fix ESS reproducibility

Author: penelopeysm

src/mcmc/ess.jl

@@ -82,7 +82,7 @@ EllipticalSliceSampling.isgaussian(::Type{<:ESSPrior}) = true
 
 # Only define out-of-place sampling
 function Base.rand(rng::Random.AbstractRNG, p::ESSPrior)
-    _, vi = DynamicPPL.init!!(p.model, p.varinfo, DynamicPPL.InitFromPrior())
+    _, vi = DynamicPPL.init!!(rng, p.model, p.varinfo, DynamicPPL.InitFromPrior())
     return vi[:]
 end
 

test/mcmc/ess.jl

@@ -2,6 +2,7 @@ module ESSTests
 
 using ..Models: MoGtest, MoGtest_default, gdemo, gdemo_default
 using ..NumericalTests: check_MoGtest_default, check_numerical
+using ..SamplerTestUtils: check_rng_respected
 using Distributions: Normal, sample
 using DynamicPPL: DynamicPPL
 using DynamicPPL: Sampler
@@ -38,6 +39,12 @@ using Turing
         c3 = sample(gdemo_default, s2, N)
     end
 
+    @testset "RNG is respected" begin
+        check_rng_respected(ESS())
+        check_rng_respected(Gibbs(:x => ESS(), :y => MH()))
+        check_rng_respected(Gibbs(:x => ESS(), :y => ESS()))
+    end
+
     @testset "ESS inference" begin
         @info "Starting ESS inference tests"
         seed = 23

test/test_utils/sampler.jl

@@ -1,5 +1,6 @@
 module SamplerTestUtils
 
+using Random
 using Turing
 using Test
 
@@ -24,4 +25,17 @@ function test_chain_logp_metadata(spl)
     @test chn[:lp] ≈ chn[:logprior] + chn[:loglikelihood]
 end
 
+function test_rng_respected(spl)
+    @model function f(z)
+        # put at least two variables here so that we can meaningfully test Gibbs
+        x ~ Normal()
+        y ~ Normal()
+        return z ~ Normal(x + y)
+    end
+    model = f(2.0)
+    chn1 = sample(Xoshiro(468), model, spl, 100)
+    chn2 = sample(Xoshiro(468), model, spl, 100)
+    @test chn1 == chn2
+end
+
 end