Fix issue with kohya locon not training the convolution layers

README.md

@@ -189,7 +189,11 @@ This will store your a backup file with your current locally installed pip packa
 
 ## Change History
 
-* 2023.03/12 (v21.2.3):
+* 2023/03/12 (v21.2.4):
+    - Fix issue with kohya locon not training the convolution layers
+    - Update LyCORIS module version
+    - Update LyCORYS locon extract tool
+* 2023/03/12 (v21.2.3):
     - Add validation that all requirements are met before starting the GUI.
 * 2023/03/11 (v21.2.2):
     - Add support for LoRA LoHa type. See https://github.com/KohakuBlueleaf/LyCORIS for more details.

lora_gui.py

@@ -507,7 +507,7 @@ def train_model(
     if LoRA_type == 'Kohya LoCon':
         run_cmd += f' --network_module=networks.lora'
         run_cmd += (
-            f' --network_args "conv_lora_dim={conv_dim}" "conv_alpha={conv_alpha}"'
+            f' --network_args "conv_dim={conv_dim}" "conv_alpha={conv_alpha}"'
         )
     if LoRA_type == 'Standard':
         run_cmd += f' --network_module=networks.lora'

requirements.txt

@@ -25,6 +25,6 @@ timm==0.6.12
 huggingface-hub==0.12.0
 tensorflow==2.10.1
 # For locon support
-lycoris_lora==0.0.9
+lycoris_lora==0.1.2
 # for kohya_ss library
 .

tools/lycoris_locon_extract.py

@@ -69,6 +69,18 @@ def get_args():
         "--conv_quantile", help="singular value quantile for conv layer quantile mode",
         default=1., type=float
     )
+    parser.add_argument(
+        "--use_sparse_bias", help="enable sparse bias",
+        default=False, action="store_true"
+    )
+    parser.add_argument(
+        "--sparsity", help="sparsity for sparse bias",
+        default=0.98, type=float
+    )
+    parser.add_argument(
+        "--disable_cp", help="don't use cp decomposition",
+        default=False, action="store_true"
+    )
     return parser.parse_args()
 ARGS = get_args()
 
@@ -102,7 +114,9 @@ def main():
         base, db,
         args.mode,
         linear_mode_param, conv_mode_param,
-        args.device
+        args.device, 
+        args.use_sparse_bias, args.sparsity,
+        # not args.disable_small_conv
     )
     
     if args.safetensors: