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Unify transition also in external samplers #2030

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merged 12 commits into from
Jul 10, 2023
Merged

Unify transition also in external samplers #2030

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71c8097
Transition
JaimeRZP Jul 5, 2023
8e28f30
Revert "Transition"
JaimeRZP Jul 5, 2023
6573895
bug
JaimeRZP Jul 5, 2023
ee45183
repeated functions
JaimeRZP Jul 5, 2023
96a70ca
move Transition to inference
JaimeRZP Jul 7, 2023
1192cf4
default get_stat
JaimeRZP Jul 7, 2023
8eeeacb
bug
JaimeRZP Jul 7, 2023
9e3aa18
Update src/inference/Inference.jl
JaimeRZP Jul 7, 2023
94177f7
Update src/inference/Inference.jl
JaimeRZP Jul 7, 2023
74fd637
Update src/inference/Inference.jl
JaimeRZP Jul 7, 2023
218bee7
rest of david changes
JaimeRZP Jul 7, 2023
911a55f
bring back Transition(a,b)
JaimeRZP Jul 8, 2023
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17 changes: 1 addition & 16 deletions src/contrib/inference/abstractmcmc.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -3,28 +3,13 @@ struct TuringState{S,F}
logdensity::F
end

struct TuringTransition{T,NT<:NamedTuple,F<:AbstractFloat}
θ::T
lp::F
stat::NT
end

function TuringTransition(vi::AbstractVarInfo, t)
theta = tonamedtuple(vi)
lp = getlogp(vi)
return TuringTransition(theta, lp, getstats(t))
end

metadata(t::TuringTransition) = merge((lp = t.lp,), t.stat)
DynamicPPL.getlogp(t::TuringTransition) = t.lp

state_to_turing(f::DynamicPPL.LogDensityFunction, state) = TuringState(state, f)
function transition_to_turing(f::DynamicPPL.LogDensityFunction, transition)
θ = getparams(transition)
varinfo = DynamicPPL.unflatten(f.varinfo, θ)
# TODO: `deepcopy` is overkill; make more efficient.
varinfo = DynamicPPL.invlink!!(deepcopy(varinfo), f.model)
return TuringTransition(varinfo, transition)
return Transition(varinfo, transition)
end

# NOTE: Only thing that depends on the underlying sampler.
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13 changes: 6 additions & 7 deletions src/inference/Inference.jl
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Expand Up @@ -123,19 +123,20 @@ end
######################
# Default Transition #
######################
# Default
# Extended in contrib/inference/abstractmcmc.jl
getstats(t) = nothing

struct Transition{T, F<:AbstractFloat, S<:Union{NamedTuple, Nothing}}
θ :: T
lp :: F # TODO: merge `lp` with `stat`
stat :: S
end

Transition(θ, lp) = Transition(θ, lp, nothing)
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function Transition(vi::AbstractVarInfo; nt::NamedTuple=NamedTuple())
function Transition(vi::AbstractVarInfo, t=nothing; nt::NamedTuple=NamedTuple())
θ = merge(tonamedtuple(vi), nt)
lp = getlogp(vi)
return Transition(θ, lp, nothing)
return Transition(θ, lp, getstats(t))
end

function metadata(t::Transition)
Expand Down Expand Up @@ -664,9 +665,7 @@ function transitions_from_chain(
model(rng, vi, sampler)

# Convert `VarInfo` into `NamedTuple` and save.
theta = DynamicPPL.tonamedtuple(vi)
lp = Turing.getlogp(vi)
Transition(theta, lp)
Transition(vi)
end

return transitions
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