MH Constructor (#2037)

* first draft

* abstractcontext + tests

* bug

* externalsampler() in tests

* Name Tupple problems

* moving stuff to DynamicPPL RP

* using new DynamicPPL PR

* mistakenly removed line

* specific constructors

* no StaticMH RWMH

* Bump bijectors compat (#2052)

* CompatHelper: bump compat for Bijectors to 0.13, (keep existing compat)

* Update Project.toml

* Replacement for #2039 (#2040)

* Fix testset for external samplers

* Update abstractmcmc.jl

* Update test/contrib/inference/abstractmcmc.jl

Co-authored-by: Tor Erlend Fjelde <[email protected]>

* Update test/contrib/inference/abstractmcmc.jl

Co-authored-by: Tor Erlend Fjelde <[email protected]>

* Update FillArrays compat to 1.4.1 (#2035)

* Update FillArrays compat to 1.4.0

* Update test compat

* Try to enable ReverseDiff tests

* Update Project.toml

* Update Project.toml

* Bump version

* Revert dependencies on FillArrays (#2042)

* Update Project.toml

* Update Project.toml

* Fix redundant definition of `getstats` (#2044)

* Fix redundant definition of `getstats`

* Update Inference.jl

* Revert "Update Inference.jl"

This reverts commit e4f51c2.

* Bump version

---------

Co-authored-by: Hong Ge <[email protected]>

* Transfer some test utility function into DynamicPPL (#2049)

* Update OptimInterface.jl

* Only run optimisation tests in numerical stage.

* fix function lookup after moving functions

---------

Co-authored-by: Xianda Sun <[email protected]>

* Move Optim support to extension (#2051)

* Move Optim support to extension

* More imports

* Update Project.toml

---------

Co-authored-by: Hong Ge <[email protected]>

---------

Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: haris organtzidis <[email protected]>
Co-authored-by: Tor Erlend Fjelde <[email protected]>
Co-authored-by: David Widmann <[email protected]>
Co-authored-by: Xianda Sun <[email protected]>
Co-authored-by: Cameron Pfiffer <[email protected]>

* Bugfixes.

* Add TODO.

* Update mh.jl

* Update Inference.jl

* Removed obsolete exports.

* removed unnecessary import of extract_priors

* added missing ) in MH tests

* fixed incorrect referneces to AdvancedMH in tests

* improve ESLogDensityFunction

* remove hardcoding of SimpleVarInfo

* added fixme comment

* minor style changes

* fixed issues with MH with RandomWalkProposal being used as an external sampler

* fixed accidental typo

* move definitions of unflatten for NamedTuple

* improved TODO

* Update Project.toml

---------

Co-authored-by: Hong Ge <[email protected]>
Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: haris organtzidis <[email protected]>
Co-authored-by: Tor Erlend Fjelde <[email protected]>
Co-authored-by: David Widmann <[email protected]>
Co-authored-by: Xianda Sun <[email protected]>
Co-authored-by: Cameron Pfiffer <[email protected]>
Co-authored-by: Hong Ge <[email protected]>

Author: 8 people

src/Turing.jl

@@ -73,7 +73,6 @@ export  @model,                 # modelling
         Prior,                  # Sampling from the prior
 
         MH,                     # classic sampling
-        RWMH,
         Emcee,
         ESS,
         Gibbs,

src/inference/Inference.jl

@@ -99,6 +99,24 @@ Wrap a sampler so it can be used as an inference algorithm.
 """
 externalsampler(sampler::AbstractSampler) = ExternalSampler(sampler)
 
+"""
+    ESLogDensityFunction
+
+A log density function for the External sampler.
+
+"""
+const ESLogDensityFunction{M<:Model,S<:Sampler{<:ExternalSampler},V<:AbstractVarInfo} = Turing.LogDensityFunction{V,M,<:DynamicPPL.DefaultContext}
+function LogDensityProblems.logdensity(f::ESLogDensityFunction, x::NamedTuple)
+    return DynamicPPL.logjoint(f.model, DynamicPPL.unflatten(f.varinfo, x))
+end
+
+# TODO: make a nicer `set_namedtuple!` and move these functions to DynamicPPL.
+function DynamicPPL.unflatten(vi::TypedVarInfo, θ::NamedTuple) 
+    set_namedtuple!(deepcopy(vi), θ)
+    return vi
+end
+DynamicPPL.unflatten(vi::SimpleVarInfo, θ::NamedTuple) = SimpleVarInfo(θ, vi.logp, vi.transformation)
+
 # Algorithm for sampling from the prior
 struct Prior <: InferenceAlgorithm end
 

src/inference/mh.jl

@@ -188,6 +188,20 @@ function MH(space...)
     return MH{tuple(syms...), typeof(proposals)}(proposals)
 end
 
+# Some of the proposals require working in unconstrained space.
+transform_maybe(proposal::AMH.Proposal) = proposal
+function transform_maybe(proposal::AMH.RandomWalkProposal)
+    return AMH.RandomWalkProposal(Bijectors.transformed(proposal.proposal))
+end
+
+function MH(model::Model; proposal_type=AMH.StaticProposal)
+    priors = DynamicPPL.extract_priors(model)
+    props = Tuple([proposal_type(prop) for prop in values(priors)])
+    vars = Tuple(map(Symbol, collect(keys(priors))))
+    priors = map(transform_maybe, NamedTuple{vars}(props))
+    return AMH.MetropolisHastings(priors)
+end
+
 #####################
 # Utility functions #
 #####################
@@ -346,6 +360,7 @@ end
 function should_link(varinfo, sampler, proposal::AdvancedMH.RandomWalkProposal)
     return true
 end
+# FIXME: This won't be hit unless `vals` are all the exactly same concrete type of `AdvancedMH.RandomWalkProposal`!
 function should_link(
     varinfo,
     sampler,

test/inference/mh.jl

@@ -17,6 +17,12 @@
 
         s4 = Gibbs(MH(:m), MH(:s))
         c4 = sample(gdemo_default, s4, N)
+
+        s5 = externalsampler(MH(gdemo_default, proposal_type=AdvancedMH.RandomWalkProposal))
+        c5 = sample(gdemo_default, s5, N)
+
+        s6 = externalsampler(MH(gdemo_default, proposal_type=AdvancedMH.StaticProposal))
+        c6 = sample(gdemo_default, s6, N)
     end
     @numerical_testset "mh inference" begin
         Random.seed!(125)