Try #454:

Project.toml

@@ -1,6 +1,6 @@
 name = "DynamicPPL"
 uuid = "366bfd00-2699-11ea-058f-f148b4cae6d8"
-version = "0.21.6"
+version = "0.22.0"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
@@ -24,7 +24,7 @@ ZygoteRules = "700de1a5-db45-46bc-99cf-38207098b444"
 AbstractMCMC = "2, 3.0, 4"
 AbstractPPL = "0.5.3"
 BangBang = "0.3"
-Bijectors = "0.5.2, 0.6, 0.7, 0.8, 0.9, 0.10"
+Bijectors = "0.11"
 ChainRulesCore = "0.9.7, 0.10, 1"
 ConstructionBase = "1"
 Distributions = "0.23.8, 0.24, 0.25"

src/abstract_varinfo.jl

@@ -405,7 +405,7 @@ end
 
 # Vector-based ones.
 function link!!(
-    t::StaticTransformation{<:Bijectors.Bijector{1}},
+    t::StaticTransformation{<:Bijectors.Transform},
     vi::AbstractVarInfo,
     spl::AbstractSampler,
     model::Model,
@@ -420,7 +420,7 @@ function link!!(
 end
 
 function invlink!!(
-    t::StaticTransformation{<:Bijectors.Bijector{1}},
+    t::StaticTransformation{<:Bijectors.Transform},
     vi::AbstractVarInfo,
     spl::AbstractSampler,
     model::Model,
@@ -452,9 +452,8 @@ julia> using DynamicPPL, Distributions, Bijectors
 julia> @model demo() = x ~ Normal()
 demo (generic function with 2 methods)
 
-julia> # By subtyping `Bijector{1}`, we inherit the `(inv)link!!` defined for
-       # bijectors which acts on 1-dimensional arrays, i.e. vectors.
-       struct MyBijector <: Bijectors.Bijector{1} end
+julia> # By subtyping `Transform`, we inherit the `(inv)link!!`.
+       struct MyBijector <: Bijectors.Transform end
 
 julia> # Define some dummy `inverse` which will be used in the `link!!` call.
        Bijectors.inverse(f::MyBijector) = identity

src/simple_varinfo.jl

@@ -648,7 +648,7 @@ Distributions.loglikelihood(model::Model, θ) = loglikelihood(model, SimpleVarIn
 
 # Allow usage of `NamedBijector` too.
 function link!!(
-    t::StaticTransformation{<:Bijectors.NamedBijector},
+    t::StaticTransformation{<:Bijectors.NamedTransform},
     vi::SimpleVarInfo{<:NamedTuple},
     spl::AbstractSampler,
     model::Model,
@@ -663,7 +663,7 @@ function link!!(
 end
 
 function invlink!!(
-    t::StaticTransformation{<:Bijectors.NamedBijector},
+    t::StaticTransformation{<:Bijectors.NamedTransform},
     vi::SimpleVarInfo{<:NamedTuple},
     spl::AbstractSampler,
     model::Model,

src/test_utils.jl

@@ -686,7 +686,7 @@ Simple model for which [`default_transformation`](@ref) returns a [`StaticTransf
 end
 
 function DynamicPPL.default_transformation(::Model{typeof(demo_static_transformation)})
-    b = Bijectors.stack(Bijectors.Exp{0}(), Bijectors.Identity{0}())
+    b = Bijectors.stack(Bijectors.elementwise(exp), identity)
     return DynamicPPL.StaticTransformation(b)
 end
 

test/Project.toml

@@ -23,7 +23,7 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 [compat]
 AbstractMCMC = "2.1, 3.0, 4"
 AbstractPPL = "0.5.1, 0.6"
-Bijectors = "0.9.5, 0.10"
+Bijectors = "0.11"
 Distributions = "0.25"
 DistributionsAD = "0.6.3"
 Documenter = "0.26.1, 0.27"

test/simple_varinfo.jl

@@ -64,6 +64,7 @@
         @testset "$(typeof(vi))" for vi in (
             SimpleVarInfo(Dict()), SimpleVarInfo(values_constrained), VarInfo(model)
         )
+            vi = SimpleVarInfo(values_constrained)
             for vn in DynamicPPL.TestUtils.varnames(model)
                 vi = DynamicPPL.setindex!!(vi, get(values_constrained, vn), vn)
             end
@@ -108,6 +109,8 @@
 
     @testset "SimpleVarInfo on $(nameof(model))" for model in
                                                      DynamicPPL.TestUtils.DEMO_MODELS
+        model = DynamicPPL.TestUtils.demo_dot_assume_matrix_dot_observe_matrix()
+
         # We might need to pre-allocate for the variable `m`, so we need
         # to see whether this is the case.
         svi_nt = SimpleVarInfo(rand(NamedTuple, model))