From f9fe841d5119cd46ad0c6392f15d5cb28529cc6b Mon Sep 17 00:00:00 2001
From: mtfishman <mfishman@flatironinstitute.org>
Date: Fri, 17 May 2024 09:46:20 -0400
Subject: [PATCH] Add missing constructor, fix typo

---
 src/specialitensornetworks.jl | 18 +++++++++++++++---
 test/test_itensornetwork.jl   |  2 +-
 2 files changed, 16 insertions(+), 4 deletions(-)

diff --git a/src/specialitensornetworks.jl b/src/specialitensornetworks.jl
index 92cd434b..f0c4f26f 100644
--- a/src/specialitensornetworks.jl
+++ b/src/specialitensornetworks.jl
@@ -70,14 +70,26 @@ Build an ITensor network on a graph specified by the inds network s.
 Bond_dim is given by link_space and entries are randomized.
 The random distribution is based on the input argument `distribution`.
 """
-function random_tensornetwork(distribution::Distribution, s::IndsNetwork; kwargs...)
+function random_tensornetwork(
+  rng::AbstractRNG, distribution::Distribution, s::IndsNetwork; kwargs...
+)
   return ITensorNetwork(s; kwargs...) do v
-    return inds -> itensor(rand(distribution, dim.(inds)...), inds)
+    return inds -> itensor(rand(rng, distribution, dim.(inds)...), inds)
   end
 end
 
+function random_tensornetwork(distribution::Distribution, s::IndsNetwork; kwargs...)
+  return random_tensornetwork(Random.default_rng(), distribution, s; kwargs...)
+end
+
+@traitfn function random_tensornetwork(
+  rng::AbstractRNG, distribution::Distribution, g::::IsUnderlyingGraph; kwargs...
+)
+  return random_tensornetwork(rng, distribution, IndsNetwork(g); kwargs...)
+end
+
 @traitfn function random_tensornetwork(
   distribution::Distribution, g::::IsUnderlyingGraph; kwargs...
 )
-  return random_tensornetwork(distribution, IndsNetwork(g); kwargs...)
+  return random_tensornetwork(Random.default_rng(), distribution, g; kwargs...)
 end
diff --git a/test/test_itensornetwork.jl b/test/test_itensornetwork.jl
index 6fda876d..7e97c6a3 100644
--- a/test/test_itensornetwork.jl
+++ b/test/test_itensornetwork.jl
@@ -349,7 +349,7 @@ const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
     dims = (2, 2)
     g = named_grid(dims)
     s = siteinds("S=1/2", g)
-    rng = StableRN(1234)
+    rng = StableRNG(1234)
     ψ = random_tensornetwork(rng, s; link_space=2)
     @test scalartype(ψ) == Float64
     ϕ = NDTensors.convert_scalartype(new_eltype, ψ)