Fix bad Lora parameters (#2341)

kohya_gui/lora_gui.py

@@ -69,32 +69,6 @@
 ]
 
 
-def update_network_args_with_kohya_lora_vars(
-    network_args: str, kohya_lora_var_list: list, vars: dict
-) -> str:
-    """
-    Update network arguments with Kohya LoRA variables.
-
-    Args:
-        network_args (str): The network arguments.
-        kohya_lora_var_list (list): The list of Kohya LoRA variables.
-        vars (dict): The dictionary of variables.
-
-    Returns:
-        str: The updated network arguments.
-    """
-    # Filter out variables that are in the Kohya LoRA variable list and have a value
-    kohya_lora_vars = {
-        key: value for key, value in vars if key in kohya_lora_var_list and value
-    }
-
-    # Iterate over the Kohya LoRA variables and append them to the network arguments
-    for key, value in kohya_lora_vars.items():
-        # Append each variable as a key-value pair to the network_args
-        network_args += f" {key}={value}"
-    return network_args
-
-
 def save_configuration(
     save_as_bool,
     file_path,
@@ -960,11 +934,17 @@ def train_model(
             "module_dropout",
         ]
         network_module = "networks.lora"
-        network_args += update_network_args_with_kohya_lora_vars(
-            network_args=network_args,
-            kohya_lora_var_list=kohya_lora_var_list,
-            vars=vars().items(),
-        )
+        kohya_lora_vars = {
+            key: value
+            for key, value in vars().items()
+            if key in kohya_lora_var_list and value
+        }
+        if LoRA_type == "Kohya LoCon":
+            network_args += f' conv_dim="{conv_dim}" conv_alpha="{conv_alpha}"'
+
+        for key, value in kohya_lora_vars.items():
+            if value:
+                network_args += f' {key}={value}'
 
     if LoRA_type in ["LoRA-FA"]:
         kohya_lora_var_list = [
@@ -979,12 +959,21 @@ def train_model(
             "rank_dropout",
             "module_dropout",
         ]
+
         network_module = "networks.lora_fa"
-        network_args += update_network_args_with_kohya_lora_vars(
-            network_args=network_args,
-            kohya_lora_var_list=kohya_lora_var_list,
-            vars=vars().items(),
-        )
+        kohya_lora_vars = {
+            key: value
+            for key, value in vars().items()
+            if key in kohya_lora_var_list and value
+        }
+
+        network_args = ""
+        if LoRA_type == "Kohya LoCon":
+            network_args += f' conv_dim="{conv_dim}" conv_alpha="{conv_alpha}"'
+
+        for key, value in kohya_lora_vars.items():
+            if value:
+                network_args += f' {key}={value}'
 
     if LoRA_type in ["Kohya DyLoRA"]:
         kohya_lora_var_list = [
@@ -1002,12 +991,20 @@ def train_model(
             "module_dropout",
             "unit",
         ]
+
         network_module = "networks.dylora"
-        network_args += update_network_args_with_kohya_lora_vars(
-            network_args=network_args,
-            kohya_lora_var_list=kohya_lora_var_list,
-            vars=vars().items(),
-        )
+        kohya_lora_vars = {
+            key: value
+            for key, value in vars().items()
+            if key in kohya_lora_var_list and value
+        }
+
+        network_args = ""
+
+        for key, value in kohya_lora_vars.items():
+            if value:
+                network_args += f' {key}={value}'
+
     # Convert learning rates to float once and store the result for re-use
     learning_rate = float(learning_rate) if learning_rate is not None else 0.0
     text_encoder_lr_float = (