diff --git a/codes/models/SRGAN_model.py b/codes/models/SRGAN_model.py
index 3183d4d9..ad151c88 100644
--- a/codes/models/SRGAN_model.py
+++ b/codes/models/SRGAN_model.py
@@ -92,6 +92,7 @@ class SRGANModel(BaseModel):
             self.D_noise_theta = train_opt['D_noise_theta_init'] if train_opt['D_noise_theta_init'] else 0
             self.D_noise_final = train_opt['D_noise_final_it'] if train_opt['D_noise_final_it'] else 0
             self.D_noise_theta_floor = train_opt['D_noise_theta_floor'] if train_opt['D_noise_theta_floor'] else 0
+            self.corruptor_swapout_steps = train_opt['corruptor_swapout_steps'] if train_opt['corruptor_swapout_steps'] else 500
 
             # optimizers
             # G
@@ -161,6 +162,7 @@ class SRGANModel(BaseModel):
 
         self.print_network()  # print network
         self.load()  # load G and D if needed
+        self.load_random_corruptor()
 
     def feed_data(self, data, need_GT=True):
         # Corrupt the data with the given corruptor, if specified.
@@ -346,6 +348,9 @@ class SRGANModel(BaseModel):
         self.add_log_entry('D_fake', torch.mean(pred_d_fake.detach()))
         self.add_log_entry('noise_theta', noise_theta)
 
+        if step % self.corruptor_swapout_steps == 0 and step > 0:
+            self.load_random_corruptor()
+
     # Allows the log to serve as an easy-to-use rotating buffer.
     def add_log_entry(self, key, value):
         key_it = "%s_it" % (key,)
@@ -377,13 +382,13 @@ class SRGANModel(BaseModel):
             self.swapout_D_duration -= 1
             if self.swapout_D_duration == 0:
                 # Swap back.
-                print("Swapping back to current D model: %s" % (self.stashed_D,))
+                logger.info("Swapping back to current D model: %s" % (self.stashed_D,))
                 self.load_network(self.stashed_D, self.netD, self.opt['path']['strict_load'])
                 self.stashed_D = None
         elif self.swapout_D_freq != 0 and step % self.swapout_D_freq == 0:
             swapped_model = self.pick_rand_prev_model('D')
             if swapped_model is not None:
-                print("Swapping to previous D model: %s" % (swapped_model,))
+                logger.info("Swapping to previous D model: %s" % (swapped_model,))
                 self.stashed_D = self.save_network(self.netD, 'D', 'swap_model')
                 self.load_network(swapped_model, self.netD, self.opt['path']['strict_load'])
                 self.swapout_D_duration = self.swapout_duration
@@ -478,6 +483,14 @@ class SRGANModel(BaseModel):
             logger.info('Loading model for D [{:s}] ...'.format(load_path_D))
             self.load_network(load_path_D, self.netD, self.opt['path']['strict_load'])
 
+    def load_random_corruptor(self):
+        if self.netC is None:
+            return
+        corruptor_files = glob.glob(os.path.join(self.opt['path']['pretrained_corruptors_dir'], "*.pth"))
+        corruptor_to_load = corruptor_files[random.randint(0, len(corruptor_files)-1)]
+        logger.info('Swapping corruptor to: %s' % (corruptor_to_load,))
+        self.load_network(corruptor_to_load, self.netC, self.opt['path']['strict_load'])
+
     def save(self, iter_step):
         self.save_network(self.netG, 'G', iter_step)
         self.save_network(self.netD, 'D', iter_step)