Argument parent in constructor of Sampler

Author: KDr2

src/Turing.jl

@@ -91,13 +91,13 @@ Turing translates models to chunks that call the modelling functions at specifie
 then include that file at the end of this one.
 """
 mutable struct Sampler{T} <: AbstractSampler
-    parent   ::  AbstractSampler
     alg      ::  T
     info     ::  Dict{Symbol, Any} # sampler infomation
     selector ::  Selector
+    parent   ::  AbstractSampler
 end
-Sampler(alg, model::Model) = Sampler(alg)
-Sampler(alg, info::Dict{Symbol, Any}) = Sampler(SampleFromPrior(), alg, info, Selector())
+Sampler(alg, model::Model, parent=SampleFromPrior()) = Sampler(alg, parent)
+Sampler(alg, info::Dict{Symbol, Any}, parent=SampleFromPrior()) = Sampler(alg, info, Selector(), parent)
 
 include("utilities/Utilities.jl")
 using .Utilities

src/inference/dynamichmc.jl

@@ -32,8 +32,8 @@ function DynamicNUTS{AD}(n_iters::Integer, space...) where AD
     DynamicNUTS{AD, eltype(_space)}(n_iters, _space)
 end
 
-function Sampler(alg::DynamicNUTS{T}) where T <: Hamiltonian
-  return Sampler(alg, Dict{Symbol,Any}())
+function Sampler(alg::DynamicNUTS{T}, parent=SampleFromPrior()) where T <: Hamiltonian
+  return Sampler(alg, Dict{Symbol,Any}(), parent)
 end
 
 function sample(model::Model,

src/inference/gibbs.jl

@@ -33,9 +33,9 @@ Gibbs(n_iters::Int, algs...; thin=true) = Gibbs(n_iters, algs, thin)
 
 const GibbsComponent = Union{Hamiltonian,MH,PG}
 
-function Sampler(alg::Gibbs, model::Model)
+function Sampler(alg::Gibbs, model::Model, parent=SampleFromPrior())
     info = Dict{Symbol, Any}()
-    spl = Sampler(alg, info)
+    spl = Sampler(alg, info, parent)
 
     n_samplers = length(alg.algs)
     samplers = Array{Sampler}(undef, n_samplers)
@@ -44,8 +44,7 @@ function Sampler(alg::Gibbs, model::Model)
     for i in 1:n_samplers
         sub_alg = alg.algs[i]
         if isa(sub_alg, GibbsComponent)
-            samplers[i] = Sampler(sub_alg, model)
-            samplers[i].parent = spl
+            samplers[i] = Sampler(sub_alg, model, spl)
         else
             @error("[Gibbs] unsupport base sampling algorithm $alg")
         end

src/inference/hmc.jl

@@ -74,11 +74,11 @@ end
 DEFAULT_ADAPT_CONF_TYPE = Nothing
 STAN_DEFAULT_ADAPT_CONF = nothing
 
-Sampler(alg::Hamiltonian) =  Sampler(alg, nothing)
-function Sampler(alg::Hamiltonian, adapt_conf::Nothing)
-    return _sampler(alg::Hamiltonian, adapt_conf)
+Sampler(alg::Hamiltonian, parent=SampleFromPrior()) =  Sampler(alg, nothing, parent)
+function Sampler(alg::Hamiltonian, adapt_conf::Nothing, parent=SampleFromPrior())
+    return _sampler(alg::Hamiltonian, adapt_conf, parent)
 end
-function _sampler(alg::Hamiltonian, adapt_conf)
+function _sampler(alg::Hamiltonian, adapt_conf, parent=SampleFromPrior())
     info=Dict{Symbol, Any}()
 
     # For state infomation
@@ -88,7 +88,7 @@ function _sampler(alg::Hamiltonian, adapt_conf)
     # Adapt configuration
     info[:adapt_conf] = adapt_conf
 
-    Sampler(alg, info)
+    Sampler(alg, info, parent)
 end
 
 function sample(model::Model, alg::Hamiltonian;

src/inference/ipmcmc.jl

@@ -52,22 +52,20 @@ function IPMCMC(n1::Int, n2::Int, n3::Int, n4::Int, space...)
   IPMCMC(n1, n2, n3, n4, resample_systematic, _space)
 end
 
-function Sampler(alg::IPMCMC)
+function Sampler(alg::IPMCMC, parent=SampleFromPrior())
   info = Dict{Symbol, Any}()
-  spl = Sampler(alg, info)
+  spl = Sampler(alg, info, parent)
   # Create SMC and CSMC nodes
   samplers = Array{Sampler}(undef, alg.n_nodes)
   # Use resampler_threshold=1.0 for SMC since adaptive resampling is invalid in this setting
   default_CSMC = CSMC(alg.n_particles, 1, alg.resampler, alg.space)
   default_SMC = SMC(alg.n_particles, alg.resampler, 1.0, false, alg.space)
 
   for i in 1:alg.n_csmc_nodes
-    samplers[i] = Sampler(default_CSMC)
-    samplers[i].parent = spl
+    samplers[i] = Sampler(default_CSMC, spl)
   end
   for i in (alg.n_csmc_nodes+1):alg.n_nodes
-    samplers[i] = Sampler(default_SMC)
-    samplers[i].parent = spl
+    samplers[i] = Sampler(default_SMC, spl)
   end
 
   info[:samplers] = samplers

src/inference/mh.jl

@@ -48,12 +48,11 @@ function MH(n_iters::Int, space...)
   MH{eltype(set)}(n_iters, proposals, set)
 end
 
-function Sampler(alg::MH, model::Model)
+function Sampler(alg::MH, model::Model, parent=SampleFromPrior())
     alg_str = "MH"
 
     # Sanity check for space
-    # TODO if (we are going to create a top-level Sampler) && !isempty(alg.space)
-    if false && !isempty(alg.space)
+    if parent == SampleFromPrior() && !isempty(alg.space)
         @assert issubset(Set(get_pvars(model)), alg.space) "[$alg_str] symbols specified to samplers ($alg.space) doesn't cover the model parameters ($(Set(get_pvars(model))))"
         if Set(get_pvars(model)) != alg.space
             warn("[$alg_str] extra parameters specified by samplers don't exist in model: $(setdiff(alg.space, Set(get_pvars(model))))")
@@ -65,7 +64,7 @@ function Sampler(alg::MH, model::Model)
     info[:prior_prob] = 0.0
     info[:violating_support] = false
 
-    return Sampler(alg, info)
+    return Sampler(alg, info, parent)
 end
 
 function propose(model, spl::Sampler{<:MH}, vi::VarInfo)

src/inference/pgibbs.jl

@@ -41,10 +41,10 @@ end
 
 const CSMC = PG # type alias of PG as Conditional SMC
 
-function Sampler(alg::PG)
+function Sampler(alg::PG, parent=SampleFromPrior())
     info = Dict{Symbol, Any}()
     info[:logevidence] = []
-    Sampler(alg, info)
+    Sampler(alg, info, parent)
 end
 
 step(model, spl::Sampler{<:PG}, vi::VarInfo, _) = step(model, spl, vi)

src/inference/pmmh.jl

@@ -32,9 +32,9 @@ end
 
 PIMH(n_iters::Int, smc_alg::SMC) = PMMH(n_iters, tuple(smc_alg), Set())
 
-function Sampler(alg::PMMH, model::Model)
+function Sampler(alg::PMMH, model::Model, parent=SampleFromPrior())
     info = Dict{Symbol, Any}()
-    spl = Sampler(alg, info)
+    spl = Sampler(alg, info, parent)
 
     alg_str = "PMMH"
     n_samplers = length(alg.algs)
@@ -45,8 +45,7 @@ function Sampler(alg::PMMH, model::Model)
     for i in 1:n_samplers
         sub_alg = alg.algs[i]
         if isa(sub_alg, Union{SMC, MH})
-            samplers[i] = Sampler(sub_alg, model)
-            samplers[i].parent = spl
+            samplers[i] = Sampler(sub_alg, model, spl)
         else
             error("[$alg_str] unsupport base sampling algorithm $alg")
         end