Xianda Sun

Remove `BangBang.possible`

6

In light of https://github.com/JuliaFolds2/BangBang.jl/commit/e679bae34a531ad8adc7dc1d896028958be2e532, we can removed the code as they are implemented in BangBang. The changes has not been released, so should verify afterward. And this PR should **not**...

`BangBang.setindex!!(vi::SimpleVarInfo{<:AbstractDict}, val, vn::VarName)` returns eltype Any arrays when `vn` is multidimensional

1

MWE ```julia-repl julia> using DynamicPPL [ Info: Precompiling DynamicPPL [366bfd00-2699-11ea-058f-f148b4cae6d8] julia> svi = SimpleVarInfo(Dict(@varname(a)=>zeros(2, 2))) SimpleVarInfo(Dict(a => [0.0 0.0; 0.0 0.0]), 0.0) julia> DynamicPPL.setindex!!(svi, ones(2, 2), @varname(a[1:2, 1:2])) SimpleVarInfo(Dict{VarName{:a, Setfield.IdentityLens},...

Add `==` definition of `ComposedOptic` and `IndexLens` from `Setfield`

3

Fix https://github.com/JuliaObjects/Accessors.jl/issues/144 Pretty much copy and paste

`==` not defined for `IndexLens`

4

We are trying to update Turing.jl to using Accessors.jl in sync with BangBang (https://github.com/TuringLang/AbstractPPL.jl/pull/91) I noticed that `==` for `IndexLens` is not defined, (c.f. [Setfield's definition](https://github.com/jw3126/Setfield.jl/blob/e31e1e361bd6a251124aa578122e6198b81197b5/src/lens.jl#L196C40-L196C42)). Are there reasons this...

ref: https://github.com/TuringLang/Turing.jl/pull/2231#issuecomment-2192601314

Give user an option to use `SimpleVarInfo` with `sample` function

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Partially address https://github.com/TuringLang/Turing.jl/issues/2213 An example ```julia julia> using AbstractMCMC, DynamicPPL [...] julia> model = DynamicPPL.TestUtils.DEMO_MODELS[1] Model{typeof(DynamicPPL.TestUtils.demo_dot_assume_dot_observe), (:x, Symbol("##arg#289")), (), (), Tuple{Vector{Float64}, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DefaultContext}(DynamicPPL.TestUtils.demo_dot_assume_dot_observe, (x = [1.5, 2.0], var"##arg#289" =...

Add some interface functions to support the new Gibbs sampler in Turing

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The recent [new Gibbs sampler](https://github.com/TuringLang/Turing.jl/pull/2231) provides a way forward for the Turing inference stack. A near-to-medium-range goal has been to further reduce the glue code between Turing and inference packages...

Turing.jl error with AdvancedHMC

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```julia using Turing, Enzyme @model function hmcmatrixsup() return v ~ Wishart(7, [1 0.5; 0.5 1]) end model_f = hmcmatrixsup() rng = Turing.Random.default_rng() alg = HMC(0.15, 7; adtype=Turing.ADTypes.AutoEnzyme()) spl = Turing.Sampler(alg,...