diff --git a/codes/models/ExtensibleTrainer.py b/codes/models/ExtensibleTrainer.py
index 079da6e1..88e34671 100644
--- a/codes/models/ExtensibleTrainer.py
+++ b/codes/models/ExtensibleTrainer.py
@@ -298,6 +298,8 @@ class ExtensibleTrainer(BaseModel):
     def load(self):
         for netdict in [self.netsG, self.netsD]:
             for name, net in netdict.items():
+                if not self.opt['networks'][name]['trainable']:
+                    continue
                 load_path = self.opt['path']['pretrain_model_%s' % (name,)]
                 if load_path is not None:
                     if self.rank <= 0:
diff --git a/codes/models/steps/tecogan_losses.py b/codes/models/steps/tecogan_losses.py
index ea8b1017..1c033c60 100644
--- a/codes/models/steps/tecogan_losses.py
+++ b/codes/models/steps/tecogan_losses.py
@@ -7,6 +7,7 @@ import torch.nn.functional as F
 import os
 import os.path as osp
 import torchvision
+import torch.distributed as dist
 
 def create_teco_loss(opt, env):
     type = opt['type']
@@ -123,6 +124,8 @@ class RecurrentImageGeneratorSequenceInjector(Injector):
         return {self.output: results}
 
     def produce_teco_visual_debugs(self, gen_input, it):
+        if dist.get_rank() > 0:
+            return
         base_path = osp.join(self.env['base_path'], "..", "visual_dbg", "teco_geninput", str(self.env['step']))
         os.makedirs(base_path, exist_ok=True)
         torchvision.utils.save_image(gen_input[:, :3], osp.join(base_path, "%s_img.png" % (it,)))
@@ -192,6 +195,8 @@ class TecoGanLoss(ConfigurableLoss):
         return l_total
 
     def produce_teco_visual_debugs(self, sext, lbl, it):
+        if dist.get_rank() > 0:
+            return
         base_path = osp.join(self.env['base_path'], "..", "visual_dbg", "teco_sext", str(self.env['step']), lbl)
         os.makedirs(base_path, exist_ok=True)
         lbls = ['img_a', 'img_b', 'img_c', 'flow_a', 'flow_b', 'flow_c']
@@ -220,8 +225,10 @@ class PingPongLoss(ConfigurableLoss):
         return l_total
 
     def produce_teco_visual_debugs(self, imglist):
+        if dist.get_rank() > 0:
+            return
         base_path = osp.join(self.env['base_path'], "..", "visual_dbg", "teco_pingpong", str(self.env['step']))
         os.makedirs(base_path, exist_ok=True)
         assert isinstance(imglist, list)
         for i, img in enumerate(imglist):
-            torchvision.utils.save_image(img, osp.join(base_path, "%s.png" % (i, )))
\ No newline at end of file
+            torchvision.utils.save_image(img, osp.join(base_path, "%s.png" % (i, )))