upgrade polynomial (#70)

* update Polynomials to 4, fix serveral bugs

* update

* bump version and try to fix tag bot

Author: GiggleLiu

.github/workflows/TagBot.yml

@@ -4,6 +4,22 @@ on:
     types:
       - created
   workflow_dispatch:
+    inputs:
+      lookback:
+        default: 3
+permissions:
+  actions: read
+  checks: read
+  contents: write
+  deployments: read
+  issues: read
+  discussions: read
+  packages: read
+  pages: read
+  pull-requests: read
+  repository-projects: read
+  security-events: read
+  statuses: read
 jobs:
   TagBot:
     if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
@@ -12,4 +28,6 @@ jobs:
       - uses: JuliaRegistries/TagBot@v1
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
+          # Edit the following line to reflect the actual name of the GitHub Secret containing your private key
           ssh: ${{ secrets.DOCUMENTER_KEY }}
+          # ssh: ${{ secrets.NAME_OF_MY_SSH_PRIVATE_KEY_SECRET }}

Project.toml

@@ -1,7 +1,7 @@
 name = "GenericTensorNetworks"
 uuid = "3521c873-ad32-4bb4-b63d-f4f178f42b49"
 authors = ["GiggleLiu <cacate0129@gmail.com> and contributors"]
-version = "1.3.5"
+version = "1.3.6"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -35,7 +35,7 @@ Graphs = "1.7"
 LuxorGraphPlot = "0.2"
 Mods = "1.3"
 OMEinsum = "0.7"
-Polynomials = "2.0, 3"
+Polynomials = "4"
 Primes = "0.5"
 Requires = "1"
 SIMDTypes = "0.1"

src/arithematics.jl

@@ -898,7 +898,7 @@ function invert_polynomial(poly::Polynomial{BS,X}) where {BS,X}
     return LaurentPolynomial{BS,X}(poly.coeffs[end:-1:1], -length(poly.coeffs)+1)
 end
 function invert_polynomial(poly::LaurentPolynomial{BS,X}) where {BS,X}
-    return LaurentPolynomial{BS,X}(poly.coeffs[end:-1:1], -poly.m[]-length(poly.coeffs)+1)
+    return LaurentPolynomial{BS,X}(poly.coeffs[end:-1:1], -poly.order[]-length(poly.coeffs)+1)
 end
 
 # for finding all solutions

src/bitvector.jl

@@ -129,6 +129,9 @@ function StaticBitVector(x::AbstractVector)
     N = length(x)
     StaticBitVector{N,_nints(N,1)}((convert(BitVector, x).chunks...,))
 end
+# to void casting StaticBitVector itself
+StaticBitVector(x::StaticBitVector) = x
+
 function Base.convert(::Type{StaticBitVector{N,C}}, x::AbstractVector) where {N,C}
     @assert length(x) == N
     StaticBitVector(x)

src/interfaces.jl

@@ -336,7 +336,7 @@ end
 
 function solve(gp::ReducedProblem, property::AbstractProperty; T=Float64, usecuda=false)
     res = solve(target_problem(gp), property; T, usecuda)
-    return asarray(extract_result.(Ref(gp), res), res)
+    return asarray(extract_result(gp).(res), res)
 end
 
 # raise an error if the property for problem can not be computed

src/networks/Reduced.jl

@@ -16,11 +16,21 @@ function target_problem end
 
 """
     extract_result(p::ReducedProblem, output)
+    extract_result(p::ReducedProblem)
 
 Post process the output of the target problem to get an output to the source problem.
+If the output is not provided, it will return a function instead.
+The result extraction rule is determined by the output type.
+e.g. If the output type is `Tropical`, it will be interpreted as the energy.
+If the output is a `Vector`, it will be interpreted as a configuration.
 """
 function extract_result end
 
+# the fallback, this interface is designed for GPU compatibility
+function extract_result(r::ReducedProblem, res)
+    return extract_result(r)(res)
+end
+
 # fixedvertices(r::ReducedProblem) = fixedvertices(target_problem(r))
 # labels(r::ReducedProblem) = labels(target_problem(r))
 # terms(r::ReducedProblem) = terms(target_problem(r))

src/networks/SpinGlass.jl

@@ -43,25 +43,21 @@ end
 target_problem(sg::SpinGlass) = sg.target
 
 # the energy should be shifted by sum(J)/2 - sum(h)
-for ET in [:Tropical, :ExtendedTropical, :TruncatedPoly, :CountingTropical]
-    @eval function extract_result(sg::SpinGlass, res::T) where T <: $(ET)
-        sumJ = sum(i->sg.J[i], 1:ne(sg.target.graph))
-        sumh = sum(i->sg.h[i], 1:nv(sg.target.graph))
+function extract_result(sg::SpinGlass)
+    sumJ = sum(i->sg.J[i], 1:ne(sg.target.graph))
+    sumh = sum(i->sg.h[i], 1:nv(sg.target.graph))
+    function extractor(res::T) where T <: Union{Tropical, ExtendedTropical, TruncatedPoly, CountingTropical}
         # the cut size is always even if the input J is integer
         return res * _x(T; invert=false) ^ (-sumJ + sumh)
     end
-end
-function extract_result(sg::SpinGlass, res::Union{Polynomial{BS,X}, LaurentPolynomial{BS,X}}) where {BS,X}
-    sumJ = sum(i->sg.J[i], 1:ne(sg.target.graph))
-    sumh = sum(i->sg.h[i], 1:nv(sg.target.graph))
-    # the cut size is always even if the input J is integer
-    lres = LaurentPolynomial{BS,X}(res)
-    return lres * LaurentPolynomial{BS,X}([one(eltype(res.coeffs))], -sumJ + sumh)
-end
-
-# the configurations are not changed, vectors are treated as configurations
-for ET in [:SumProductTree, :ConfigSampler, :ConfigEnumerator, :Real, :AbstractVector]
-    @eval extract_result(sg::SpinGlass, res::T) where T <: $(ET) = res
+    function extractor(res::T) where {BS, X, T <: Union{Polynomial{BS,X}, LaurentPolynomial{BS,X}}}
+        lres = LaurentPolynomial{BS,X}(res)
+        return lres * LaurentPolynomial{BS,X}([one(eltype(res.coeffs))], -sumJ + sumh)
+    end
+    function extractor(res::T) where T<:Union{SumProductTree, ConfigSampler, ConfigEnumerator, Real, AbstractVector}
+        return res
+    end
+    return extractor
 end
 
 """

src/networks/networks.jl

@@ -198,7 +198,7 @@ function _pow(x::LaurentPolynomial{BS,X}, i) where {BS,X}
         return x^i
     else
         @assert length(x.coeffs) == 1
-        return LaurentPolynomial(x.coeffs .^ i, x.m[]*i)
+        return LaurentPolynomial(x.coeffs .^ i, x.order[]*i)
     end
 end
 

test/cuda.jl

@@ -54,4 +54,13 @@ end
     @test res12.c.data ∈ res13.c.data
     @test res14.maxorder == 4 && res14.coeffs[1]==30 && res14.coeffs[2] == 30 && res14.coeffs[3]==5
     @test res18 ≈ res2  
-end
+end
+
+@testset "spinglass" begin
+    g = Graphs.smallgraph("petersen")
+    gp = SpinGlass(g)
+    usecuda=true
+    @test solve(gp, CountingMax(); usecuda) isa CuArray
+    gp2 = SpinGlass(g; openvertices=(2,))
+    @test solve(gp2, CountingMax(); usecuda) isa CuArray
+end

test/networks/HyperSpinGlass.jl

@@ -33,8 +33,8 @@ using GenericTensorNetworks, Test, Graphs
     @test solve(gp, ConfigsMin())[].n ≈ sorted_energies[1]
     @test solve(gp, CountingAll())[] ≈ 1024
     poly = solve(gp, GraphPolynomial(; method=:laurent))[]
-    @test poly.m[] == sorted_energies[1]
-    @test poly.n[] == sorted_energies[end]
+    @test poly.order[] == sorted_energies[1]
+    @test poly.order[] + length(poly.coeffs) - 1 == sorted_energies[end]
 end
 
 @testset "auto laurent" begin
@@ -51,4 +51,4 @@ end
     problem = HyperSpinGlass(num_vertices, graph; weights);
     poly = solve(problem, GraphPolynomial())[]
     @test poly isa LaurentPolynomial
-end
+end