Remove Sampler and its interface

HISTORY.md

@@ -42,6 +42,18 @@ The main change that this is likely to create is for those who are implementing
 The exact way in which this happens will be detailed in the Turing.jl changelog when a new release is made.
 Broadly speaking, though, `SamplingContext(MySampler())` will be removed so if your sampler needs custom behaviour with the tilde-pipeline you will likely have to define your own context.
 
+### Removal of `DynamicPPL.Sampler`
+
+`DynamicPPL.Sampler` and **all associated interface functions** have also been removed entirely.
+If you were using these, the corresponding replacements are:
+
+  - `DynamicPPL.Sampler(S)`: just don't wrap `S`; but make sure `S` subtypes `AbstractMCMC.AbstractSampler`
+  - `DynamicPPL.initialstep`: directly implement `AbstractMCMC.step` and `AbstractMCMC.step_warmup` as per the AbstractMCMC interface
+  - `DynamicPPL.loadstate`: `Turing.loadstate` (will be introduced in the next version)
+  - `DynamicPPL.default_chain_type`: `Turing.default_chain_type` (will be introduced in the next version)
+  - `DynamicPPL.initialsampler`: `Turing.init_strategy` (will be introduced in the next version; note that this function must return an `AbstractInitStrategy`, see above for explanation)
+  - `DynamicPPL.default_varinfo`: `Turing.default_varinfo` (will be introduced in the next version)
+
 ### Simplification of the tilde-pipeline
 
 There are now only two functions in the tilde-pipeline that need to be overloaded to change the behaviour of tilde-statements, namely, `tilde_assume!!` and `tilde_observe!!`.

docs/src/api.md

@@ -504,27 +504,7 @@ DynamicPPL.AbstractInitStrategy
 DynamicPPL.init
 ```
 
-### Samplers
-
-In DynamicPPL a generic sampler for inference is implemented.
-
-```@docs
-Sampler
-```
-
-The default implementation of [`Sampler`](@ref) uses the following unexported functions.
-
-```@docs
-DynamicPPL.initialstep
-DynamicPPL.loadstate
-DynamicPPL.init_strategy
-```
-
-Finally, to specify which varinfo type a [`Sampler`](@ref) should use for a given [`Model`](@ref), this is specified by [`DynamicPPL.default_varinfo`](@ref) and can thus be overloaded for each  `model`-`sampler` combination. This can be useful in cases where one has explicit knowledge that one type of varinfo will be more performant for the given `model` and `sampler`.
-
-```@docs
-DynamicPPL.default_varinfo
-```
+### Choosing a suitable VarInfo
 
 There is also the _experimental_ [`DynamicPPL.Experimental.determine_suitable_varinfo`](@ref), which uses static checking via [JET.jl](https://github.com/aviatesk/JET.jl) to determine whether one should use [`DynamicPPL.typed_varinfo`](@ref) or [`DynamicPPL.untyped_varinfo`](@ref), depending on which supports the model:
 

ext/DynamicPPLMCMCChainsExt.jl

@@ -3,18 +3,6 @@ module DynamicPPLMCMCChainsExt
 using DynamicPPL: DynamicPPL, AbstractPPL
 using MCMCChains: MCMCChains
 
-# Load state from a `Chains`: By convention, it is stored in `:samplerstate` metadata
-function DynamicPPL.loadstate(chain::MCMCChains.Chains)
-    if !haskey(chain.info, :samplerstate)
-        throw(
-            ArgumentError(
-                "The chain object does not contain the final state of the sampler: Metadata `:samplerstate` missing.",
-            ),
-        )
-    end
-    return chain.info[:samplerstate]
-end
-
 _has_varname_to_symbol(info::NamedTuple{names}) where {names} = :varname_to_symbol in names
 
 function DynamicPPL.supports_varname_indexing(chain::MCMCChains.Chains)

src/DynamicPPL.jl

@@ -92,8 +92,6 @@ export AbstractVarInfo,
     getargnames,
     extract_priors,
     values_as_in_model,
-    # Samplers
-    Sampler,
     # LogDensityFunction
     LogDensityFunction,
     # Contexts
@@ -128,8 +126,6 @@ export AbstractVarInfo,
     prefix,
     returned,
     to_submodel,
-    # Chain save/resume
-    loadstate,
     # Convenience macros
     @addlogprob!,
     value_iterator_from_chain,
@@ -181,7 +177,6 @@ include("contexts/transformation.jl")
 include("contexts/prefix.jl")
 include("contexts/conditionfix.jl")  # Must come after contexts/prefix.jl
 include("model.jl")
-include("sampler.jl")
 include("varname.jl")
 include("distribution_wrappers.jl")
 include("submodel.jl")

test/runtests.jl

@@ -61,7 +61,6 @@ include("test_util.jl")
         include("varinfo.jl")
         include("simple_varinfo.jl")
         include("model.jl")
-        include("sampler.jl")
         include("distribution_wrappers.jl")
         include("logdensityfunction.jl")
         include("linking.jl")