Remove tonamedtuple (#547)

* Remove dependencies to `tonamedtuple`

* Remove `tonamedtuple`s

* Minor version bump

---------

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

Author: sunxd3

Project.toml

@@ -1,6 +1,6 @@
 name = "DynamicPPL"
 uuid = "366bfd00-2699-11ea-058f-f148b4cae6d8"
-version = "0.23.21"
+version = "0.24.0"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"

docs/src/api.md

@@ -258,7 +258,6 @@ DynamicPPL.reconstruct
 Base.merge(::AbstractVarInfo)
 DynamicPPL.subset
 DynamicPPL.unflatten
-DynamicPPL.tonamedtuple
 DynamicPPL.varname_leaves
 DynamicPPL.varname_and_value_leaves
 ```

src/DynamicPPL.jl

@@ -71,7 +71,6 @@ export AbstractVarInfo,
     invlink,
     invlink!,
     invlink!!,
-    tonamedtuple,
     values_as,
     # VarName (reexport from AbstractPPL)
     VarName,

src/abstract_varinfo.jl

@@ -738,21 +738,6 @@ function unflatten(sampler::AbstractSampler, varinfo::AbstractVarInfo, ::Abstrac
     return unflatten(varinfo, sampler, θ)
 end
 
-"""
-    tonamedtuple(vi::AbstractVarInfo)
-
-Convert a `vi` into a `NamedTuple` where each variable symbol maps to the values and 
-indexing string of the variable.
-
-For example, a model that had a vector of vector-valued
-variables `x` would return
-
-```julia
-(x = ([1.5, 2.0], [3.0, 1.0], ["x[1]", "x[2]"]), )
-```
-"""
-function tonamedtuple end
-
 # TODO: Clean up all this linking stuff once and for all!
 """
     with_logabsdet_jacobian_and_reconstruct([f, ]dist, x)

src/simple_varinfo.jl

@@ -532,44 +532,6 @@ function dot_assume(
     return value, lp, vi
 end
 
-# We need these to be compatible with how chains are constructed from `AbstractVarInfo` in Turing.jl.
-# TODO: Move away from using these `tonamedtuple` methods.
-function tonamedtuple(vi::SimpleOrThreadSafeSimple{<:NamedTuple{names}}) where {names}
-    nt_vals = map(keys(vi)) do vn
-        val = vi[vn]
-        vns = collect(TestUtils.varname_leaves(vn, val))
-        vals = map(copy ∘ Base.Fix1(getindex, vi), vns)
-        (vals, map(string, vns))
-    end
-
-    return NamedTuple{names}(nt_vals)
-end
-
-function tonamedtuple(vi::SimpleOrThreadSafeSimple{<:Dict})
-    syms_to_result = Dict{Symbol,Tuple{Vector{Real},Vector{String}}}()
-    for vn in keys(vi)
-        # Extract the leaf varnames and values.
-        val = vi[vn]
-        vns = collect(TestUtils.varname_leaves(vn, val))
-        vals = map(copy ∘ Base.Fix1(getindex, vi), vns)
-
-        # Determine the corresponding symbol.
-        sym = only(unique(map(getsym, vns)))
-
-        # Initialize entry if not yet initialized.
-        if !haskey(syms_to_result, sym)
-            syms_to_result[sym] = (Real[], String[])
-        end
-
-        # Combine with old result.
-        old_vals, old_string_vns = syms_to_result[sym]
-        syms_to_result[sym] = (vcat(old_vals, vals), vcat(old_string_vns, map(string, vns)))
-    end
-
-    # Construct `NamedTuple`.
-    return NamedTuple(pairs(syms_to_result))
-end
-
 # NOTE: We don't implement `settrans!!(vi, trans, vn)`.
 function settrans!!(vi::SimpleVarInfo, trans)
     return settrans!!(vi, trans ? DynamicTransformation() : NoTransformation())

src/threadsafe.jl

@@ -209,8 +209,6 @@ function is_flagged(vi::ThreadSafeVarInfo, vn::VarName, flag::String)
     return is_flagged(vi.varinfo, vn, flag)
 end
 
-tonamedtuple(vi::ThreadSafeVarInfo) = tonamedtuple(vi.varinfo)
-
 # Transformations.
 function settrans!!(vi::ThreadSafeVarInfo, trans::Bool, vn::VarName)
     return Setfield.@set vi.varinfo = settrans!!(vi.varinfo, trans, vn)

src/varinfo.jl

@@ -1506,22 +1506,6 @@ end
     return expr
 end
 
-# TODO: Remove this completely.
-tonamedtuple(varinfo::VarInfo) = tonamedtuple(varinfo.metadata, varinfo)
-function tonamedtuple(metadata::NamedTuple{names}, varinfo::VarInfo) where {names}
-    length(names) === 0 && return NamedTuple()
-
-    vals_tuple = map(values(metadata)) do x
-        # NOTE: `tonamedtuple` is really only used in Turing.jl to convert to
-        # a "transition". This means that we really don't mutations of the values
-        # in `varinfo` to propoagate the previous samples. Hence we `copy.`
-        vals = map(copy ∘ Base.Fix1(getindex, varinfo), x.vns)
-        return vals, map(string, x.vns)
-    end
-
-    return NamedTuple{names}(vals_tuple)
-end
-
 @inline function findvns(vi, f_vns)
     if length(f_vns) == 0
         throw("Unidentified error, please report this error in an issue.")

test/test_util.jl

@@ -58,22 +58,22 @@ function test_setval!(model, chain; sample_idx=1, chain_idx=1)
     DynamicPPL.setval!(var_info, chain, sample_idx, chain_idx)
     θ_new = var_info[spl]
     @test θ_old != θ_new
-    nt = DynamicPPL.tonamedtuple(var_info)
-    for (k, (vals, names)) in pairs(nt)
-        for (n, v) in zip(names, vals)
-            if Symbol(n) ∉ keys(chain)
-                # Assume it's a group
-                chain_val = vec(
-                    MCMCChains.group(chain, Symbol(n)).value[sample_idx, :, chain_idx]
-                )
-                v_true = vec(v)
-            else
-                chain_val = chain[sample_idx, n, chain_idx]
-                v_true = v
-            end
-
-            @test v_true == chain_val
+    vals = DynamicPPL.values_as(var_info, OrderedDict)
+    iters = map(DynamicPPL.varname_and_value_leaves, keys(vals), values(vals))
+    for (n, v) in mapreduce(collect, vcat, iters)
+        n = string(n)
+        if Symbol(n) ∉ keys(chain)
+            # Assume it's a group
+            chain_val = vec(
+                MCMCChains.group(chain, Symbol(n)).value[sample_idx, :, chain_idx]
+            )
+            v_true = vec(v)
+        else
+            chain_val = chain[sample_idx, n, chain_idx]
+            v_true = v
         end
+
+        @test v_true == chain_val
     end
 end