From 28fcc616ebc286d504a8adae9b71df430057be7f Mon Sep 17 00:00:00 2001
From: Penelope Yong <penelopeysm@gmail.com>
Date: Mon, 25 Nov 2024 19:02:51 +0000
Subject: [PATCH] Use Mooncake in BNN doc (#521)

---
 tutorials/03-bayesian-neural-network/index.qmd | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tutorials/03-bayesian-neural-network/index.qmd b/tutorials/03-bayesian-neural-network/index.qmd
index fcfa7502f..87d556634 100755
--- a/tutorials/03-bayesian-neural-network/index.qmd
+++ b/tutorials/03-bayesian-neural-network/index.qmd
@@ -19,7 +19,7 @@ using Turing
 using FillArrays
 using Lux
 using Plots
-using Tracker
+import Mooncake
 using Functors
 
 using LinearAlgebra
@@ -208,7 +208,7 @@ setprogress!(false)
 ```{julia}
 # Perform inference.
 N = 2_000
-ch = sample(bayes_nn(reduce(hcat, xs), ts), NUTS(; adtype=AutoTracker()), N);
+ch = sample(bayes_nn(reduce(hcat, xs), ts), NUTS(; adtype=AutoMooncake(; config=nothing)), N);
 ```
 
 Now we extract the parameter samples from the sampled chain as `θ` (this is of size `5000 x 20` where `5000` is the number of iterations and `20` is the number of parameters).