TuringLang · mhauru · Mar 19, 2025 · Feb 14, 2025 · Feb 14, 2025 · Feb 25, 2025
diff --git a/.github/workflows/Tests.yml b/.github/workflows/Tests.yml
@@ -24,8 +24,6 @@ jobs:
         test:
           # Run some of the slower test files individually. The last one catches everything
           # not included in the others.
-          - name: "essential/ad"
-            args: "essential/ad.jl"
           - name: "mcmc/gibbs"
             args: "mcmc/gibbs.jl"
           - name: "mcmc/hmc"
@@ -37,7 +35,7 @@ jobs:
           - name: "mcmc/ess"
             args: "mcmc/ess.jl"
           - name: "everything else"
-            args: "--skip essential/ad.jl mcmc/gibbs.jl mcmc/hmc.jl mcmc/abstractmcmc.jl mcmc/Inference.jl mcmc/ess.jl"
+            args: "--skip mcmc/gibbs.jl mcmc/hmc.jl mcmc/abstractmcmc.jl mcmc/Inference.jl mcmc/ess.jl"
         runner:
           # Default
           - version: '1'

diff --git a/HISTORY.md b/HISTORY.md
@@ -1,3 +1,44 @@
+# Release 0.37.0
+
+## Breaking changes
+
+### Gibbs constructors
+
+0.37 removes the old Gibbs constructors deprecated in 0.36.
+
+### Remove Zygote support
+
+Zygote is no longer officially supported as an automatic differentiation backend, and `AutoZygote` is no longer exported. You can continue to use Zygote by importing `AutoZygote` from ADTypes and it may well continue to work, but it is no longer tested and no effort will be expended to fix it if something breaks.
+
+[Mooncake](https://github.com/compintell/Mooncake.jl/) is the recommended replacement for Zygote.
+
+### DynamicPPL 0.35
+
+Turing.jl v0.37 uses DynamicPPL v0.35, which brings with it several breaking changes:
+
+  - The right hand side of `.~` must from now on be a univariate distribution.
+  - Indexing `VarInfo` objects by samplers has been removed completely.
+  - The order in which nested submodel prefixes are applied has been reversed.
+  - The arguments for the constructor of `LogDensityFunction` have changed. `LogDensityFunction` also now satisfies the `LogDensityProblems` interface, without needing a wrapper object.
+
+For more details about all of the above, see the changelog of DynamicPPL [here](https://github.com/TuringLang/DynamicPPL.jl/releases/tag/v0.35.0).
+
+### Export list
+
+Turing.jl's export list has been cleaned up a fair bit. This affects what is imported into your namespace when you do an unqualified `using Turing`. You may need to import things more explicitly than before.
+
+  - The `DynamicPPL` and `AbstractMCMC` modules are no longer exported. You will need to `import DynamicPPL` or `using DynamicPPL: DynamicPPL` (likewise `AbstractMCMC`) yourself, which in turn means that they have to be made available in your project environment.
+
+  - `@logprob_str` and `@prob_str` have been removed following a long deprecation period.
+  - We no longer re-export everything from `Bijectors` and `Libtask`. To get around this, add `using Bijectors` or `using Libtask` at the top of your script (but we recommend using more selective imports).
+
+      + We no longer export `Bijectors.ordered`. If you were using `ordered`, even Bijectors does not (currently) export this. You will have to manually import it with `using Bijectors: ordered`.
+
+On the other hand, we have added a few more exports:
+
+  - `DynamicPPL.returned` and `DynamicPPL.prefix` are exported (for use with submodels).
+  - `LinearAlgebra.I` is exported for convenience.
+
 # Release 0.36.0
 
 ## Breaking changes

diff --git a/Project.toml b/Project.toml
@@ -1,6 +1,6 @@
 name = "Turing"
 uuid = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
-version = "0.36.3"
+version = "0.37.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -23,7 +23,6 @@ ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Libtask = "6f1fad26-d15e-5dc8-ae53-837a1d7b8c9f"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
-LogDensityProblemsAD = "996a588d-648d-4e1f-a8f0-a84b347e47b1"
 MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 NamedArrays = "86f7a689-2022-50b4-a561-43c23ac3c673"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
@@ -59,17 +58,16 @@ BangBang = "0.4.2"
 Bijectors = "0.14, 0.15"
 Compat = "4.15.0"
 DataStructures = "0.18"
-Distributions = "0.23.3, 0.24, 0.25"
+Distributions = "0.25.77"
 DistributionsAD = "0.6"
 DocStringExtensions = "0.8, 0.9"
 DynamicHMC = "3.4"
-DynamicPPL = "0.34.1"
+DynamicPPL = "0.35"
 EllipticalSliceSampling = "0.5, 1, 2"
 ForwardDiff = "0.10.3"
 Libtask = "0.8.8"
 LinearAlgebra = "1"
 LogDensityProblems = "2"
-LogDensityProblemsAD = "1.7.0"
 MCMCChains = "5, 6"
 NamedArrays = "0.9, 0.10"
 Optim = "1"

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -1,7 +1,4 @@
 [deps]
-Bijectors = "76274a88-744f-5084-9051-94815aaf08c4"
-Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DocumenterInterLinks = "d12716ef-a0f6-4df4-a9f1-a5a34e75c656"
-DynamicPPL = "366bfd00-2699-11ea-058f-f148b4cae6d8"
 Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,35 +1,32 @@
 using Documenter
 using Turing
-# Need to import Distributions and Bijectors to generate docs for functions
-# from those packages.
-using Distributions
-using Bijectors
-using DynamicPPL
 
 using DocumenterInterLinks
 
 links = InterLinks(
     "DynamicPPL" => "https://turinglang.org/DynamicPPL.jl/stable/objects.inv",
-    "AbstractPPL" => "https://turinglang.org/AbstractPPL.jl/dev/objects.inv",
+    "AbstractPPL" => "https://turinglang.org/AbstractPPL.jl/stable/objects.inv",
+    "LinearAlgebra" => "https://docs.julialang.org/en/v1/objects.inv",
+    "AbstractMCMC" => "https://turinglang.org/AbstractMCMC.jl/stable/objects.inv",
     "ADTypes" => "https://sciml.github.io/ADTypes.jl/stable/objects.inv",
     "AdvancedVI" => "https://turinglang.org/AdvancedVI.jl/v0.2.8/objects.inv",
     "DistributionsAD" => "https://turinglang.org/DistributionsAD.jl/stable/objects.inv",
+    "OrderedCollections" => "https://juliacollections.github.io/OrderedCollections.jl/stable/objects.inv",
 )
 
 # Doctest setup
 DocMeta.setdocmeta!(Turing, :DocTestSetup, :(using Turing); recursive=true)
 
 makedocs(;
     sitename="Turing",
-    modules=[Turing, Distributions, Bijectors],
+    modules=[Turing],
     pages=[
         "Home" => "index.md",
         "API" => "api.md",
         "Submodule APIs" =>
             ["Inference" => "api/Inference.md", "Optimisation" => "api/Optimisation.md"],
     ],
     checkdocs=:exports,
-    # checkdocs_ignored_modules=[Turing, Distributions, DynamicPPL, AbstractPPL, Bijectors],
     doctest=false,
     warnonly=true,
     plugins=[links],

diff --git a/docs/src/api.md b/docs/src/api.md
@@ -6,15 +6,13 @@ Turing.jl directly re-exports the entire public API of the following packages:
 
   - [Distributions.jl](https://juliastats.org/Distributions.jl)
   - [MCMCChains.jl](https://turinglang.org/MCMCChains.jl)
-  - [AbstractMCMC.jl](https://turinglang.org/AbstractMCMC.jl)
-  - [Bijectors.jl](https://turinglang.org/Bijectors.jl)
-  - [Libtask.jl](https://github.com/TuringLang/Libtask.jl)
 
 Please see the individual packages for their documentation.
 
 ## Individual exports and re-exports
 
-**All** of the following symbols are exported unqualified by Turing, even though the documentation suggests that many of them are qualified.
+In this API documentation, for the sake of clarity, we have listed the module that actually defines each of the exported symbols.
+Note, however, that **all** of the following symbols are exported unqualified by Turing.
 That means, for example, you can just write
 
 ```julia
@@ -37,17 +35,22 @@ 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 |
-| `to_submodel`   | [`DynamicPPL.to_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                                                                            |
+| `prefix`             | [`DynamicPPL.prefix`](@extref)             | Prefix all variable names in a model with a given symbol                                     |
+| `LogDensityFunction` | [`DynamicPPL.LogDensityFunction`](@extref) | A struct containing all information about how to evaluate a model. Mostly for advanced users |
 
 ### Inference
 
-| Exported symbol | Documentation                                                                                    | Description         |
-|:--------------- |:------------------------------------------------------------------------------------------------ |:------------------- |
-| `sample`        | [`StatsBase.sample`](https://turinglang.org/AbstractMCMC.jl/stable/api/#Sampling-a-single-chain) | Sample from a model |
+| Exported symbol   | Documentation                                                                                    | Description                        |
+|:----------------- |:------------------------------------------------------------------------------------------------ |:---------------------------------- |
+| `sample`          | [`StatsBase.sample`](https://turinglang.org/AbstractMCMC.jl/stable/api/#Sampling-a-single-chain) | Sample from a model                |
+| `MCMCThreads`     | [`AbstractMCMC.MCMCThreads`](@extref)                                                            | Run MCMC using multiple threads    |
+| `MCMCDistributed` | [`AbstractMCMC.MCMCDistributed`](@extref)                                                        | Run MCMC using multiple processes  |
+| `MCMCSerial`      | [`AbstractMCMC.MCMCSerial`](@extref)                                                             | Run MCMC using without parallelism |
 
 ### Samplers
 
@@ -68,6 +71,7 @@ even though [`Prior()`](@ref) is actually defined in the `Turing.Inference` modu
 | `SMC`                | [`Turing.Inference.SMC`](@ref)                | Sequential Monte Carlo                                              |
 | `PG`                 | [`Turing.Inference.PG`](@ref)                 | Particle Gibbs                                                      |
 | `CSMC`               | [`Turing.Inference.CSMC`](@ref)               | The same as PG                                                      |
+| `RepeatSampler`      | [`Turing.Inference.RepeatSampler`](@ref)      | A sampler that runs multiple times on the same variable             |
 | `externalsampler`    | [`Turing.Inference.externalsampler`](@ref)    | Wrap an external sampler for use in Turing                          |
 
 ### Variational inference
@@ -88,7 +92,6 @@ See the [AD guide](https://turinglang.org/docs/tutorials/docs-10-using-turing-au
 |:----------------- |:------------------------------------ |:---------------------- |
 | `AutoForwardDiff` | [`ADTypes.AutoForwardDiff`](@extref) | ForwardDiff.jl backend |
 | `AutoReverseDiff` | [`ADTypes.AutoReverseDiff`](@extref) | ReverseDiff.jl backend |
-| `AutoZygote`      | [`ADTypes.AutoZygote`](@extref)      | Zygote.jl backend      |
 | `AutoMooncake`    | [`ADTypes.AutoMooncake`](@extref)    | Mooncake.jl backend    |
 
 ### Debugging
@@ -109,52 +112,37 @@ OrderedLogistic
 LogPoisson
 ```
 
-`BernoulliLogit` is part of Distributions.jl since version 0.25.77.
-If you are using an older version of Distributions where this isn't defined, Turing will export the same distribution.
-
-```@docs
-Distributions.BernoulliLogit
-```
-
 ### Tools to work with distributions
 
 | Exported symbol | Documentation                          | Description                                                    |
 |:--------------- |:-------------------------------------- |:-------------------------------------------------------------- |
+| `I`             | [`LinearAlgebra.I`](@extref)           | Identity matrix                                                |
 | `filldist`      | [`DistributionsAD.filldist`](@extref)  | Create a product distribution from a distribution and integers |
 | `arraydist`     | [`DistributionsAD.arraydist`](@extref) | Create a product distribution from an array of distributions   |
 | `NamedDist`     | [`DynamicPPL.NamedDist`](@extref)      | A distribution that carries the name of the variable           |
 
 ### Predictions
 
-```@docs
-DynamicPPL.predict
-```
+| Exported symbol | Documentation                                                                     | Description                                             |
+|:--------------- |:--------------------------------------------------------------------------------- |:------------------------------------------------------- |
+| `predict`       | [`StatsAPI.predict`](https://turinglang.org/DynamicPPL.jl/stable/api/#Predicting) | Generate samples from posterior predictive distribution |
 
 ### Querying model probabilities and quantities
 
 Please see the [generated quantities](https://turinglang.org/docs/tutorials/usage-generated-quantities/) and [probability interface](https://turinglang.org/docs/tutorials/usage-probability-interface/) guides for more information.
 
-| Exported symbol            | Documentation                                                                                                                     | Description                                                     |
-|:-------------------------- |:--------------------------------------------------------------------------------------------------------------------------------- |:--------------------------------------------------------------- |
-| `generated_quantities`     | [`DynamicPPL.generated_quantities`](@extref)                                                                                      | Calculate additional quantities defined in a model              |
-| `pointwise_loglikelihoods` | [`DynamicPPL.pointwise_loglikelihoods`](@extref)                                                                                  | Compute log likelihoods for each sample in a chain              |
-| `logprior`                 | [`DynamicPPL.logprior`](@extref)                                                                                                  | Compute log prior probability                                   |
-| `logjoint`                 | [`DynamicPPL.logjoint`](@extref)                                                                                                  | Compute log joint probability                                   |
-| `LogDensityFunction`       | [`DynamicPPL.LogDensityFunction`](@extref)                                                                                        | Wrap a Turing model to satisfy LogDensityFunctions.jl interface |
-| `condition`                | [`AbstractPPL.condition`](@extref)                                                                                                | Condition a model on data                                       |
-| `decondition`              | [`AbstractPPL.decondition`](@extref)                                                                                              | Remove conditioning on data                                     |
-| `conditioned`              | [`DynamicPPL.conditioned`](@extref)                                                                                               | Return the conditioned values of a model                        |
-| `fix`                      | [`DynamicPPL.fix`](@extref)                                                                                                       | Fix the value of a variable                                     |
-| `unfix`                    | [`DynamicPPL.unfix`](@extref)                                                                                                     | Unfix the value of a variable                                   |
-| `OrderedDict`              | [`OrderedCollections.OrderedDict`](https://juliacollections.github.io/OrderedCollections.jl/dev/ordered_containers/#OrderedDicts) | An ordered dictionary                                           |
-
-### Extra re-exports from Bijectors
-
-Note that Bijectors itself does not export `ordered`.
-
-```@docs
-Bijectors.ordered
-```
+| Exported symbol            | Documentation                                                                                                                | Description                                        |
+|:-------------------------- |:---------------------------------------------------------------------------------------------------------------------------- |:-------------------------------------------------- |
+| `returned`                 | [`DynamicPPL.returned`](https://turinglang.org/DynamicPPL.jl/stable/api/#DynamicPPL.returned-Tuple%7BModel,%20NamedTuple%7D) | Calculate additional quantities defined in a model |
+| `pointwise_loglikelihoods` | [`DynamicPPL.pointwise_loglikelihoods`](@extref)                                                                             | Compute log likelihoods for each sample in a chain |
+| `logprior`                 | [`DynamicPPL.logprior`](@extref)                                                                                             | Compute log prior probability                      |
+| `logjoint`                 | [`DynamicPPL.logjoint`](@extref)                                                                                             | Compute log joint probability                      |
+| `condition`                | [`AbstractPPL.condition`](@extref)                                                                                           | Condition a model on data                          |
+| `decondition`              | [`AbstractPPL.decondition`](@extref)                                                                                         | Remove conditioning on data                        |
+| `conditioned`              | [`DynamicPPL.conditioned`](@extref)                                                                                          | Return the conditioned values of a model           |
+| `fix`                      | [`DynamicPPL.fix`](@extref)                                                                                                  | Fix the value of a variable                        |
+| `unfix`                    | [`DynamicPPL.unfix`](@extref)                                                                                                | Unfix the value of a variable                      |
+| `OrderedDict`              | [`OrderedCollections.OrderedDict`](@extref)                                                                                  | An ordered dictionary                              |
 
 ### Point estimates