From bec9e7ab0f57cd0d632621f17b4b6895c723ef87 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Laure=CE=B7t?= <laurent@fainsin.bzh>
Date: Mon, 28 Aug 2023 16:46:34 +0200
Subject: [PATCH] ddpm cfg algo requirements fix

---
 pdf/paper.tex | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pdf/paper.tex b/pdf/paper.tex
index 76a619d..a1553c8 100644
--- a/pdf/paper.tex
+++ b/pdf/paper.tex
@@ -710,10 +710,10 @@ Formellement, l'algorithme d'entraînement par \gls{cfg} est décrit dans l'algo
   \begin{algorithmic}[1]
     \Require $T \in \mathbb{N}^\star$: number of diffusion steps
     \Require $\alpha_t \in \mathbb{R}^T$: variance schedule
+    \Require $p_\text{uncond} \in [0, 1]$: probability of unconditional training
     \Require $\boldsymbol{x}_0$: data distribution to be learned
-    \Require $\boldsymbol{c}$: embeddings distribution to be learned
+    \Require $\boldsymbol{c}$: embedding distribution to be learned
     \Require $\epsilon_\theta$: neural network
-    \Require $p_\text{uncond}$: probability of unconditional training
     \Repeat
     \State $(x_0, c) \sim (\boldsymbol{x_0}, \boldsymbol{c})$
     \State $c \leftarrow \varnothing$ with probability $p_\text{uncond}$