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Import code from
Tensors package (#81)
* Format code * Import code from `Tensors` * Fix OMEinsum import in tests * Update Julia minimum version to v1.9 * Remove `NetworkLayout` dependency * Fix `BlockArray` test dependency * Clean code * Stop testing on Julia 1.8 * Bump `EinExprs` minimum version to v0.4 * Rename `labels` to `EinExprs.inds` * Fix namespace clash in `expand` * Fix `einexpr` call * Implement conversion to `EinExprs.Tensor` * Bump `EinExprs` to v0.5 Temporarily break `contract` function * Fix name shadowing of `inds` method * Refactor `RankSimplifaction` to new `EinExprs` structure * Skip `contract` in `Transformation` tests * Bump `EinExprs` to v0.5.1
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| fail-fast: false | ||
| matrix: | ||
| version: | ||
| - '1.8' | ||
| - '1.9' | ||
| os: | ||
| - ubuntu-latest | ||
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@@ -8,7 +8,6 @@ jobs: | |
| strategy: | ||
| matrix: | ||
| version: | ||
| - '1.8' | ||
| - '1.9' | ||
| os: | ||
| - ubuntu-latest | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,146 @@ | ||
| using OMEinsum | ||
| using LinearAlgebra | ||
| using UUIDs: uuid4 | ||
| using EinExprs: inds | ||
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| # TODO test array container typevar on output | ||
| for op in [ | ||
| :+, | ||
| :-, | ||
| :*, | ||
| :/, | ||
| :\, | ||
| :^, | ||
| :÷, | ||
| :fld, | ||
| :cld, | ||
| :mod, | ||
| :%, | ||
| :fldmod, | ||
| :fld1, | ||
| :mod1, | ||
| :fldmod1, | ||
| ://, | ||
| :gcd, | ||
| :lcm, | ||
| :gcdx, | ||
| :widemul, | ||
| ] | ||
| @eval Base.$op(a::Tensor{A,0}, b::Tensor{B,0}) where {A,B} = broadcast($op, a, b) | ||
| end | ||
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| """ | ||
| contract(a::Tensor[, b::Tensor, dims=nonunique([inds(a)..., inds(b)...])]) | ||
| Perform tensor contraction operation. | ||
| """ | ||
| function contract(a::Tensor, b::Tensor; dims = (∩(inds(a), inds(b)))) | ||
| ia = inds(a) | ||
| ib = inds(b) | ||
| i = ∩(dims, ia, ib) | ||
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| ic = tuple(setdiff(ia ∪ ib, i isa Base.AbstractVecOrTuple ? i : (i,))...) | ||
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| data = EinCode((String.(ia), String.(ib)), String.(ic))(parent(a), parent(b)) | ||
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| # TODO merge metadata? | ||
| return Tensor(data, ic) | ||
| end | ||
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| function contract(a::Tensor; dims = nonunique(inds(a))) | ||
| ia = inds(a) | ||
| i = ∩(dims, ia) | ||
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| ic = tuple(setdiff(ia, i isa Base.AbstractVecOrTuple ? i : (i,))...) | ||
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| data = EinCode((String.(ia),), String.(ic))(parent(a)) | ||
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| # TODO merge metadata | ||
| return Tensor(data, ic) | ||
| end | ||
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| contract(a::Union{T,AbstractArray{T,0}}, b::Tensor{T}) where {T} = contract(Tensor(a), b) | ||
| contract(a::Tensor{T}, b::Union{T,AbstractArray{T,0}}) where {T} = contract(a, Tensor(b)) | ||
| contract(a::AbstractArray{<:Any,0}, b::AbstractArray{<:Any,0}) = contract(Tensor(a), Tensor(b)) |> only | ||
| contract(a::Number, b::Number) = contract(fill(a), fill(b)) | ||
| contract(tensors::Tensor...; kwargs...) = reduce((x, y) -> contract(x, y; kwargs...), tensors) | ||
|
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| """ | ||
| *(::Tensor, ::Tensor) | ||
| Alias for [`contract`](@ref). | ||
| """ | ||
| Base.:*(a::Tensor, b::Tensor) = contract(a, b) | ||
| Base.:*(a::Tensor, b) = contract(a, b) | ||
| Base.:*(a, b::Tensor) = contract(a, b) | ||
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| LinearAlgebra.svd(t::Tensor{<:Any,2}; kwargs...) = Base.@invoke svd(t::Tensor; left_inds = (first(inds(t)),), kwargs...) | ||
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| function LinearAlgebra.svd(t::Tensor; left_inds, kwargs...) | ||
| if isempty(left_inds) | ||
| throw(ErrorException("no left-indices in SVD factorization")) | ||
| elseif any(∉(inds(t)), left_inds) | ||
| # TODO better error exception and checks | ||
| throw(ErrorException("all left-indices must be in $(inds(t))")) | ||
| end | ||
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| right_inds = setdiff(inds(t), left_inds) | ||
| if isempty(right_inds) | ||
| # TODO better error exception and checks | ||
| throw(ErrorException("no right-indices in SVD factorization")) | ||
| end | ||
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| # permute array | ||
| tensor = permutedims(t, (left_inds..., right_inds...)) | ||
| data = reshape(parent(tensor), prod(i -> size(t, i), left_inds), prod(i -> size(t, i), right_inds)) | ||
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| # compute SVD | ||
| U, s, V = svd(data; kwargs...) | ||
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| # tensorify results | ||
| U = reshape(U, ([size(t, ind) for ind in left_inds]..., size(U, 2))) | ||
| s = Diagonal(s) | ||
| Vt = reshape(V', (size(V', 1), [size(t, ind) for ind in right_inds]...)) | ||
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| vlind = Symbol(uuid4()) | ||
| vrind = Symbol(uuid4()) | ||
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| U = Tensor(U, (left_inds..., vlind)) | ||
| s = Tensor(s, (vlind, vrind)) | ||
| Vt = Tensor(Vt, (vrind, right_inds...)) | ||
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| return U, s, Vt | ||
| end | ||
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| LinearAlgebra.qr(t::Tensor{<:Any,2}; kwargs...) = Base.@invoke qr(t::Tensor; left_inds = (first(inds(t)),), kwargs...) | ||
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| function LinearAlgebra.qr(t::Tensor; left_inds = (), right_inds = (), virtualind::Symbol = Symbol(uuid4()), kwargs...) | ||
| isdisjoint(left_inds, right_inds) || | ||
| throw(ArgumentError("left ($left_inds) and right $(right_inds) indices must be disjoint")) | ||
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| left_inds, right_inds = | ||
| isempty(left_inds) ? (setdiff(inds(t), right_inds), right_inds) : | ||
| isempty(right_inds) ? (left_inds, setdiff(inds(t), left_inds)) : | ||
| throw(ArgumentError("cannot set both left and right indices")) | ||
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| all(!isempty, (left_inds, right_inds)) || throw(ArgumentError("no right-indices left in QR factorization")) | ||
| all(∈(inds(t)), left_inds ∪ right_inds) || throw(ArgumentError("indices must be in $(inds(t))")) | ||
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| virtualind ∉ inds(t) || throw(ArgumentError("new virtual bond name ($virtualind) cannot be already be present")) | ||
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| # permute array | ||
| tensor = permutedims(t, (left_inds..., right_inds...)) | ||
| data = reshape(parent(tensor), prod(i -> size(t, i), left_inds), prod(i -> size(t, i), right_inds)) | ||
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| # compute QR | ||
| Q, R = qr(data; kwargs...) | ||
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| # tensorify results | ||
| Q = reshape(Q, ([size(t, ind) for ind in left_inds]..., size(Q, 2))) | ||
| R = reshape(R, (size(R, 1), [size(t, ind) for ind in right_inds]...)) | ||
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| Q = Tensor(Q, (left_inds..., virtualind)) | ||
| R = Tensor(R, (virtualind, right_inds...)) | ||
|
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| return Q, R | ||
| end |
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