Restrict values_as_in_model API (#778)

Project.toml

@@ -1,6 +1,6 @@
 name = "DynamicPPL"
 uuid = "366bfd00-2699-11ea-058f-f148b4cae6d8"
-version = "0.33.1"
+version = "0.34.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"

src/values_as_in_model.jl

@@ -19,9 +19,9 @@ wants to extract the realization of a model in a constrained space.
 # Fields
 $(TYPEDFIELDS)
 """
-struct ValuesAsInModelContext{T,C<:AbstractContext} <: AbstractContext
+struct ValuesAsInModelContext{C<:AbstractContext} <: AbstractContext
     "values that are extracted from the model"
-    values::T
+    values::OrderedDict
     "whether to extract variables on the LHS of :="
     include_colon_eq::Bool
     "child context"
@@ -114,34 +114,32 @@ function dot_tilde_assume(
 end
 
 """
-    values_as_in_model(model::Model, include_colon_eq::Bool[, varinfo::AbstractVarInfo, context::AbstractContext])
-    values_as_in_model(rng::Random.AbstractRNG, model::Model, include_colon_eq::Bool[, varinfo::AbstractVarInfo, context::AbstractContext])
+    values_as_in_model(model::Model, include_colon_eq::Bool, varinfo::AbstractVarInfo[, context::AbstractContext])
 
 Get the values of `varinfo` as they would be seen in the model.
 
-If no `varinfo` is provided, then this is effectively the same as
-[`Base.rand(rng::Random.AbstractRNG, model::Model)`](@ref).
+More specifically, this method attempts to extract the realization _as seen in
+the model_. For example, `x[1] ~ truncated(Normal(); lower=0)` will result in a
+realization that is compatible with `truncated(Normal(); lower=0)` -- i.e. one
+where the value of `x[1]` is positive -- regardless of whether `varinfo` is
+working in unconstrained space.
 
-More specifically, this method attempts to extract the realization _as seen in the model_.
-For example, `x[1] ~ truncated(Normal(); lower=0)` will result in a realization compatible
-with `truncated(Normal(); lower=0)` regardless of whether `varinfo` is working in unconstrained
-space.
-
-Hence this method is a "safe" way of obtaining realizations in constrained space at the cost
-of additional model evaluations.
+Hence this method is a "safe" way of obtaining realizations in constrained
+space at the cost of additional model evaluations.
 
 # Arguments
 - `model::Model`: model to extract realizations from.
 - `include_colon_eq::Bool`: whether to also include variables on the LHS of `:=`.
 - `varinfo::AbstractVarInfo`: variable information to use for the extraction.
-- `context::AbstractContext`: context to use for the extraction. If `rng` is specified, then `context`
-    will be wrapped in a [`SamplingContext`](@ref) with the provided `rng`.
+- `context::AbstractContext`: base context to use for the extraction. Defaults
+   to `DynamicPPL.DefaultContext()`.
 
 # Examples
 
 ## When `VarInfo` fails
 
-The following demonstrates a common pitfall when working with [`VarInfo`](@ref) and constrained variables.
+The following demonstrates a common pitfall when working with [`VarInfo`](@ref)
+and constrained variables.
 
 ```jldoctest
 julia> using Distributions, StableRNGs
@@ -191,19 +189,10 @@ true
 function values_as_in_model(
     model::Model,
     include_colon_eq::Bool,
-    varinfo::AbstractVarInfo=VarInfo(),
+    varinfo::AbstractVarInfo,
     context::AbstractContext=DefaultContext(),
 )
     context = ValuesAsInModelContext(include_colon_eq, context)
     evaluate!!(model, varinfo, context)
     return context.values
 end
-function values_as_in_model(
-    rng::Random.AbstractRNG,
-    model::Model,
-    include_colon_eq::Bool,
-    varinfo::AbstractVarInfo=VarInfo(),
-    context::AbstractContext=DefaultContext(),
-)
-    return values_as_in_model(model, true, varinfo, SamplingContext(rng, context))
-end

test/model.jl

@@ -429,22 +429,6 @@ const GDEMO_DEFAULT = DynamicPPL.TestUtils.demo_assume_observe_literal()
                 end
             end
         end
-
-        @testset "check that sampling obeys rng if passed" begin
-            @model function f()
-                x ~ Normal(0)
-                return y ~ Normal(x)
-            end
-            model = f()
-            # Call values_as_in_model with the rng
-            values = values_as_in_model(Random.Xoshiro(43), model, false)
-            # Check that they match the values that would be used if vi was seeded
-            # with that seed instead
-            expected_vi = VarInfo(Random.Xoshiro(43), model)
-            for vn in keys(values)
-                @test values[vn] == expected_vi[vn]
-            end
-        end
     end
 
     @testset "Erroneous model call" begin