UndefVarError: tempered not defined

[vembha]

Hello. I am new to MCMCTempering.jl package and recently started using. As per the tutorial, I tried to use the function tempered(sampler, temperature_steps) with the default NUTS() sampler from Turing.jl. But it looks like I there is not function named tempered at all. There is one Tempered with the capital T, but when I use it, the sampler throws the following error:

ERROR: MethodError: no method matching make_tempered_model(::DynamicPPL.Model{typeof(truth_data_fitting!), (:data, :ODEtspan, :num_variants, :tot_pop, :interp_IPTCC, :interp_mobil), (), (), Tuple{DataFrame, Tuple{Float64, Float64}, Int64, Int64, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}}, Tuple{}, DynamicPPL.DefaultContext}, ::Float64)
Stacktrace:
[1] (::MCMCTempering.var"#5#6"{Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Random._GLOBAL_RNG, DynamicPPL.Model{typeof(truth_data_fitting!), (:data, :ODEtspan, :num_variants, :tot_pop, :interp_IPTCC, :interp_mobil), (), (), Tuple{DataFrame, Tuple{Float64, Float64}, Int64, Int64, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}},
Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}}, Tuple{}, DynamicPPL.DefaultContext}, TemperedSampler{NUTS{Turing.Essential.ForwardDiffAD{40}, (), DiagEuclideanMetric}}})(Δi::Int64)
@ MCMCTempering .\none:0
[2] iterate
@ .\generator.jl:47 [inlined]
[3] collect(itr::Base.Generator{Vector{Int64}, MCMCTempering.var"#5#6"{Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Random._GLOBAL_RNG, DynamicPPL.Model{typeof(truth_data_fitting!), (:data, :ODEtspan, :num_variants, :tot_pop, :interp_IPTCC, :interp_mobil), (), (), Tuple{DataFrame, Tuple{Float64, Float64}, Int64, Int64, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}}, Tuple{}, DynamicPPL.DefaultContext}, TemperedSampler{NUTS{Turing.Essential.ForwardDiffAD{40}, (), DiagEuclideanMetric}}}})
@ Base .\array.jl:678
[4] step(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(truth_data_fitting!), (:data, :ODEtspan, :num_variants, :tot_pop, :interp_IPTCC, :interp_mobil), (), (), Tuple{DataFrame, Tuple{Float64, Float64}, Int64, Int64, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}}, Tuple{}, DynamicPPL.DefaultContext}, spl::TemperedSampler{NUTS{Turing.Essential.ForwardDiffAD{40}, (), DiagEuclideanMetric}}; kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ MCMCTempering C:\Users\Bharadwaj.julia\packages\MCMCTempering\ALY2z\src\stepping.jl:37
[5] step
@ C:\Users\Bharadwaj.julia\packages\MCMCTempering\ALY2z\src\stepping.jl:37 [inlined]
[6] macro expansion
@ C:\Users\Bharadwaj.julia\packages\AbstractMCMC\BPJCW\src\sample.jl:123 [inlined]
[7] macro expansion
@ C:\Users\Bharadwaj.julia\packages\ProgressLogging\6KXlp\src\ProgressLogging.jl:328 [inlined]
[8] macro expansion
@ C:\Users\Bharadwaj.julia\packages\AbstractMCMC\BPJCW\src\logging.jl:8 [inlined]
[9] mcmcsample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(truth_data_fitting!), (:data, :ODEtspan, :num_variants, :tot_pop, :interp_IPTCC, :interp_mobil), (), (), Tuple{DataFrame, Tuple{Float64, Float64}, Int64, Int64, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}, Interpolations.BSplineInterpolation{Float64, 1, Vector{Float64}, BSpline{Linear{Throw{OnGrid}}}, Tuple{Base.OneTo{Int64}}}}, Tuple{}, DynamicPPL.DefaultContext}, sampler::TemperedSampler{NUTS{Turing.Essential.ForwardDiffAD{40}, (), DiagEuclideanMetric}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, discard_initial::Int64, thinning::Int64, chain_type::Type, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ AbstractMCMC C:\Users\Bharadwaj.julia\packages\AbstractMCMC\BPJCW\src\sample.jl:114
[10] #sample#16
@ C:\Users\Bharadwaj.julia\packages\AbstractMCMC\BPJCW\src\sample.jl:36 [inlined]
[11] #sample#15
@ C:\Users\Bharadwaj.julia\packages\AbstractMCMC\BPJCW\src\sample.jl:21 [inlined]
[12] top-level scope
@ REPL[53]:1

Can someone help me out, please? Following are my packages on Windows 10:
Julia 1.6.2
[ce233488] MCMCTempering v0.1.1
[fce5fe82] Turing v0.20.1

[yebai]

Likely fixed now.