init_strategy

Author: penelopeysm

src/debug_utils.jl

@@ -520,7 +520,7 @@ function has_static_constraints(
     traces = map(last, results)
     dists_per_trace = map(distributions_in_trace, traces)
     transforms = map(dists_per_trace) do dists
-        map(Bijectors.bijector, dists)
+        map(DynamicPPL.link_transform, dists)
     end
 
     # Check if the distributions are the same across all runs.

src/sampler.jl

@@ -88,6 +88,14 @@ Default type of the chain of posterior samples from `sampler`.
 """
 default_chain_type(sampler::Sampler) = Any
 
+"""
+    init_strategy(sampler)
+
+Define the initialisation strategy used for generating initial values when
+sampling with `sampler`. Defaults to `PriorInit()`, but can be overridden.
+"""
+init_strategy(::Sampler) = PriorInit()
+
 """
     initialstep(rng, model, sampler, varinfo; kwargs...)
 

src/simple_varinfo.jl

@@ -620,7 +620,7 @@ from_internal_transform(vi::SimpleVarInfo, ::VarName, dist) = identity
 # TODO: Should the following methods specialize on the case where we have a `StaticTransformation{<:Bijectors.NamedTransform}`?
 from_linked_internal_transform(vi::SimpleVarInfo, ::VarName) = identity
 function from_linked_internal_transform(vi::SimpleVarInfo, ::VarName, dist)
-    return inverse(Bijectors.bijector(dist))
+    return invlink_transform(dist)
 end
 
 has_varnamedvector(vi::SimpleVarInfo) = vi.values isa VarNamedVector

src/transforming.jl

@@ -26,7 +26,7 @@ function tilde_assume(
 
     # Only transform if `!isinverse` since `vi[vn, right]`
     # already performs the inverse transformation if it's transformed.
-    r_transformed = isinverse ? r : Bijectors.bijector(right)(r)
+    r_transformed = isinverse ? r : link_transform(right)(r)
     if hasacc(vi, Val(:LogPrior))
         vi = acclogprior!!(vi, lp)
     end

src/utils.jl

@@ -197,6 +197,28 @@ function to_namedtuple_expr(syms, vals)
     return :(NamedTuple{$names_expr}($vals_expr))
 end
 
+"""
+    link_transform(dist)
+Return the constrained-to-unconstrained bijector for distribution `dist`.
+By default, this is just `Bijectors.bijector(dist)`.
+!!! warning
+    Note that currently this is not used by `Bijectors.logpdf_with_trans`,
+    hence that needs to be overloaded separately if the intention is
+    to change behavior of an existing distribution.
+"""
+link_transform(dist) = bijector(dist)
+
+"""
+    invlink_transform(dist)
+Return the unconstrained-to-constrained bijector for distribution `dist`.
+By default, this is just `inverse(link_transform(dist))`.
+!!! warning
+    Note that currently this is not used by `Bijectors.logpdf_with_trans`,
+    hence that needs to be overloaded separately if the intention is
+    to change behavior of an existing distribution.
+"""
+invlink_transform(dist) = inverse(link_transform(dist))
+
 #####################################################
 # Helper functions for vectorize/reconstruct values #
 #####################################################
@@ -355,14 +377,11 @@ from_vec_transform(f, sz) = from_vec_transform_for_size(Bijectors.output_size(f,
 Return the transformation from the unconstrained vector to the constrained
 realization of distribution `dist`.
 
-By default, this is just `inverse(bijector(dist)) ∘ from_vec_transform(dist)`.
-
-See also: [`DynamicPPL.from_vec_transform`](@ref).
+See also: [`DynamicPPL.invlink_transform`](@ref), [`DynamicPPL.from_vec_transform`](@ref).
 """
 function from_linked_vec_transform(dist::Distribution)
-    f_link = Bijectors.bijector(dist)
-    f_invlink = inverse(f_link)
-    f_vec = from_vec_transform(f_link, size(dist))
+    f_invlink = invlink_transform(dist)
+    f_vec = from_vec_transform(inverse(f_invlink), size(dist))
     return f_invlink ∘ f_vec
 end
 
@@ -372,9 +391,8 @@ end
 # TODO(mhauru) Hopefully all this can go once the old Gibbs sampler is removed and
 # VarNamedVector takes over from Metadata.
 function from_linked_vec_transform(dist::UnivariateDistribution)
-    f_link = Bijectors.bijector(dist)
-    f_invlink = inverse(f_link)
-    f_vec = from_vec_transform(f_link, size(dist))
+    f_invlink = invlink_transform(dist)
+    f_vec = from_vec_transform(inverse(f_invlink), size(dist))
     f_combined = f_invlink ∘ f_vec
     sz = Bijectors.output_size(f_combined, size(dist))
     return UnwrapSingletonTransform(sz) ∘ f_combined