Merge branch 'tor/dppl-update' of github.com:TuringLang/Turing.jl into tor/dppl-update

Author: torfjelde

Project.toml

@@ -1,6 +1,6 @@
 name = "Turing"
 uuid = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
-version = "0.17.0"
+version = "0.17.1"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
@@ -44,7 +44,7 @@ DataStructures = "0.18"
 Distributions = "0.23.3, 0.24, 0.25"
 DistributionsAD = "0.6"
 DocStringExtensions = "0.8"
-DynamicPPL = "0.12.1, 0.13, 0.14"
+DynamicPPL = "0.14"
 EllipticalSliceSampling = "0.4"
 ForwardDiff = "0.10.3"
 Libtask = "0.4, 0.5.3"

src/modes/ModeEstimation.jl

@@ -28,6 +28,10 @@ struct OptimizationContext{C<:AbstractContext} <: AbstractContext
     context::C
 end
 
+DynamicPPL.NodeTrait(::OptimizationContext) = DynamicPPL.IsParent()
+DynamicPPL.childcontext(context::OptimizationContext) = context.context
+DynamicPPL.setchildcontext(::OptimizationContext, child) = OptimizationContext(child)
+
 # assume
 function DynamicPPL.tilde_assume(rng::Random.AbstractRNG, ctx::OptimizationContext, spl, dist, vn, inds, vi)
     return DynamicPPL.tilde_assume(ctx, spl, dist, vn, inds, vi)
@@ -43,16 +47,6 @@ function DynamicPPL.tilde_assume(ctx::OptimizationContext, spl, dist, vn, inds,
     return r, Distributions.logpdf(dist, r)
 end
 
-
-# observe
-function DynamicPPL.tilde_observe(ctx::OptimizationContext, sampler, right, left, vi)
-    return DynamicPPL.observe(right, left, vi)
-end
-
-function DynamicPPL.tilde_observe(ctx::OptimizationContext{<:PriorContext}, sampler, right, left, vi)
-    return 0
-end
-
 # dot assume
 function DynamicPPL.dot_tilde_assume(rng::Random.AbstractRNG, ctx::OptimizationContext, sampler, right, left, vns, inds, vi)
     return DynamicPPL.dot_tilde_assume(ctx, sampler, right, left, vns, inds, vi)
@@ -72,26 +66,6 @@ function DynamicPPL.dot_tilde_assume(ctx::OptimizationContext, sampler::SampleFr
     return r, loglikelihood(right, r)
 end
 
-# dot observe
-function DynamicPPL.dot_tilde_observe(ctx::OptimizationContext{<:PriorContext}, sampler, right, left, vn, _, vi)
-    return 0
-end
-
-function DynamicPPL.dot_tilde_observe(ctx::OptimizationContext{<:PriorContext}, sampler, right, left, vi)
-    return 0
-end
-
-function DynamicPPL.dot_tilde_observe(ctx::OptimizationContext, sampler::SampleFromPrior, right, left, vns, _, vi)
-    # Values should be set and we're using `SampleFromPrior`, hence the `rng` argument shouldn't
-    # affect anything.
-    r = DynamicPPL.get_and_set_val!(Random.GLOBAL_RNG, vi, vns, right, sampler)
-    return loglikelihood(right, r)
-end
-
-function DynamicPPL.dot_tilde_observe(ctx::OptimizationContext, sampler, dists, value, vi)
-    return sum(Distributions.logpdf.(dists, value))
-end
-
 """
     OptimLogDensity{M<:Model,C<:Context,V<:VarInfo}
 

test/Project.toml

@@ -37,7 +37,7 @@ CmdStan = "6.0.8"
 Distributions = "< 0.25.11"
 DistributionsAD = "0.6.3"
 DynamicHMC = "2.1.6, 3.0"
-DynamicPPL = "0.12, 0.13, 0.14"
+DynamicPPL = "0.14"
 FiniteDifferences = "0.10.8, 0.11, 0.12"
 ForwardDiff = "0.10.12"
 MCMCChains = "4.13.0"