From 59ce286b724ad7d39c8eafadc443bf57486ae154 Mon Sep 17 00:00:00 2001
From: Roulbac <oulbacha.reda@gmail.com>
Date: Wed, 30 Jan 2019 11:30:14 -0500
Subject: [PATCH] Important node to gradient penalty for wgangp

As recommended in https://arxiv.org/pdf/1704.00028.pdf, using WGAN-GP loss needs not to use a normalization layer.
---
 models/networks.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/models/networks.py b/models/networks.py
index c49b9b7bda0..fcc2b6bc567 100644
--- a/models/networks.py
+++ b/models/networks.py
@@ -281,6 +281,7 @@ def cal_gradient_penalty(netD, real_data, fake_data, device, type='mixed', const
         lambda_gp (float)           -- weight for this loss
 
     Returns the gradient penalty loss
+    NOTE: Strongly advised not to use batch/instance norm with the Discriminator(or Critic) if using gradient penalty!
     """
     if lambda_gp > 0.0:
         if type == 'real':   # either use real images, fake images, or a linear interpolation of two.