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Add support for Adapt which enables converting tensor networks to GPU (…
…#187) * Add support for Adapt which enables converting tensor networks to GPU * Bump to v0.11.13
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@@ -1,7 +1,7 @@ | ||
name = "ITensorNetworks" | ||
uuid = "2919e153-833c-4bdc-8836-1ea460a35fc7" | ||
authors = ["Matthew Fishman <[email protected]>, Joseph Tindall <[email protected]> and contributors"] | ||
version = "0.11.12" | ||
version = "0.11.13" | ||
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[deps] | ||
AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c" | ||
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@@ -36,19 +36,22 @@ TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f" | |
TupleTools = "9d95972d-f1c8-5527-a6e0-b4b365fa01f6" | ||
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[weakdeps] | ||
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e" | ||
EinExprs = "b1794770-133b-4de1-afb4-526377e9f4c5" | ||
GraphsFlows = "06909019-6f44-4949-96fc-b9d9aaa02889" | ||
OMEinsumContractionOrders = "6f22d1fd-8eed-4bb7-9776-e7d684900715" | ||
Observers = "338f10d5-c7f1-4033-a7d1-f9dec39bcaa0" | ||
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[extensions] | ||
ITensorNetworksAdaptExt = "Adapt" | ||
ITensorNetworksEinExprsExt = "EinExprs" | ||
ITensorNetworksGraphsFlowsExt = "GraphsFlows" | ||
ITensorNetworksOMEinsumContractionOrdersExt = "OMEinsumContractionOrders" | ||
ITensorNetworksObserversExt = "Observers" | ||
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[compat] | ||
AbstractTrees = "0.4.4" | ||
Adapt = "4" | ||
Combinatorics = "1" | ||
Compat = "3, 4" | ||
DataGraphs = "0.2.3" | ||
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@@ -82,6 +85,7 @@ TupleTools = "1.4" | |
julia = "1.10" | ||
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[extras] | ||
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e" | ||
EinExprs = "b1794770-133b-4de1-afb4-526377e9f4c5" | ||
GraphsFlows = "06909019-6f44-4949-96fc-b9d9aaa02889" | ||
OMEinsumContractionOrders = "6f22d1fd-8eed-4bb7-9776-e7d684900715" | ||
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module ITensorNetworksAdaptExt | ||
using Adapt: Adapt, adapt | ||
using ITensorNetworks: AbstractITensorNetwork, map_vertex_data_preserve_graph | ||
function Adapt.adapt_structure(to, tn::AbstractITensorNetwork) | ||
# TODO: Define and use: | ||
# | ||
# @preserve_graph map_vertex_data(adapt(to), tn) | ||
# | ||
# or just: | ||
# | ||
# @preserve_graph map(adapt(to), tn) | ||
return map_vertex_data_preserve_graph(adapt(to), tn) | ||
end | ||
end |
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@@ -0,0 +1,5 @@ | ||
[deps] | ||
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e" | ||
ITensorNetworks = "2919e153-833c-4bdc-8836-1ea460a35fc7" | ||
ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5" | ||
NamedGraphs = "678767b0-92e7-4007-89e4-4527a8725b19" |
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@eval module $(gensym()) | ||
using Adapt: Adapt, adapt | ||
using NamedGraphs.NamedGraphGenerators: named_grid | ||
using ITensorNetworks: random_tensornetwork, siteinds | ||
using ITensors: ITensors | ||
using Test: @test, @testset | ||
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struct SinglePrecisionAdaptor end | ||
single_precision(::Type{<:AbstractFloat}) = Float32 | ||
single_precision(type::Type{<:Complex}) = complex(single_precision(real(type))) | ||
Adapt.adapt_storage(::SinglePrecisionAdaptor, x) = single_precision(eltype(x)).(x) | ||
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@testset "Test ITensorNetworksAdaptExt (eltype=$elt)" for elt in ( | ||
Float32, Float64, Complex{Float32}, Complex{Float64} | ||
) | ||
g = named_grid((2, 2)) | ||
s = siteinds("S=1/2", g) | ||
tn = random_tensornetwork(elt, s) | ||
@test ITensors.scalartype(tn) === elt | ||
tn′ = adapt(SinglePrecisionAdaptor(), tn) | ||
@test ITensors.scalartype(tn′) === single_precision(elt) | ||
end | ||
end |
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Registration pull request created: JuliaRegistries/General/107974
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