Add tests

Author: lkdvos

test/test_tensoroperations.jl

@@ -0,0 +1,121 @@
+using Test: @test, @testset, @inferred
+using TensorOperations: @tensor, ncon, tensorcontract
+using TensorAlgebra: Matricize
+
+@testset "tensorcontract" begin
+  A = randn(Float64, (3, 20, 5, 3, 4))
+  B = randn(Float64, (5, 6, 20, 3))
+  C1 = @inferred tensorcontract(
+    A, ((1, 4, 5), (2, 3)), false, B, ((3, 1), (2, 4)), false, ((1, 5, 3, 2, 4), ()), 1.0
+  )
+  C2 = @inferred tensorcontract(
+    A,
+    ((1, 4, 5), (2, 3)),
+    false,
+    B,
+    ((3, 1), (2, 4)),
+    false,
+    ((1, 5, 3, 2, 4), ()),
+    1.0,
+    Matricize(),
+  )
+  @test C1 ≈ C2
+end
+
+elts = (Float32, Float64, ComplexF32, ComplexF64)
+
+@testset "tensor network examples ($T)" for T in elts
+  D1, D2, D3 = 30, 40, 20
+  d1, d2 = 2, 3
+  A1 = rand(T, D1, d1, D2) .- 1//2
+  A2 = rand(T, D2, d2, D3) .- 1//2
+  rhoL = rand(T, D1, D1) .- 1//2
+  rhoR = rand(T, D3, D3) .- 1//2
+  H = rand(T, d1, d2, d1, d2) .- 1//2
+
+  @tensor HrA12[a, s1, s2, c] :=
+    rhoL[a, a'] * A1[a', t1, b] * A2[b, t2, c'] * rhoR[c', c] * H[s1, s2, t1, t2]
+  @tensor backend = Matricize() HrA12′[a, s1, s2, c] :=
+    rhoL[a, a'] * A1[a', t1, b] * A2[b, t2, c'] * rhoR[c', c] * H[s1, s2, t1, t2]
+
+  @test HrA12 ≈ HrA12′
+  @test HrA12 ≈ ncon(
+    [rhoL, H, A2, rhoR, A1],
+    [[-1, 1], [-2, -3, 4, 5], [2, 5, 3], [3, -4], [1, 4, 2]];
+    backend=Matricize(),
+  )
+  E = @tensor rhoL[a', a] *
+    A1[a, s, b] *
+    A2[b, s', c] *
+    rhoR[c, c'] *
+    H[t, t', s, s'] *
+    conj(A1[a', t, b']) *
+    conj(A2[b', t', c'])
+  @test E ≈ @tensor backend = Matricize() rhoL[a', a] *
+    A1[a, s, b] *
+    A2[b, s', c] *
+    rhoR[c, c'] *
+    H[t, t', s, s'] *
+    conj(A1[a', t, b']) *
+    conj(A2[b', t', c'])
+end
+
+function generate_random_network(
+  num_contracted_inds, num_open_inds, max_dim, max_ind_per_tensor
+)
+  contracted_indices = repeat(collect(1:num_contracted_inds), 2)
+  open_indices = collect(1:num_open_inds)
+  dimensions = [
+    repeat(rand(1:max_dim, num_contracted_inds), 2)
+    rand(1:max_dim, num_open_inds)
+  ]
+
+  sizes = Vector{Int64}[]
+  indices = Vector{Int64}[]
+
+  while !isempty(contracted_indices) || !isempty(open_indices)
+    num_inds = rand(
+      1:min(max_ind_per_tensor, length(contracted_indices) + length(open_indices))
+    )
+
+    cur_inds = Int64[]
+    cur_dims = Int64[]
+
+    for _ in 1:num_inds
+      curind_index = rand(1:(length(contracted_indices) + length(open_indices)))
+
+      if curind_index <= length(contracted_indices)
+        push!(cur_inds, contracted_indices[curind_index])
+        push!(cur_dims, dimensions[curind_index])
+        deleteat!(contracted_indices, curind_index)
+        deleteat!(dimensions, curind_index)
+      else
+        tind = curind_index - length(contracted_indices)
+        push!(cur_inds, -open_indices[tind])
+        push!(cur_dims, dimensions[curind_index])
+        deleteat!(open_indices, tind)
+        deleteat!(dimensions, curind_index)
+      end
+    end
+
+    push!(sizes, cur_dims)
+    push!(indices, cur_inds)
+  end
+  return sizes, indices
+end
+
+@testset "random contractions" begin
+  MAX_CONTRACTED_INDICES = 10
+  MAX_OPEN_INDICES = 5
+  MAX_DIM = 5
+  MAX_IND_PER_TENS = 3
+  NUM_TESTS = 10
+
+  for _ in 1:NUM_TESTS
+    sizes, indices = generate_random_network(rand(1:MAX_CONTRACTED_INDICES), rand(1:MAX_OPEN_INDICES), MAX_DIM, MAX_IND_PER_TENS)
+    tensors = map(splat(randn), sizes)
+    result1 = ncon(tensors, indices)
+    result2 = ncon(tensors, indices; backend=Matricize())
+    @test result1 ≈ result2
+  end
+end