Fix method ambiguity issues (#123)

* Fix method ambiguity issues * Fix format Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> * Update tolerances --------- Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
TuringLang · Jun 20, 2023 · d7c549f · d7c549f · devmotion · Jun 20, 2023
1 parent e149f9f
commit d7c549f
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Showing 3 changed files with 23 additions and 6 deletions.
diff --git a/Project.toml b/Project.toml
@@ -3,7 +3,7 @@ uuid = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
 keywords = ["markov chain monte carlo", "probablistic programming"]
 license = "MIT"
 desc = "A lightweight interface for common MCMC methods."
-version = "4.4.1"
+version = "4.4.2"
 
 [deps]
 BangBang = "198e06fe-97b7-11e9-32a5-e1d131e6ad66"

diff --git a/src/interface.jl b/src/interface.jl
@@ -30,13 +30,30 @@ be specified with the `chain_type` argument.
 By default, this method returns `samples`.
 """
 function bundle_samples(
-    samples, ::AbstractModel, ::AbstractSampler, ::Any, ::Type; kwargs...
+    samples, model::AbstractModel, sampler::AbstractSampler, state, ::Type{T}; kwargs...
+) where {T}
+    # dispatch to internal method for default implementations to fix
+    # method ambiguity issues (see #120)
+    return _bundle_samples(samples, model, sampler, state, T; kwargs...)
+end
+
+function _bundle_samples(
+    samples,
+    @nospecialize(::AbstractModel),
+    @nospecialize(::AbstractSampler),
+    @nospecialize(::Any),
+    ::Type;
+    kwargs...,
 )
     return samples
 end
-
-function bundle_samples(
-    samples::Vector, ::AbstractModel, ::AbstractSampler, ::Any, ::Type{Vector{T}}; kwargs...
+function _bundle_samples(
+    samples::Vector,
+    @nospecialize(::AbstractModel),
+    @nospecialize(::AbstractSampler),
+    @nospecialize(::Any),
+    ::Type{Vector{T}};
+    kwargs...,
 ) where {T}
     return map(samples) do sample
         convert(T, sample)

diff --git a/test/sample.jl b/test/sample.jl
@@ -564,7 +564,7 @@
         @test ismissing(chain[1].a)
         @test mean(x.a for x in view(chain, 2:1_000)) ≈ 0.5 atol = 6e-2
         @test var(x.a for x in view(chain, 2:1_000)) ≈ 1 / 12 atol = 1e-2
-        @test mean(x.b for x in chain) ≈ 0 atol = 0.1
+        @test mean(x.b for x in chain) ≈ 0 atol = 0.11
         @test var(x.b for x in chain) ≈ 1 atol = 0.15
     end