Format

Author: penelopeysm

main.jl

@@ -13,13 +13,13 @@ import Zygote
 
 # AD backends to test.
 ADTYPES = Dict(
-    "FiniteDifferences" => AutoFiniteDifferences(; fdm=central_fdm(5, 1)),
+    "FiniteDifferences" => AutoFiniteDifferences(; fdm = central_fdm(5, 1)),
     "ForwardDiff" => AutoForwardDiff(),
-    "ReverseDiff" => AutoReverseDiff(; compile=false),
-    "ReverseDiffCompiled" => AutoReverseDiff(; compile=true),
-    "Mooncake" => AutoMooncake(; config=nothing),
-    "EnzymeForward" => AutoEnzyme(; mode=set_runtime_activity(Forward, true)),
-    "EnzymeReverse" => AutoEnzyme(; mode=set_runtime_activity(Reverse, true)),
+    "ReverseDiff" => AutoReverseDiff(; compile = false),
+    "ReverseDiffCompiled" => AutoReverseDiff(; compile = true),
+    "Mooncake" => AutoMooncake(; config = nothing),
+    "EnzymeForward" => AutoEnzyme(; mode = set_runtime_activity(Forward, true)),
+    "EnzymeReverse" => AutoEnzyme(; mode = set_runtime_activity(Reverse, true)),
     "Zygote" => AutoZygote(),
 )
 
@@ -75,9 +75,9 @@ elseif length(ARGS) == 3 && ARGS[1] == "--run"
             # https://github.com/TuringLang/ADTests/issues/4
             vi = DynamicPPL.unflatten(VarInfo(model), [0.5, -0.5])
             params = [-0.5, 0.5]
-            result = run_ad(model, adtype; varinfo=vi, params=params, benchmark=true)
+            result = run_ad(model, adtype; varinfo = vi, params = params, benchmark = true)
         else
-            result = run_ad(model, adtype; benchmark=true)
+            result = run_ad(model, adtype; benchmark = true)
         end
         # If reached here - nothing went wrong
         @printf("%.3f", result.time_vs_primal)

models/demo_assume_dot_observe.jl

@@ -1,10 +1,10 @@
-@model function demo_assume_dot_observe(x=[1.5, 2.0])
+@model function demo_assume_dot_observe(x = [1.5, 2.0])
     # `assume` and `dot_observe`
     s ~ InverseGamma(2, 3)
     m ~ Normal(0, sqrt(s))
     x .~ Normal(m, sqrt(s))
 
-    return (; s=s, m=m, x=x, logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = x, logp = getlogp(__varinfo__))
 end
 
 @register demo_assume_dot_observe()

models/demo_assume_dot_observe_literal.jl

@@ -4,7 +4,7 @@
     m ~ Normal(0, sqrt(s))
     [1.5, 2.0] .~ Normal(m, sqrt(s))
 
-    return (; s=s, m=m, x=[1.5, 2.0], logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = [1.5, 2.0], logp = getlogp(__varinfo__))
 end
 
 @model demo_assume_dot_observe_literal()

models/demo_assume_matrix_observe_matrix_index.jl

@@ -1,5 +1,6 @@
 @model function demo_assume_matrix_observe_matrix_index(
-    x=transpose([1.5 2.0;]), ::Type{TV}=Array{Float64}
+    x = transpose([1.5 2.0;]),
+    ::Type{TV} = Array{Float64},
 ) where {TV}
     n = length(x)
     d = n ÷ 2
@@ -9,7 +10,7 @@
 
     x[:, 1] ~ MvNormal(m, Diagonal(s_vec))
 
-    return (; s=s, m=m, x=x, logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = x, logp = getlogp(__varinfo__))
 end
 
 @register demo_assume_matrix_observe_matrix_index()

models/demo_assume_multivariate_observe.jl

@@ -1,10 +1,10 @@
-@model function demo_assume_multivariate_observe(x=[1.5, 2.0])
+@model function demo_assume_multivariate_observe(x = [1.5, 2.0])
     # Multivariate `assume` and `observe`
     s ~ product_distribution([InverseGamma(2, 3), InverseGamma(2, 3)])
     m ~ MvNormal(zero(x), Diagonal(s))
     x ~ MvNormal(m, Diagonal(s))
 
-    return (; s=s, m=m, x=x, logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = x, logp = getlogp(__varinfo__))
 end
 
 @register demo_assume_multivariate_observe()

models/demo_assume_multivariate_observe_literal.jl

@@ -4,7 +4,7 @@
     m ~ MvNormal(zeros(2), Diagonal(s))
     [1.5, 2.0] ~ MvNormal(m, Diagonal(s))
 
-    return (; s=s, m=m, x=[1.5, 2.0], logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = [1.5, 2.0], logp = getlogp(__varinfo__))
 end
 
 @register demo_assume_multivariate_observe_literal()

models/demo_assume_observe_literal.jl

@@ -5,7 +5,7 @@
     1.5 ~ Normal(m, sqrt(s))
     2.0 ~ Normal(m, sqrt(s))
 
-    return (; s=s, m=m, x=[1.5, 2.0], logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = [1.5, 2.0], logp = getlogp(__varinfo__))
 end
 
 @register demo_assume_observe_literal()

models/demo_assume_submodel_observe_index_literal.jl

@@ -1,4 +1,4 @@
-@model function _prior_dot_assume(::Type{TV}=Vector{Float64}) where {TV}
+@model function _prior_dot_assume(::Type{TV} = Vector{Float64}) where {TV}
     s = TV(undef, 2)
     s .~ InverseGamma(2, 3)
     m = TV(undef, 2)
@@ -13,7 +13,7 @@ end
     1.5 ~ Normal(m[1], sqrt(s[1]))
     2.0 ~ Normal(m[2], sqrt(s[2]))
 
-    return (; s=s, m=m, x=[1.5, 2.0], logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = [1.5, 2.0], logp = getlogp(__varinfo__))
 end
 
 @register demo_assume_submodel_observe_index_literal()

models/demo_dot_assume_observe_index.jl

@@ -1,5 +1,6 @@
 @model function demo_dot_assume_observe_index(
-    x=[1.5, 2.0], ::Type{TV}=Vector{Float64}
+    x = [1.5, 2.0],
+    ::Type{TV} = Vector{Float64},
 ) where {TV}
     # `dot_assume` and `observe` with indexing
     s = TV(undef, length(x))
@@ -10,7 +11,7 @@
         x[i] ~ Normal(m[i], sqrt(s[i]))
     end
 
-    return (; s=s, m=m, x=x, logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = x, logp = getlogp(__varinfo__))
 end
 
 @register demo_dot_assume_observe_index()

models/demo_dot_assume_observe_index_literal.jl

@@ -1,4 +1,6 @@
-@model function demo_dot_assume_observe_index_literal(::Type{TV}=Vector{Float64}) where {TV}
+@model function demo_dot_assume_observe_index_literal(
+    ::Type{TV} = Vector{Float64},
+) where {TV}
     # `dot_assume` and literal `observe` with indexing
     s = TV(undef, 2)
     m = TV(undef, 2)
@@ -8,7 +10,7 @@
     1.5 ~ Normal(m[1], sqrt(s[1]))
     2.0 ~ Normal(m[2], sqrt(s[2]))
 
-    return (; s=s, m=m, x=[1.5, 2.0], logp=getlogp(__varinfo__))
+    return (; s = s, m = m, x = [1.5, 2.0], logp = getlogp(__varinfo__))
 end
 
 @register demo_dot_assume_observe_index_literal()