From a27dd170975c104f9945063c332aad2ec8109dc0 Mon Sep 17 00:00:00 2001
From: Qingyu Qu <52615090+ErikQQY@users.noreply.github.com>
Date: Sun, 30 Jul 2023 11:18:47 +0800
Subject: [PATCH] Update docs/src/examples/hamiltonian_nn.md

---
 docs/src/examples/hamiltonian_nn.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/src/examples/hamiltonian_nn.md b/docs/src/examples/hamiltonian_nn.md
index f079af19c..b2f001659 100644
--- a/docs/src/examples/hamiltonian_nn.md
+++ b/docs/src/examples/hamiltonian_nn.md
@@ -63,7 +63,7 @@ ylabel!("Momentum (p)")
 The HNN predicts the gradients ``(\dot q, \dot p)`` given ``(q, p)``. Hence, we generate the pairs ``(q, p)`` using the equations given at the top. Additionally, to supervise the training, we also generate the gradients. Next, we use Flux DataLoader for automatically batching our dataset.
 
 ```@example hamiltonian
-using Flux, DiffEqFlux, DifferentialEquations, Statistics, Plots, ReverseDiff, Random, IterTools, Lux
+using Flux, DiffEqFlux, DifferentialEquations, Statistics, Plots, ReverseDiff, Random, IterTools, Lux, ComponentArrays
 
 t = range(0.0f0, 1.0f0, length = 1024)
 π_32 = Float32(π)