Change getlogjoint -> getlogjoint_internal where needed

Author: penelopeysm

ext/TuringDynamicHMCExt.jl

@@ -63,7 +63,7 @@ function DynamicPPL.initialstep(
 
     # Define log-density function.
     ℓ = DynamicPPL.LogDensityFunction(
-        model, DynamicPPL.getlogjoint, vi; adtype=spl.alg.adtype
+        model, DynamicPPL.getlogjoint_internal, vi; adtype=spl.alg.adtype
     )
 
     # Perform initial step.

src/mcmc/Inference.jl

@@ -19,6 +19,7 @@ using DynamicPPL:
     setlogp!!,
     getlogp,
     getlogjoint,
+    getlogjoint_internal,
     VarName,
     getsym,
     getdist,
@@ -136,11 +137,13 @@ end
 
 Transition(θ, lp) = Transition(θ, lp, nothing)
 function Transition(model::DynamicPPL.Model, vi::AbstractVarInfo, t)
+    # TODO(DPPL0.37/penelopeysm): Fix this
     θ = getparams(model, vi)
-    lp = getlogjoint(vi)
+    lp = getlogjoint_internal(vi)
     return Transition(θ, lp, getstats(t))
 end
 
+# TODO(DPPL0.37/penelopeysm): Add log-prior and log-likelihood terms as well
 function metadata(t::Transition)
     stat = t.stat
     if stat === nothing
@@ -150,9 +153,11 @@ function metadata(t::Transition)
     end
 end
 
+# TODO(DPPL0.37/penelopeysm): Fix this
 DynamicPPL.getlogjoint(t::Transition) = t.lp
 
 # Metadata of VarInfo object
+# TODO(DPPL0.37/penelopeysm): Add log-prior and log-likelihood terms as well
 metadata(vi::AbstractVarInfo) = (lp=getlogjoint(vi),)
 
 ##########################

src/mcmc/emcee.jl

@@ -72,7 +72,7 @@ function AbstractMCMC.step(
         vis[1],
         map(vis) do vi
             vi = DynamicPPL.link!!(vi, model)
-            AMH.Transition(vi[:], DynamicPPL.getlogjoint(vi), false)
+            AMH.Transition(vi[:], DynamicPPL.getlogjoint_internal(vi), false)
         end,
     )
 
@@ -87,7 +87,7 @@ function AbstractMCMC.step(
     densitymodel = AMH.DensityModel(
         Base.Fix1(
             LogDensityProblems.logdensity,
-            DynamicPPL.LogDensityFunction(model, DynamicPPL.getlogjoint, vi),
+            DynamicPPL.LogDensityFunction(model, DynamicPPL.getlogjoint_internal, vi),
         ),
     )
 

src/mcmc/external_sampler.jl

@@ -163,7 +163,7 @@ function AbstractMCMC.step(
 
     # Construct LogDensityFunction
     f = DynamicPPL.LogDensityFunction(
-        model, DynamicPPL.getlogjoint, varinfo; adtype=alg.adtype
+        model, DynamicPPL.getlogjoint_internal, varinfo; adtype=alg.adtype
     )
 
     # Then just call `AbstractMCMC.step` with the right arguments.

src/mcmc/gibbs.jl

@@ -568,7 +568,7 @@ function setparams_varinfo!!(
     params::AbstractVarInfo,
 )
     logdensity = DynamicPPL.LogDensityFunction(
-        model, DynamicPPL.getlogjoint, state.ldf.varinfo; adtype=sampler.alg.adtype
+        model, DynamicPPL.getlogjoint_internal, state.ldf.varinfo; adtype=sampler.alg.adtype
     )
     new_inner_state = setparams_varinfo!!(
         AbstractMCMC.LogDensityModel(logdensity), sampler, state.state, params

src/mcmc/hmc.jl

@@ -193,7 +193,7 @@ function DynamicPPL.initialstep(
     metricT = getmetricT(spl.alg)
     metric = metricT(length(theta))
     ldf = DynamicPPL.LogDensityFunction(
-        model, DynamicPPL.getlogjoint, vi; adtype=spl.alg.adtype
+        model, DynamicPPL.getlogjoint_internal, vi; adtype=spl.alg.adtype
     )
     lp_func = Base.Fix1(LogDensityProblems.logdensity, ldf)
     lp_grad_func = Base.Fix1(LogDensityProblems.logdensity_and_gradient, ldf)
@@ -308,7 +308,7 @@ end
 function get_hamiltonian(model, spl, vi, state, n)
     metric = gen_metric(n, spl, state)
     ldf = DynamicPPL.LogDensityFunction(
-        model, DynamicPPL.getlogjoint, vi; adtype=spl.alg.adtype
+        model, DynamicPPL.getlogjoint_internal, vi; adtype=spl.alg.adtype
     )
     lp_func = Base.Fix1(LogDensityProblems.logdensity, ldf)
     lp_grad_func = Base.Fix1(LogDensityProblems.logdensity_and_gradient, ldf)

src/mcmc/mh.jl

@@ -304,7 +304,7 @@ function propose!!(
 
     # Create a sampler and the previous transition.
     mh_sampler = AMH.MetropolisHastings(dt)
-    prev_trans = AMH.Transition(vt, DynamicPPL.getlogjoint(vi), false)
+    prev_trans = AMH.Transition(vt, DynamicPPL.getlogjoint_internal(vi), false)
 
     # Make a new transition.
     spl_model = DynamicPPL.contextualize(
@@ -313,7 +313,7 @@ function propose!!(
     densitymodel = AMH.DensityModel(
         Base.Fix1(
             LogDensityProblems.logdensity,
-            DynamicPPL.LogDensityFunction(spl_model, DynamicPPL.getlogjoint, vi),
+            DynamicPPL.LogDensityFunction(spl_model, DynamicPPL.getlogjoint_internal, vi),
         ),
     )
     trans, _ = AbstractMCMC.step(rng, densitymodel, mh_sampler, prev_trans)
@@ -341,7 +341,7 @@ function propose!!(
 
     # Create a sampler and the previous transition.
     mh_sampler = AMH.MetropolisHastings(spl.alg.proposals)
-    prev_trans = AMH.Transition(vals, DynamicPPL.getlogjoint(vi), false)
+    prev_trans = AMH.Transition(vals, DynamicPPL.getlogjoint_internal(vi), false)
 
     # Make a new transition.
     spl_model = DynamicPPL.contextualize(
@@ -350,7 +350,7 @@ function propose!!(
     densitymodel = AMH.DensityModel(
         Base.Fix1(
             LogDensityProblems.logdensity,
-            DynamicPPL.LogDensityFunction(spl_model, DynamicPPL.getlogjoint, vi),
+            DynamicPPL.LogDensityFunction(spl_model, DynamicPPL.getlogjoint_internal, vi),
         ),
     )
     trans, _ = AbstractMCMC.step(rng, densitymodel, mh_sampler, prev_trans)

src/mcmc/particle_mcmc.jl

@@ -147,7 +147,7 @@ end
 
 function SMCTransition(model::DynamicPPL.Model, vi::AbstractVarInfo, weight)
     theta = getparams(model, vi)
-    lp = DynamicPPL.getlogjoint(vi)
+    lp = DynamicPPL.getlogjoint_internal(vi)
     return SMCTransition(theta, lp, weight)
 end
 
@@ -323,7 +323,7 @@ varinfo(state::PGState) = state.vi
 
 function PGTransition(model::DynamicPPL.Model, vi::AbstractVarInfo, logevidence)
     theta = getparams(model, vi)
-    lp = DynamicPPL.getlogjoint(vi)
+    lp = DynamicPPL.getlogjoint_internal(vi)
     return PGTransition(theta, lp, logevidence)
 end
 

src/mcmc/sghmc.jl

@@ -200,7 +200,7 @@ end
 
 function SGLDTransition(model::DynamicPPL.Model, vi::AbstractVarInfo, stepsize)
     theta = getparams(model, vi)
-    lp = DynamicPPL.getlogjoint(vi)
+    lp = DynamicPPL.getlogjoint_internal(vi)
     return SGLDTransition(theta, lp, stepsize)
 end
 

test/mcmc/external_sampler.jl

@@ -21,7 +21,7 @@ function initialize_nuts(model::DynamicPPL.Model)
 
     # Create a LogDensityFunction
     f = DynamicPPL.LogDensityFunction(
-        model, DynamicPPL.getlogjoint, linked_vi; adtype=Turing.DEFAULT_ADTYPE
+        model, DynamicPPL.getlogjoint_internal, linked_vi; adtype=Turing.DEFAULT_ADTYPE
     )
 
     # Choose parameter dimensionality and initial parameter value