Bump Turing/DynamicPPL compat (#214)

* Bump compat for Turing -> 0.35, DynamicPPL -> 0.29 * Fix links to old Turing website * Bump patch version * Increment patch number --------- Co-authored-by: Seth Axen <[email protected]>
mlcolab · Oct 25, 2024 · 8211737 · 8211737 · sethaxen · Oct 25, 2024
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diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "Pathfinder"
 uuid = "b1d3bc72-d0e7-4279-b92f-7fa5d6d2d454"
 authors = ["Seth Axen <[email protected]> and contributors"]
-version = "0.9.3"
+version = "0.9.4"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -41,7 +41,7 @@ ADTypes = "0.2, 1"
 Accessors = "0.1.12"
 Distributions = "0.25.87"
 DynamicHMC = "3.4.0"
-DynamicPPL = "0.25.2, 0.27, 0.28"
+DynamicPPL = "0.25.2, 0.27, 0.28, 0.29"
 Folds = "0.2.9"
 ForwardDiff = "0.10.19"
 IrrationalConstants = "0.1.1, 0.2"
@@ -62,7 +62,7 @@ SciMLBase = "1.95.0, 2"
 Statistics = "1.6"
 StatsBase = "0.33.7, 0.34"
 Transducers = "0.4.81"
-Turing = "0.31.4, 0.32, 0.33, 0.34"
+Turing = "0.31.4, 0.32, 0.33, 0.34, 0.35"
 UnPack = "1"
 julia = "1.6"
 

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -30,4 +30,4 @@ StatsFuns = "1"
 StatsPlots = "0.14.21, 0.15"
 TransformVariables = "0.6.2, 0.7, 0.8"
 TransformedLogDensities = "1.0.2"
-Turing = "0.31.4, 0.32, 0.33, 0.34"
+Turing = "0.31.4, 0.32, 0.33, 0.34, 0.35"
diff --git a/docs/src/examples/initializing-hmc.md b/docs/src/examples/initializing-hmc.md
@@ -17,7 +17,7 @@ Pathfinder can be used to initialize MCMC, and in particular HMC, in 3 ways:
 
 This tutorial demonstrates all three approaches with [DynamicHMC.jl](https://tamaspapp.eu/DynamicHMC.jl/stable/) and [AdvancedHMC.jl](https://github.com/TuringLang/AdvancedHMC.jl).
 Both of these packages have standalone implementations of adaptive HMC (aka NUTS) and can be used independently of any probabilistic programming language (PPL).
-Both the [Turing](https://turing.ml/stable/) and [Soss](https://github.com/cscherrer/Soss.jl) PPLs have some DynamicHMC integration, while Turing also integrates with AdvancedHMC.
+Both the [Turing](https://turinglang.org/) and [Soss](https://github.com/cscherrer/Soss.jl) PPLs have some DynamicHMC integration, while Turing also integrates with AdvancedHMC.
 
 For demonstration purposes, we'll use the following dummy data:
 
@@ -234,4 +234,4 @@ samples_ahmc3, stats_ahmc3 = sample(
 )
 ```
 
-[^1]: https://mc-stan.org/docs/reference-manual/hmc-algorithm-parameters.html
+[^1]: https://mc-stan.org/docs/reference-manual/hmc-algorithm-parameters.html
diff --git a/docs/src/examples/turing.md b/docs/src/examples/turing.md
@@ -1,6 +1,6 @@
 # Running Pathfinder on Turing.jl models
 
-This tutorial demonstrates how [Turing](https://turing.ml/stable/) can be used with Pathfinder.
+This tutorial demonstrates how [Turing](https://turinglang.org/) can be used with Pathfinder.
 
 We'll demonstrate with a regression example.
 

diff --git a/test/integration/Turing/Project.toml b/test/integration/Turing/Project.toml
@@ -9,5 +9,5 @@ Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 [compat]
 LogDensityProblems = "2.1.0"
 Pathfinder = "0.9"
-Turing = "0.31.4, 0.32, 0.33, 0.34"
+Turing = "0.31.4, 0.32, 0.33, 0.34, 0.35"
 julia = "1.6"