Merge branch 'master' into mhauru/change-gibbs-sampler

Author: penelopeysm

.github/workflows/Tests.yml

@@ -6,6 +6,11 @@ on:
       - master
   pull_request:
 
+# Cancel existing tests on the same PR if a new commit is added to a pull request
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref || github.run_id }}
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+
 jobs:
   test:
     # Use matrix.test.name here to avoid it taking up the entire window width

Project.toml

@@ -63,7 +63,7 @@ Distributions = "0.23.3, 0.24, 0.25"
 DistributionsAD = "0.6"
 DocStringExtensions = "0.8, 0.9"
 DynamicHMC = "3.4"
-DynamicPPL = "0.30.4, 0.31"
+DynamicPPL = "0.32"
 EllipticalSliceSampling = "0.5, 1, 2"
 ForwardDiff = "0.10.3"
 Libtask = "0.8.8"

docs/src/api.md

@@ -37,11 +37,11 @@ even though [`Prior()`](@ref) is actually defined in the `Turing.Inference` modu
 
 ### Modelling
 
-| Exported symbol | Documentation                     | Description                                  |
-|:--------------- |:--------------------------------- |:-------------------------------------------- |
-| `@model`        | [`DynamicPPL.@model`](@extref)    | Define a probabilistic model                 |
-| `@varname`      | [`AbstractPPL.@varname`](@extref) | Generate a `VarName` from a Julia expression |
-| `@submodel`     | [`DynamicPPL.@submodel`](@extref) | Define a submodel                            |
+| Exported symbol | Documentation                       | Description                                  |
+|:--------------- |:----------------------------------- |:-------------------------------------------- |
+| `@model`        | [`DynamicPPL.@model`](@extref)      | Define a probabilistic model                 |
+| `@varname`      | [`AbstractPPL.@varname`](@extref)   | Generate a `VarName` from a Julia expression |
+| `to_submodel`   | [`DynamicPPL.to_submodel`](@extref) | Define a submodel                            |
 
 ### Inference
 

src/Turing.jl

@@ -70,15 +70,17 @@ using DynamicPPL:
     decondition,
     fix,
     unfix,
-    conditioned
+    conditioned,
+    to_submodel
 using StatsBase: predict
 using Bijectors: ordered
 using OrderedCollections: OrderedDict
 
 # Turing essentials - modelling macros and inference algorithms
 export @model,                 # modelling
     @varname,
-    @submodel,
+    @submodel,  # Deprecated
+    to_submodel,
     DynamicPPL,
     Prior,                  # Sampling from the prior
     MH,                     # classic sampling

src/mcmc/Inference.jl

@@ -6,8 +6,6 @@ using DynamicPPL:
     VarInfo,
     TypedVarInfo,
     islinked,
-    invlink!,
-    link!,
     setindex!!,
     push!!,
     setlogp!!,

src/mcmc/hmc.jl

@@ -479,6 +479,12 @@ end
 
 getstepsize(sampler::Sampler{<:Hamiltonian}, state) = sampler.alg.ϵ
 getstepsize(sampler::Sampler{<:AdaptiveHamiltonian}, state) = AHMC.getϵ(state.adaptor)
+function getstepsize(
+    sampler::Sampler{<:AdaptiveHamiltonian},
+    state::HMCState{TV,TKernel,THam,PhType,AHMC.Adaptation.NoAdaptation},
+) where {TV,TKernel,THam,PhType}
+    return state.kernel.τ.integrator.ϵ
+end
 
 gen_metric(dim::Int, spl::Sampler{<:Hamiltonian}, state) = AHMC.UnitEuclideanMetric(dim)
 function gen_metric(dim::Int, spl::Sampler{<:AdaptiveHamiltonian}, state)

test/Project.toml

@@ -1,9 +1,11 @@
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
+AbstractPPL = "7a57a42e-76ec-4ea3-a279-07e840d6d9cf"
 AdvancedMH = "5b7e9947-ddc0-4b3f-9b55-0d8042f74170"
 AdvancedPS = "576499cb-2369-40b2-a588-c64705576edc"
 AdvancedVI = "b5ca4192-6429-45e5-a2d9-87aec30a685c"
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
+BangBang = "198e06fe-97b7-11e9-32a5-e1d131e6ad66"
 Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
@@ -46,15 +48,15 @@ Clustering = "0.14, 0.15"
 Distributions = "0.25"
 DistributionsAD = "0.6.3"
 DynamicHMC = "2.1.6, 3.0"
-DynamicPPL = "0.30.4, 0.31"
+DynamicPPL = "0.32.2"
 FiniteDifferences = "0.10.8, 0.11, 0.12"
 ForwardDiff = "0.10.12 - 0.10.32, 0.10"
 HypothesisTests = "0.11"
 LinearAlgebra = "1"
 LogDensityProblems = "2"
 LogDensityProblemsAD = "1.4"
 MCMCChains = "5, 6"
-Mooncake = "0.4.19"
+Mooncake = "0.4.61"
 NamedArrays = "0.9.4, 0.10"
 Optim = "1"
 Optimization = "3, 4"