diff --git a/networks/lora.py b/networks/lora.py
index 9f2f5094..27f59344 100644
--- a/networks/lora.py
+++ b/networks/lora.py
@@ -400,7 +400,7 @@ def parse_block_lr_kwargs(nw_kwargs):
     return down_lr_weight, mid_lr_weight, up_lr_weight
 
 
-def create_network(multiplier, network_dim, network_alpha, vae, text_encoder, unet, dropout=None, **kwargs):
+def create_network(multiplier, network_dim, network_alpha, vae, text_encoder, unet, neuron_dropout=None, **kwargs):
     if network_dim is None:
         network_dim = 4  # default
     if network_alpha is None:
@@ -455,7 +455,7 @@ def create_network(multiplier, network_dim, network_alpha, vae, text_encoder, un
         multiplier=multiplier,
         lora_dim=network_dim,
         alpha=network_alpha,
-        dropout=dropout,
+        dropout=neuron_dropout,
         rank_dropout=rank_dropout,
         module_dropout=module_dropout,
         conv_lora_dim=conv_dim,
diff --git a/train_network.py b/train_network.py
index c6ea7e4e..b62aef7e 100644
--- a/train_network.py
+++ b/train_network.py
@@ -212,7 +212,7 @@ def train(args):
     else:
         # LyCORIS will work with this...
         network = network_module.create_network(
-            1.0, args.network_dim, args.network_alpha, vae, text_encoder, unet, dropout=args.network_dropout, **net_kwargs
+            1.0, args.network_dim, args.network_alpha, vae, text_encoder, unet, neuron_dropout=args.network_dropout, **net_kwargs
         )
     if network is None:
         return
@@ -724,7 +724,7 @@ def train(args):
             progress_bar.set_postfix(**logs)
 
             if args.scale_weight_norms:
-                progress_bar.set_postfix(**{**max_mean_logs,**logs})
+                progress_bar.set_postfix(**{**max_mean_logs, **logs})
 
             if args.logging_dir is not None:
                 logs = generate_step_logs(args, current_loss, avr_loss, lr_scheduler, keys_scaled, mean_norm, maximum_norm)