diff --git a/networks/lora_lumina.py b/networks/lora_lumina.py
index e4149b4a..0929e839 100644
--- a/networks/lora_lumina.py
+++ b/networks/lora_lumina.py
@@ -562,23 +562,26 @@ class LoRANetwork(torch.nn.Module):
 
                         # Set dim/alpha to modules dim/alpha
                         if modules_dim is not None and modules_alpha is not None:
-                            # モジュール指定あり
+                            # network from weights
                             if lora_name in modules_dim:
                                 dim = modules_dim[lora_name]
                                 alpha = modules_alpha[lora_name]
+                            else:
+                                dim = 0 # skip if not found
 
-                        # Set dims to type_dims
-                        if is_lumina and type_dims is not None:
-                            identifier = [
-                                ("attention",),  # attention layers
-                                ("mlp",),       # MLP layers
-                                ("modulation",), # modulation layers
-                                ("refiner",),   # refiner blocks
-                            ]
-                            for i, d in enumerate(type_dims):
-                                if d is not None and all([id in lora_name for id in identifier[i]]):
-                                    dim = d  # may be 0 for skip
-                                    break
+                        else:
+                            # Set dims to type_dims
+                            if is_lumina and type_dims is not None:
+                                identifier = [
+                                    ("attention",),  # attention layers
+                                    ("mlp",),       # MLP layers
+                                    ("modulation",), # modulation layers
+                                    ("refiner",),   # refiner blocks
+                                ]
+                                for i, d in enumerate(type_dims):
+                                    if d is not None and all([id in lora_name for id in identifier[i]]):
+                                        dim = d  # may be 0 for skip
+                                        break
 
                         # Drop blocks if we are only training some blocks
                         if (