Update to AutoDiffOperators v0.2

Project.toml

@@ -1,6 +1,6 @@
 name = "BAT"
 uuid = "c0cd4b16-88b7-57fa-983b-ab80aecada7e"
-version = "3.3.0"
+version = "3.3.1"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -95,7 +95,7 @@ AdvancedHMC = "0.5, 0.6"
 AffineMaps = "0.2.3, 0.3"
 ArgCheck = "1, 2.0"
 ArraysOfArrays = "0.4, 0.5, 0.6"
-AutoDiffOperators = "0.1"
+AutoDiffOperators = "0.2"
 ChainRulesCore = "0.9.44, 0.10, 1"
 ChangesOfVariables = "0.1.1"
 Clustering = "0.13, 0.14, 0.15"
@@ -135,7 +135,7 @@ Measurements = "2"
 NamedArrays = "0.9, 0.10"
 NestedSamplers = "0.8"
 Optim = "0.19,0.20, 0.21, 0.22, 1"
-Optimization = "3"
+Optimization = "3, 4"
 PDMats = "0.9, 0.10, 0.11"
 ParallelProcessingTools = "0.4"
 Parameters = "0.12, 0.13"

docs/src/list_of_algorithms.md

@@ -32,7 +32,7 @@ BAT sampling algorithm type: [`MCMCSampling`](@ref), MCMC algorithm subtype: [`H
 
 ```julia
 import AdvancedHMC, ForwardDiff
-set_batcontext(ad = ADModule(:ForwardDiff))
+set_batcontext(ad = ADSelector(ForwardDiff))
 bat_sample(target, MCMCSampling(mcalg = HamiltonianMC()))
 ```
 Requires the [AdvancedHMC](https://github.com/TuringLang/AdvancedHMC.jl) Julia package to be loaded explicitly.
@@ -160,7 +160,7 @@ using Optim
 bat_findmode(target, OptimAlg(optalg = Optim.NelderMead()))
 
 import ForwardDiff
-set_batcontext(ad = ADModule(:ForwardDiff))
+set_batcontext(ad = ADSelector(ForwardDiff))
 bat_findmode(target, OptimAlg(optalg = Optim.LBFGS()))
 ```
 

examples/dev-internal/test_findmode.jl

@@ -88,7 +88,7 @@ using AutoDiffOperators
 b = Optimization.SciMLBase.NoAD()
 supertype(typeof(b))
 
-adm = ADModule(:ForwardDiff)
+adm = ADSelector(ForwardDiff)
 
 adsel = BAT.get_adselector(context)
 supertype(typeof(adsel))

examples/paper-example/paper_example.jl

@@ -12,7 +12,7 @@ import Cuba, AdvancedHMC, ForwardDiff
 using AutoDiffOperators
 #using AHMI
 
-BAT.set_batcontext(ad = ADModule(:ForwardDiff))
+BAT.set_batcontext(ad = ADSelector(ForwardDiff))
 
 
 function log_pdf_poisson(λ::T, k::U) where {T<:Real,U<:Real}

test/distributions/test_hierarchical_distribution.jl

@@ -11,7 +11,7 @@ import AdvancedHMC
 
 
 @testset "hierarchial_distribution" begin
-    context = BATContext(ad = ADModule(:ForwardDiff))
+    context = BATContext(ad = ADSelector(ForwardDiff))
 
     let
         primary_dist = NamedTupleDist(

test/measures/test_bat_pushfwd_measure.jl

@@ -13,7 +13,7 @@ using Optim
 
 
 @testset "bat_pushfwd_measure" begin
-    context = BATContext(ad = ADModule(:ForwardDiff))
+    context = BATContext(ad = ADSelector(ForwardDiff))
 
     @testset "distribution transforms" begin
         function test_uv_transformed(target_type::Type{<:Distribution}, source_dist::Distribution)

test/optimization/test_mode_estimators.jl

@@ -89,7 +89,7 @@ using Optim, OptimizationOptimJL
     end
 
     @testset "Optim.jl - LBFGS" begin
-        context = BATContext(rng = Philox4x((0, 0)), ad = ADModule(:ForwardDiff))
+        context = BATContext(rng = Philox4x((0, 0)), ad = ADSelector(ForwardDiff))
         # Result Optim.maximize with LBFGS is not type-stable:
         test_findmode(posterior, OptimAlg(optalg = LBFGS(), trafo = DoNotTransform()), 0.01, inferred = false, context)
 

test/samplers/mcmc/test_hmc.jl

@@ -11,7 +11,7 @@ import ForwardDiff, Zygote
 import AdvancedHMC
 
 @testset "HamiltonianMC" begin
-    context = BATContext(ad = ADModule(:ForwardDiff))
+    context = BATContext(ad = ADSelector(ForwardDiff))
     objective = NamedTupleDist(a = Normal(1, 1.5), b = MvNormal([-1.0, 2.0], [2.0 1.5; 1.5 3.0]))
 
     shaped_target = @inferred(batmeasure(objective))
@@ -143,7 +143,7 @@ import AdvancedHMC
     @testset "HMC autodiff" begin
         posterior = BAT.example_posterior()
 
-        for adsel in [ADModule(:ForwardDiff), ADModule(:Zygote)]
+        for adsel in [ADSelector(ForwardDiff), ADSelector(Zygote)]
             @testset "$adsel" begin
                 context = BATContext(ad = adsel)