diff --git a/codes/models/steps/tecogan_losses.py b/codes/models/steps/tecogan_losses.py
index 100ee9fa..52cac3c9 100644
--- a/codes/models/steps/tecogan_losses.py
+++ b/codes/models/steps/tecogan_losses.py
@@ -238,6 +238,7 @@ class TecoGanLoss(ConfigurableLoss):
         self.min_loss = opt['min_loss'] if 'min_loss' in opt.keys() else 0
         self.margin = opt['margin']  # Per the tecogan paper, the GAN loss only pays attention to an inner part of the image with the margin removed, to get rid of artifacts resulting from flow errors.
         self.ff = opt['fast_forward'] if 'fast_forward' in opt.keys() else False
+        self.noise = opt['noise'] if 'noise' in opt.keys() else 0
 
     def forward(self, _, state):
         if self.ff:
@@ -288,6 +289,9 @@ class TecoGanLoss(ConfigurableLoss):
     def compute_loss(self, real_sext, fake_sext):
         fp16 = self.env['opt']['fp16']
         net = self.env['discriminators'][self.opt['discriminator']]
+        if self.noise != 0:
+            real_sext += torch.randn_like(real_sext) * self.noise
+            fake_sext += torch.randn_like(fake_sext) * self.noise
         with autocast(enabled=fp16):
             d_fake = net(fake_sext)
             d_real = net(real_sext)