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TuringLang · Oct 2, 2024 · 8832099 · 8832099
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diff --git a/.JuliaFormatter.toml b/.JuliaFormatter.toml
@@ -5,6 +5,8 @@ import_to_using = false
 # We ignore these files because when formatting was first put in place they were being worked on.
 # These ignores should be removed once the relevant PRs are merged/closed.
 ignore = [
+    # Upstream issue
+    "docs/src/api.md",
     # https://github.com/TuringLang/Turing.jl/pull/2231/files
     "src/experimental/gibbs.jl",
     "src/mcmc/abstractmcmc.jl",

diff --git a/docs/make.jl b/docs/make.jl
@@ -22,10 +22,8 @@ makedocs(;
     pages=[
         "Home" => "index.md",
         "API" => "api.md",
-        "Submodule APIs" => [
-            "Inference" => "api/Inference.md",
-            "Optimisation" => "api/Optimisation.md",
-        ]
+        "Submodule APIs" =>
+            ["Inference" => "api/Inference.md", "Optimisation" => "api/Optimisation.md"],
     ],
     checkdocs=:exports,
     # checkdocs_ignored_modules=[Turing, Distributions, DynamicPPL, AbstractPPL, Bijectors],

diff --git a/docs/src/api.md b/docs/src/api.md
@@ -48,25 +48,25 @@ even though [`Prior()`](@ref) is actually defined in the `Turing.Inference` modu
 
 ### Samplers
 
-| Exported symbol      | Documentation                                 | Description                                                      |
-| ---                  | ---                                           | ---                                                              |
-| `Prior`              | [`Turing.Inference.Prior`](@ref)              | Sample from the prior distribution                               |
-| `MH`                 | [`Turing.Inference.MH`](@ref)                 | Metropolis–Hastings                                              |
-| `Emcee`              | [`Turing.Inference.Emcee`](@ref)              | Affine-invariant ensemble sampler                                |
-| `ESS`                | [`Turing.Inference.ESS`](@ref)                | Elliptical slice sampling                                        |
-| `Gibbs`              | [`Turing.Inference.Gibbs`](@ref)              | Gibbs sampling                                                   |
-| `GibbsConditional`   | [`Turing.Inference.GibbsConditional`](@ref)   | A "pseudo-sampler" to provide analytical conditionals to `Gibbs` |
-| `HMC`                | [`Turing.Inference.HMC`](@ref)                | Hamiltonian Monte Carlo                                          |
-| `SGLD`               | [`Turing.Inference.SGLD`](@ref)               | Stochastic gradient Langevin dynamics                            |
-| `SGHMC`              | [`Turing.Inference.SGHMC`](@ref)              | Stochastic gradient Hamiltonian Monte Carlo                      |
-| `HMCDA`              | [`Turing.Inference.HMCDA`](@ref)              | Hamiltonian Monte Carlo with dual averaging                      |
-| `NUTS`               | [`Turing.Inference.NUTS`](@ref)               | No-U-Turn Sampler                                                |
-| `PolynomialStepsize` | [`Turing.Inference.PolynomialStepsize`](@ref) | A function to generate a polynomially decaying step size         |
-| `IS`                 | [`Turing.Inference.IS`](@ref)                 | Importance sampling                                              |
-| `SMC`                | [`Turing.Inference.SMC`](@ref)                | Sequential Monte Carlo                                           |
-| `PG`                 | [`Turing.Inference.PG`](@ref)                 | Particle Gibbs                                                   |
-| `CSMC`               | [`Turing.Inference.CSMC`](@ref)               | The same as PG                                                   |
-| `externalsampler`    | [`Turing.Inference.externalsampler`](@ref)    | Wrap an external sampler for use in Turing                       |
+| Exported symbol      | Documentation                                 | Description                                                         |
+| ---                  | ---                                           | ---                                                                 |
+| `Prior`              | [`Turing.Inference.Prior`](@ref)              | Sample from the prior distribution                                  |
+| `MH`                 | [`Turing.Inference.MH`](@ref)                 | Metropolis–Hastings                                                 |
+| `Emcee`              | [`Turing.Inference.Emcee`](@ref)              | Affine-invariant ensemble sampler                                   |
+| `ESS`                | [`Turing.Inference.ESS`](@ref)                | Elliptical slice sampling                                           |
+| `Gibbs`              | [`Turing.Inference.Gibbs`](@ref)              | Gibbs sampling                                                      |
+| `GibbsConditional`   | [`Turing.Inference.GibbsConditional`](@ref)   | A "pseudo-sampler" to provide analytical conditionals to `Gibbs`    |
+| `HMC`                | [`Turing.Inference.HMC`](@ref)                | Hamiltonian Monte Carlo                                             |
+| `SGLD`               | [`Turing.Inference.SGLD`](@ref)               | Stochastic gradient Langevin dynamics                               |
+| `SGHMC`              | [`Turing.Inference.SGHMC`](@ref)              | Stochastic gradient Hamiltonian Monte Carlo                         |
+| `PolynomialStepsize` | [`Turing.Inference.PolynomialStepsize`](@ref) | Returns a function which generates polynomially decaying step sizes |
+| `HMCDA`              | [`Turing.Inference.HMCDA`](@ref)              | Hamiltonian Monte Carlo with dual averaging                         |
+| `NUTS`               | [`Turing.Inference.NUTS`](@ref)               | No-U-Turn Sampler                                                   |
+| `IS`                 | [`Turing.Inference.IS`](@ref)                 | Importance sampling                                                 |
+| `SMC`                | [`Turing.Inference.SMC`](@ref)                | Sequential Monte Carlo                                              |
+| `PG`                 | [`Turing.Inference.PG`](@ref)                 | Particle Gibbs                                                      |
+| `CSMC`               | [`Turing.Inference.CSMC`](@ref)               | The same as PG                                                      |
+| `externalsampler`    | [`Turing.Inference.externalsampler`](@ref)    | Wrap an external sampler for use in Turing                          |
 
 ### Variational inference