Allow conditioning with tuples with more than one element (#849)

Author: penelopeysm

HISTORY.md

@@ -1,5 +1,20 @@
 # DynamicPPL Changelog
 
+## 0.35.3
+
+`model | (@varname(x) => 1.0, @varname(y) => 2.0)` now works.
+Previously, this would throw a `MethodError` if the tuple had more than one element.
+
+## 0.35.2
+
+`unflatten(::VarInfo, params)` now works with params that have non-float types (such as Int or Bool).
+
+## 0.35.1
+
+`subset(::AbstractVarInfo, ::AbstractVector{<:VarName})` now preserves the ordering of the varnames in the original varinfo argument.
+Previously, this would select the varnames according to their order in the second argument.
+This fixes an upstream Turing.jl issue with Gibbs sampling when a component sampler was assigned multiple variables.
+
 ## 0.35.0
 
 **Breaking changes**

Project.toml

@@ -1,6 +1,6 @@
 name = "DynamicPPL"
 uuid = "366bfd00-2699-11ea-058f-f148b4cae6d8"
-version = "0.35.2"
+version = "0.35.3"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"

src/model.jl

@@ -287,7 +287,7 @@ AbstractDict (e.g. `model | (x=1, y=2)`), as well as if they are splatted (e.g.
 `condition(model, x=1, y=2)`).
 """
 _make_conditioning_values(values::Union{NamedTuple,AbstractDict}) = values
-_make_conditioning_values(values::Tuple{Pair{<:VarName}}) = Dict(values)
+_make_conditioning_values(values::NTuple{N,Pair{<:VarName}}) where {N} = Dict(values)
 _make_conditioning_values(v::Pair{<:Symbol}, vs::Pair{<:Symbol}...) = NamedTuple(v, vs...)
 _make_conditioning_values(v::Pair{<:VarName}, vs::Pair{<:VarName}...) = Dict(v, vs...)
 

test/model.jl

@@ -117,13 +117,22 @@ const GDEMO_DEFAULT = DynamicPPL.TestUtils.demo_assume_observe_literal()
             conditioned_model = condition(model, (y=2,))
             @test keys(VarInfo(conditioned_model)) == [@varname(x)]
         end
+
         @testset "conditioning AbstractDict" begin
+            # condition just 1 variable
             expected_values = Dict(@varname(y) => 2)
             @test condition(model, Dict(@varname(y) => 2)).context.values == expected_values
             @test condition(model, @varname(y) => 2).context.values == expected_values
             @test (model | (@varname(y) => 2,)).context.values == expected_values
             conditioned_model = condition(model, Dict(@varname(y) => 2))
             @test keys(VarInfo(conditioned_model)) == [@varname(x)]
+
+            # condition 2 variables
+            expected_values = Dict(@varname(x) => 1, @varname(y) => 2)
+            @test condition(model, (@varname(x) => 1, @varname(y) => 2)).context.values ==
+                expected_values
+            conditioned_model = condition(model, (@varname(x) => 1, @varname(y) => 2))
+            @test keys(VarInfo(conditioned_model)) == []
         end
 
         @testset "deconditioning" begin