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Fixes to AD backend usage in externalsampler #2223

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merged 9 commits into from
May 18, 2024
Merged

Fixes to AD backend usage in externalsampler #2223

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cbd5554
fixes to AD backend usage in `externalsampler`
torfjelde May 16, 2024
9ec3ba5
test issue raised in #2223
torfjelde May 16, 2024
a10d55b
bumped patch version
torfjelde May 16, 2024
5336bd0
fixed external HMC tests and disabled external MH tests using NAmedTuple
torfjelde May 17, 2024
ba3fc03
disabled another test for MH with `externalsampler`
torfjelde May 17, 2024
adc1210
added commen to test
torfjelde May 17, 2024
9467dc5
disabled another externalsampler test for MH
torfjelde May 17, 2024
642bf9c
disable test for `demo_assume_index_observe` on Julia 1.7
torfjelde May 18, 2024
cbb1e59
relax experimental Gibbs test further
torfjelde May 18, 2024
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "Turing"
uuid = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
version = "0.31.4"
version = "0.31.5"

[deps]
ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
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6 changes: 4 additions & 2 deletions src/mcmc/abstractmcmc.jl
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Expand Up @@ -12,7 +12,7 @@ function transition_to_turing(f::DynamicPPL.LogDensityFunction, transition)
return Transition(f.model, varinfo, transition)
end

state_to_turing(f::LogDensityProblemsAD.ADGradientWrapper, state) = state_to_turing(parent(f), state)
state_to_turing(f::LogDensityProblemsAD.ADGradientWrapper, state) = TuringState(state, f)
function transition_to_turing(f::LogDensityProblemsAD.ADGradientWrapper, transition)
return transition_to_turing(parent(f), transition)
end
Expand All @@ -29,7 +29,9 @@ getvarinfo(f::DynamicPPL.LogDensityFunction) = f.varinfo
getvarinfo(f::LogDensityProblemsAD.ADGradientWrapper) = getvarinfo(parent(f))

setvarinfo(f::DynamicPPL.LogDensityFunction, varinfo) = Accessors.@set f.varinfo = varinfo
setvarinfo(f::LogDensityProblemsAD.ADGradientWrapper, varinfo) = setvarinfo(parent(f), varinfo)
function setvarinfo(f::LogDensityProblemsAD.ADGradientWrapper, varinfo)
return Accessors.@set f.ℓ = setvarinfo(f.ℓ, varinfo)
end

function AbstractMCMC.step(
rng::Random.AbstractRNG,
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13 changes: 13 additions & 0 deletions test/mcmc/abstractmcmc.jl
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Expand Up @@ -110,6 +110,19 @@ end
end
end
end

@testset "don't drop `ADgradient` (PR: #2223)" begin
rng = Random.default_rng()
model = DynamicPPL.TestUtils.DEMO_MODELS[1]
sampler = initialize_nuts(model)
sampler_ext = externalsampler(sampler; unconstrained=true, adtype=AutoForwardDiff())
# Initial step.
state = last(AbstractMCMC.step(rng, model, DynamicPPL.Sampler(sampler_ext)); n_adapts=0)
@test state.logdensity isa LogDensityProblemsAD.ADGradientWrapper
# Subsequent step.
state = last(AbstractMCMC.step(rng, model, DynamicPPL.Sampler(sampler_ext), state); n_adapts=0)
@test state.logdensity isa LogDensityProblemsAD.ADGradientWrapper
end
end

@turing_testset "AdvancedMH.jl" begin
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