Remove unused code (#2312)

src/mcmc/hmc.jl

@@ -563,58 +563,3 @@ end
 function AHMCAdaptor(::Hamiltonian, ::AHMC.AbstractMetric; kwargs...)
     return AHMC.Adaptation.NoAdaptation()
 end
-
-##########################
-# HMC State Constructors #
-##########################
-
-function HMCState(
-    rng::AbstractRNG,
-    model::Model,
-    spl::Sampler{<:Hamiltonian},
-    vi::AbstractVarInfo;
-    kwargs...,
-)
-    # Link everything if needed.
-    waslinked = islinked(vi, spl)
-    if !waslinked
-        vi = link!!(vi, spl, model)
-    end
-
-    # Get the initial log pdf and gradient functions.
-    ∂logπ∂θ = gen_∂logπ∂θ(vi, spl, model)
-    logπ = Turing.LogDensityFunction(
-        vi,
-        model,
-        DynamicPPL.SamplingContext(rng, spl, DynamicPPL.leafcontext(model.context)),
-    )
-
-    # Get the metric type.
-    metricT = getmetricT(spl.alg)
-
-    # Create a Hamiltonian.
-    θ_init = Vector{Float64}(spl.state.vi[spl])
-    metric = metricT(length(θ_init))
-    h = AHMC.Hamiltonian(metric, logπ, ∂logπ∂θ)
-
-    # Find good eps if not provided one
-    if iszero(spl.alg.ϵ)
-        ϵ = AHMC.find_good_stepsize(rng, h, θ_init)
-        @info "Found initial step size" ϵ
-    else
-        ϵ = spl.alg.ϵ
-    end
-
-    # Generate a kernel.
-    kernel = make_ahmc_kernel(spl.alg, ϵ)
-
-    # Generate a phasepoint. Replaced during sample_init!
-    h, t = AHMC.sample_init(rng, h, θ_init) # this also ensure AHMC has the same dim as θ.
-
-    # Unlink everything, if it was indeed linked before.
-    if waslinked
-        vi = invlink!!(vi, spl, model)
-    end
-
-    return HMCState(vi, 0, 0, kernel.τ, h, AHMCAdaptor(spl.alg, metric; ϵ=ϵ), t.z)
-end