diff --git a/codes/models/ExtensibleTrainer.py b/codes/models/ExtensibleTrainer.py
index 9d4339f8..86d7e1fd 100644
--- a/codes/models/ExtensibleTrainer.py
+++ b/codes/models/ExtensibleTrainer.py
@@ -300,7 +300,8 @@ class ExtensibleTrainer(BaseModel):
             for name, net in netdict.items():
                 load_path = self.opt['path']['pretrain_model_%s' % (name,)]
                 if load_path is not None:
-                    logger.info('Loading model for [%s]' % (load_path))
+                    if self.rank <= 0:
+                        logger.info('Loading model for [%s]' % (load_path,))
                     self.load_network(load_path, net, self.opt['path']['strict_load'])
 
     def save(self, iter_step):
diff --git a/codes/train.py b/codes/train.py
index af709a3f..0c732664 100644
--- a/codes/train.py
+++ b/codes/train.py
@@ -294,7 +294,7 @@ def main():
                     # log
                     logger.info('# Validation # PSNR: {:.4e} Fea: {:.4e}'.format(avg_psnr, avg_fea_loss))
                     # tensorboard logger
-                    if opt['use_tb_logger'] and 'debug' not in opt['name']:
+                    if opt['use_tb_logger'] and 'debug' not in opt['name'] and rank <= 0:
                         #tb_logger.add_scalar('val_psnr', avg_psnr, current_step)
                         tb_logger.add_scalar('val_fea', avg_fea_loss, current_step)