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Remove compat/ad.jl
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test/Project.toml

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@@ -6,7 +6,6 @@ Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
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Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
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Bijectors = "76274a88-744f-5084-9051-94815aaf08c4"
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Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
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Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
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DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
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Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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Aqua = "0.8"
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Bijectors = "0.15.1"
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Combinatorics = "1"
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Compat = "4.3.0"
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DifferentiationInterface = "0.6.41, 0.7"
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Distributions = "0.25"
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DistributionsAD = "0.6.3"

test/compat/ad.jl

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test/runtests.jl

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@@ -15,7 +15,6 @@ using MCMCChains
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using StableRNGs
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using ReverseDiff
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using Zygote
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using Compat
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using Distributed
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using LinearAlgebra
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end
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if GROUP == "All" || GROUP == "Group2"
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@testset "compat" begin
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include(joinpath("compat", "ad.jl"))
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end
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@testset "extensions" begin
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include("ext/DynamicPPLMCMCChainsExt.jl")
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include("ext/DynamicPPLJETExt.jl")

test/test_util.jl

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end
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const gdemo_default = gdemo_d()
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# TODO(penelopeysm): Remove this (and also test/compat/ad.jl)
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function test_model_ad(model, logp_manual)
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vi = VarInfo(model)
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x = vi[:]
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# Log probabilities using the model.
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= DynamicPPL.LogDensityFunction(model, vi)
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logp_model = Base.Fix1(LogDensityProblems.logdensity, ℓ)
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# Check that both functions return the same values.
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lp = logp_manual(x)
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@test logp_model(x) lp
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# Gradients based on the manual implementation.
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grad = ForwardDiff.gradient(logp_manual, x)
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# Gradients based on the model.
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@test ForwardDiff.gradient(logp_model, x) grad
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end
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"""
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short_varinfo_name(vi::AbstractVarInfo)
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