/src/default_kwargs.jl b/NDTensors/src/lib/RankFactorization/src/default_kwargs.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 replace_nothing(::Nothing, replacement) = replacement
 replace_nothing(value, replacement) = value
 
diff --git a/NDTensors/src/lib/RankFactorization/src/truncate_spectrum.jl b/NDTensors/src/lib/RankFactorization/src/truncate_spectrum.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 
 ## TODO write Exposed version of truncate
 function truncate!!(P::AbstractArray; kwargs...)
diff --git a/NDTensors/src/linearalgebra/linearalgebra.jl b/NDTensors/src/linearalgebra/linearalgebra.jl
@@ -387,7 +387,7 @@ function qr_positive(M::AbstractMatrix)
     return (Q, R)
 end
 
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 """
     ql_positive(M::AbstractMatrix)
 
diff --git a/NDTensors/src/linearalgebra/svd.jl b/NDTensors/src/linearalgebra/svd.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 # The state of the `svd_recursive` algorithm.
 function svd_recursive_state(S::AbstractArray, thresh::Float64)
     return svd_recursive_state(unwrap_array_type(S), S, thresh)
diff --git a/NDTensors/src/tensor/set_types.jl b/NDTensors/src/tensor/set_types.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, Position, parenttype
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, Position, parenttype
 function TypeParameterAccessors.set_ndims(arraytype::Type{<:Tensor}, ndims)
     # TODO: Implement something like:
     # ```julia
diff --git a/NDTensors/src/tensor/similar.jl b/NDTensors/src/tensor/similar.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, set_indstype, similartype
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, set_indstype, similartype
 
 # NDTensors.similar
 similar(tensor::Tensor) = setstorage(tensor, similar(storage(tensor)))
diff --git a/NDTensors/src/tensorstorage/default_storage.jl b/NDTensors/src/tensorstorage/default_storage.jl
@@ -3,7 +3,7 @@
 default_datatype(eltype::Type = default_eltype()) = Vector{eltype}
 default_eltype() = Float64
 
-using TypeParameterAccessors: specify_default_type_parameters
+using .Vendored.TypeParameterAccessors: specify_default_type_parameters
 ## TODO use multiple dispace to make this pick between dense and blocksparse
 function default_storagetype(datatype::Type{<:AbstractArray}, inds::Tuple)
     datatype = specify_default_type_parameters(datatype)
diff --git a/NDTensors/src/tensorstorage/set_types.jl b/NDTensors/src/tensorstorage/set_types.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors
 function TypeParameterAccessors.set_ndims(arraytype::Type{<:TensorStorage}, ndims::Int)
     # TODO: Change to this once `TensorStorage` types support wrapping
     # non-AbstractVector types.
diff --git a/NDTensors/src/tensorstorage/similar.jl b/NDTensors/src/tensorstorage/similar.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: TypeParameterAccessors, set_ndims, similartype
+using .Vendored.TypeParameterAccessors: TypeParameterAccessors, set_ndims, similartype
 
 # NDTensors.similar
 similar(storage::TensorStorage) = setdata(storage, NDTensors.similar(data(storage)))
diff --git a/NDTensors/src/truncate.jl b/NDTensors/src/truncate.jl
@@ -1,4 +1,4 @@
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 ## TODO write Exposed version of truncate
 function truncate!!(P::AbstractArray; kwargs...)
     return truncate!!(unwrap_array_type(P), P; kwargs...)
@@ -10,7 +10,7 @@ function truncate!!(::Type{<:Array}, P::AbstractArray; kwargs...)
     return P, truncerr, docut
 end
 
-using TypeParameterAccessors: unwrap_array_type
+using .Vendored.TypeParameterAccessors: unwrap_array_type
 # GPU fallback version, convert to CPU.
 function truncate!!(::Type{<:AbstractArray}, P::AbstractArray; kwargs...)
     P_cpu = cpu(P)

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-using TypeParameterAccessors:`
	`1`	`+using .Vendored.TypeParameterAccessors:`
`2`	`2`	`unwrap_array_type,`
`3`	`3`	`specify_default_type_parameters,`
`4`	`4`	`specify_type_parameters,`
Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-using TypeParameterAccessors: unwrap_array_type`
	`1`	`+using .Vendored.TypeParameterAccessors: unwrap_array_type`
`2`	`2`	# TODO: Make `isgpu`, `ismtl`, etc.
`3`	`3`	# For `isgpu`, will require a `NDTensorsGPUArrayCoreExt`.
`4`	`4`	`iscu(A::AbstractArray) = iscu(typeof(A))`
Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-using TypeParameterAccessors: TypeParameterAccessors`
	`1`	`+using .Vendored.TypeParameterAccessors: TypeParameterAccessors`
`2`	`2`
`3`	`3`	`"""`
`4`	`4`	`# Do we still want to define things like this?`
Original file line number	Diff line number	Diff line change
`@@ -27,7 +27,7 @@ double_precision(x) = fmap(x -> adapt(double_precision(eltype(x)), x), x)`
`27`	`27`	# Used to adapt `EmptyStorage` types
`28`	`28`	`#`
`29`	`29`
`30`		`-using TypeParameterAccessors: specify_type_parameters`
	`30`	`+using .Vendored.TypeParameterAccessors: specify_type_parameters`
`31`	`31`	`function adapt_storagetype(to::Type{<:AbstractVector}, x::Type{<:TensorStorage})`
`32`	`32`	`return set_datatype(x, specify_type_parameters(to, eltype, eltype(x)))`
`33`	`33`	`end`