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[TypeParameterAccessors] similartype (#1561)
* [TypeParameterAccessors] `similartype` * [NDTensors] Bump to v0.3.50
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17 files changed

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‎NDTensors/Project.toml‎

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name = "NDTensors"
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uuid = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
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authors = ["Matthew Fishman <[email protected]>"]
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version = "0.3.49"
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version = "0.3.50"
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[deps]
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Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"

‎NDTensors/src/abstractarray/set_types.jl‎

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using .TypeParameterAccessors: TypeParameterAccessors, set_ndims
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using .TypeParameterAccessors: TypeParameterAccessors
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"""
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# Do we still want to define things like this?
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TODO: Use `Accessors.jl` notation:
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function TypeParameterAccessors.set_ndims(numbertype::Type{<:Number}, ndims)
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return numbertype
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end
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"""
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`set_indstype` should be overloaded for
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types with structured dimensions,
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like `OffsetArrays` or named indices
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(such as ITensors).
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"""
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function set_indstype(arraytype::Type{<:AbstractArray}, dims::Tuple)
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return set_ndims(arraytype, length(dims))
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end

‎NDTensors/src/abstractarray/similar.jl‎

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using .TypeParameterAccessors: IsWrappedArray, unwrap_array_type, set_eltype
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using Base: DimOrInd, Dims, OneTo
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using .TypeParameterAccessors: IsWrappedArray, unwrap_array_type, set_eltype, similartype
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## Custom `NDTensors.similar` implementation.
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## More extensive than `Base.similar`.
@@ -96,58 +97,3 @@ end
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# Use the `size` to determine the dimensions
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# NDTensors.similar
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similar(array::AbstractArray) = NDTensors.similar(typeof(array), size(array))
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## similartype
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function similartype(arraytype::Type{<:AbstractArray}, eltype::Type, dims::Tuple)
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return similartype(similartype(arraytype, eltype), dims)
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end
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@traitfn function similartype(
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arraytype::Type{ArrayT}, eltype::Type
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) where {ArrayT; !IsWrappedArray{ArrayT}}
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return set_eltype(arraytype, eltype)
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end
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@traitfn function similartype(
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arraytype::Type{ArrayT}, dims::Tuple
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) where {ArrayT; !IsWrappedArray{ArrayT}}
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return set_indstype(arraytype, dims)
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end
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function similartype(arraytype::Type{<:AbstractArray}, dims::DimOrInd...)
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return similartype(arraytype, dims)
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end
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function similartype(arraytype::Type{<:AbstractArray})
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return similartype(arraytype, eltype(arraytype))
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end
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## Wrapped arrays
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@traitfn function similartype(
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arraytype::Type{ArrayT}, eltype::Type
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) where {ArrayT; IsWrappedArray{ArrayT}}
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return similartype(unwrap_array_type(arraytype), eltype)
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end
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@traitfn function similartype(
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arraytype::Type{ArrayT}, dims::Tuple
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) where {ArrayT; IsWrappedArray{ArrayT}}
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return similartype(unwrap_array_type(arraytype), dims)
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end
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# This is for uniform `Diag` storage which uses
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# a Number as the data type.
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# TODO: Delete this when we change to using a
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# `FillArray` instead. This is a stand-in
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# to make things work with the current design.
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function similartype(numbertype::Type{<:Number})
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return numbertype
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end
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# Instances
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function similartype(array::AbstractArray, eltype::Type, dims...)
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return similartype(typeof(array), eltype, dims...)
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end
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similartype(array::AbstractArray, eltype::Type) = similartype(typeof(array), eltype)
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similartype(array::AbstractArray, dims...) = similartype(typeof(array), dims...)

‎NDTensors/src/blocksparse/blockdims.jl‎

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@@ -1,3 +1,5 @@
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using .TypeParameterAccessors: TypeParameterAccessors
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"""
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BlockDim
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@@ -18,7 +20,9 @@ const BlockDims{N} = NTuple{N,BlockDim}
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Base.ndims(ds::Type{<:BlockDims{N}}) where {N} = N
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similartype(::Type{<:BlockDims}, ::Type{Val{N}}) where {N} = BlockDims{N}
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function TypeParameterAccessors.similartype(::Type{<:BlockDims}, ::Type{Val{N}}) where {N}
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return BlockDims{N}
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end
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Base.copy(ds::BlockDims) = ds
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‎NDTensors/src/blocksparse/blocksparsetensor.jl‎

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using .TypeParameterAccessors: similartype
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#
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# BlockSparseTensor (Tensor using BlockSparse storage)
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#

‎NDTensors/src/blocksparse/diagblocksparse.jl‎

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using .TypeParameterAccessors: similartype
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export DiagBlockSparse, DiagBlockSparseTensor
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# DiagBlockSparse can have either Vector storage, in which case

‎NDTensors/src/blocksparse/similar.jl‎

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using .TypeParameterAccessors: similartype
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# NDTensors.similar
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function similar(storagetype::Type{<:BlockSparse}, blockoffsets::BlockOffsets, dims::Tuple)
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data = similar(datatype(storagetype), nnz(blockoffsets, dims))

‎NDTensors/src/diag/similar.jl‎

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@@ -1,11 +1,13 @@
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using NDTensors.TypeParameterAccessors: TypeParameterAccessors
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# NDTensors.similar
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function similar(storagetype::Type{<:Diag}, dims::Dims)
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return setdata(storagetype, similar(datatype(storagetype), mindim(dims)))
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end
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# TODO: Redesign UniformDiag to make it handled better
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# by generic code.
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function similartype(storagetype::Type{<:UniformDiag}, eltype::Type)
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function TypeParameterAccessors.similartype(storagetype::Type{<:UniformDiag}, eltype::Type)
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# This will also set the `datatype`.
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return set_eltype(storagetype, eltype)
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end

‎NDTensors/src/dims.jl‎

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using .DiagonalArrays: DiagonalArrays
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using .TypeParameterAccessors: TypeParameterAccessors
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export dense, dims, dim, mindim, diaglength
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@@ -52,7 +53,7 @@ dim_to_stride(ds, k::Int) = dim_to_strides(ds)[k]
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# code (it helps to construct a Tuple(::NTuple{N,Int}) where the
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# only known thing for dispatch is a concrete type such
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# as Dims{4})
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similartype(::Type{<:Dims}, ::Type{Val{N}}) where {N} = Dims{N}
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TypeParameterAccessors.similartype(::Type{<:Dims}, ::Type{Val{N}}) where {N} = Dims{N}
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# This is to help with ITensor compatibility
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dim(i::Int) = i

‎NDTensors/src/empty/empty.jl‎

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@@ -1,22 +1,25 @@
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using .TypeParameterAccessors: TypeParameterAccessors, set_eltype, similartype
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#
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# Represents a tensor order that could be set to any order.
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#
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struct EmptyOrder end
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function similartype(StoreT::Type{<:TensorStorage{EmptyNumber}}, ElT::Type)
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function TypeParameterAccessors.similartype(
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StoreT::Type{<:TensorStorage{EmptyNumber}}, ElT::Type
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)
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return set_eltype(StoreT, ElT)
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end
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function similartype(
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function TypeParameterAccessors.similartype(
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StoreT::Type{<:TensorStorage{EmptyNumber}}, DataT::Type{<:AbstractArray}
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)
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return set_datatype(StoreT, DataT)
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end
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## TODO fix this similartype to use set eltype for BlockSparse
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function similartype(
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function TypeParameterAccessors.similartype(
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::Type{StoreT}, ::Type{ElT}
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) where {StoreT<:BlockSparse{EmptyNumber},ElT}
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return BlockSparse{ElT,similartype(datatype(StoreT), ElT),ndims(StoreT)}

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