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Remove trailing whitespace (#2260)
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benchmarks/benchmarks_suite.jl

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@@ -4,14 +4,14 @@ using LinearAlgebra
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const BenchmarkSuite = BenchmarkTools.BenchmarkGroup()
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#
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# Add models to benchmarks
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# Add models to benchmarks
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#
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include("models/hlr.jl")
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include("models/lr.jl")
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include("models/sv_nuts.jl")
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# constrained
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# constrained
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BenchmarkSuite["constrained"] = BenchmarkGroup(["constrained"])
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data = [0, 1, 0, 1, 1, 1, 1, 1, 1, 1]

benchmarks/models/lr_nuts.data

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src/mcmc/Inference.jl

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@@ -316,7 +316,7 @@ Return a named tuple of parameters.
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getparams(model, t) = t.θ
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function getparams(model::DynamicPPL.Model, vi::DynamicPPL.VarInfo)
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# NOTE: In the past, `invlink(vi, model)` + `values_as(vi, OrderedDict)` was used.
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# Unfortunately, using `invlink` can cause issues in scenarios where the constraints
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# Unfortunately, using `invlink` can cause issues in scenarios where the constraints
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# of the parameters change depending on the realizations. Hence we have to use
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# `values_as_in_model`, which re-runs the model and extracts the parameters
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# as they are seen in the model, i.e. in the constrained space. Moreover,

src/mcmc/particle_mcmc.jl

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@@ -340,7 +340,7 @@ function trace_local_varinfo_maybe(varinfo)
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trace = AdvancedPS.current_trace()
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return trace.model.f.varinfo
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catch e
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# NOTE: this heuristic allows Libtask evaluating a model outside a `Trace`.
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# NOTE: this heuristic allows Libtask evaluating a model outside a `Trace`.
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if e == KeyError(:__trace) || current_task().storage isa Nothing
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return varinfo
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else

test/mcmc/hmc.jl

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@@ -308,7 +308,7 @@ using Turing
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initial_params=[0.5, 1.75, 1.0]
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)
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chain_prior = sample(model, Prior(), num_samples)
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# Extract the `x` like this because running `generated_quantities` was how
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# the issue was discovered, hence we also want to make sure that it works.
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results = generated_quantities(model, chain)

test/runtests.jl

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@@ -41,7 +41,7 @@ end
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@timeit_include("mcmc/ess.jl")
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@timeit_include("mcmc/is.jl")
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end
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@timeit TIMEROUTPUT "inference" begin
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@testset "inference with samplers" begin
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@timeit_include("mcmc/gibbs.jl")

test/skipped/advi_demo.jl

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Original file line numberDiff line numberDiff line change
@@ -90,7 +90,7 @@ for seed in seeds
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# Eq. (90) in "Conjugate Bayesian analysis of the Gaussian distribution" by Murphy
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# `scale(post)` = θ
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p_τ = Gamma(post.shape, scale(post))
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p_σ²_pdf = z -> pdf(p_τ, 1 / z) # τ => 1 / σ²
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p_σ²_pdf = z -> pdf(p_τ, 1 / z) # τ => 1 / σ²
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# marginal of μ
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# Eq. (91) in "Conjugate Bayesian analysis of the Gaussian distribution" by Murphy
@@ -102,7 +102,7 @@ for seed in seeds
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βₙ = post.rate # β → rate
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# numerically more stable but doesn't seem to have effect; issue is probably internal to
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# `pdf` which needs to compute ≈ Γ(1000)
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# `pdf` which needs to compute ≈ Γ(1000)
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p_μ_pdf =
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z -> exp(
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logpdf(

test/variational/advi.jl

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@@ -69,7 +69,7 @@ using Turing.Essential: TuringDiagMvNormal
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x ~ Dirichlet([1.0,1.0])
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return x
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end
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m = dirichlet()
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b = bijector(m)
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x0 = m()

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