add compatibility with Turing.Experimental.Gibbs

Author: Red-Portal

Project.toml

@@ -1,6 +1,6 @@
 name = "SliceSampling"
 uuid = "43f4d3e8-9711-4a8c-bd1b-03ac73a255cf"
-version = "0.5.0"
+version = "0.6.0"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
@@ -31,7 +31,7 @@ LogDensityProblemsAD = "1"
 Random = "1"
 Requires = "1"
 SimpleUnPack = "1"
-Turing = "0.31, 0.32, 0.33"
+Turing = "0.33"
 julia = "1.7"
 
 [extras]

docs/src/general.md

@@ -60,6 +60,39 @@ model     = demo()
 sample(model, externalsampler(sampler), n_samples)
 ```
 
+### Conditional sampling in a `Turing.Experimental.Gibbs` sampler
+`SliceSampling.jl` be used as a conditional sampler in `Turing.Experimental.Gibbs`.
+
+```@example turinggibbs
+using Distributions
+using FillArrays
+using Turing
+using SliceSampling
+
+@model function simple_choice(xs)
+    p ~ Beta(2, 2)
+    z ~ Bernoulli(p)
+    for i in 1:length(xs)
+        if z == 1
+            xs[i] ~ Normal(0, 1)
+        else
+            xs[i] ~ Normal(2, 1)
+        end
+    end
+end
+
+sampler = Turing.Experimental.Gibbs(
+    (
+        p = externalsampler(SliceSteppingOut(2.0)),
+        z = PG(20, :z)
+    )
+)
+
+n_samples = 1000
+model     = simple_choice([1.5, 2.0, 0.3])
+sample(model, sampler, n_samples)
+```
+
 ## Drawing Samples
 For drawing samples using the algorithms provided by `SliceSampling`, the user only needs to call:
 ```julia

ext/SliceSamplingTuringExt.jl

@@ -5,18 +5,53 @@ if isdefined(Base, :get_extension)
     using LogDensityProblemsAD
     using Random
     using SliceSampling
-    using Turing: Turing
+    using Turing
+   # using Turing: Turing, Experimental
 else
     using ..LogDensityProblemsAD
     using ..Random
     using ..SliceSampling
-    using ..Turing: Turing
+    using ..Turing
+    #using ..Turing: Turing, Experimental
 end
 
+# Required for using the slice samplers as `externalsampler`s in Turing
+# begin
 Turing.Inference.getparams(
           ::Turing.DynamicPPL.Model,
     sample::SliceSampling.Transition
 ) = sample.params
+# end
+
+# Required for using the slice samplers as `Experimental.Gibbs` samplers in Turing
+# begin
+Turing.Inference.getparams(
+         ::Turing.DynamicPPL.Model,
+    state::SliceSampling.UnivariateSliceState
+) = state.transition.params
+
+Turing.Inference.getparams(
+         ::Turing.DynamicPPL.Model,
+    state::SliceSampling.GibbsState
+) = state.transition.params
+
+Turing.Inference.getparams(
+         ::Turing.DynamicPPL.Model,
+    state::SliceSampling.HitAndRunState
+) = state.transition.params
+
+Turing.Experimental.gibbs_requires_recompute_logprob(
+    model_dst,
+    ::Turing.DynamicPPL.Sampler{
+        <: Turing.Inference.ExternalSampler{
+            <: SliceSampling.AbstractSliceSampling, A, U
+        }
+    },
+    sampler_src,
+    state_dst,
+    state_src
+) where {A,U} = false
+# end
 
 function SliceSampling.initial_sample(
     rng::Random.AbstractRNG,

test/Project.toml

@@ -18,5 +18,5 @@ MCMCTesting = "0.3"
 Random = "1"
 StableRNGs = "1"
 Test = "1"
-Turing = "0.31"
+Turing = "0.33"
 julia = "1.6"

test/turing.jl

@@ -35,4 +35,25 @@
             progress=false,
         )
     end
+
+    @testset "gibbs($sampler)" for sampler in [
+        RandPermGibbs(Slice(1)),
+        RandPermGibbs(SliceSteppingOut(1)),
+        RandPermGibbs(SliceDoublingOut(1)),
+        Slice(1),
+        SliceSteppingOut(1),
+        SliceDoublingOut(1),
+    ]
+        sample(
+            model,
+            Turing.Experimental.Gibbs(
+                (
+                    s = externalsampler(sampler),
+                    m = externalsampler(sampler),
+                ),
+            ),
+            n_samples,
+            progress=false,
+        )
+    end
 end