cleanup repo

.gitmodules

@@ -36,9 +36,6 @@
 [submodule "extensions-builtin/sd-webui-controlnet"]
 	path = extensions-builtin/sd-webui-controlnet
 	url = https://github.com/Mikubill/sd-webui-controlnet
-[submodule "modules/locon"]
-	path = modules/locon
-	url = https://github.com/KohakuBlueleaf/LoCon
 [submodule "modules/lycoris"]
 	path = modules/lycoris
 	url = https://github.com/KohakuBlueleaf/LyCORIS

.vscode/settings.json

@@ -3,6 +3,8 @@
     "./modules/lora",
     "./repositories/BLIP",
     "./repositories/CodeFormer",
+    "./repositories/k-diffusion",
+    "./repositories/taming-transformers",
     "./repositories/stable-diffusion-stability-ai"
   ],
   "python.analysis.typeCheckingMode": "off"

README.md

@@ -124,7 +124,7 @@ Fork does differ in few things:
 - Uses simplified folder structure  
   e.g. `/train`, `/outputs/*`  
 - Modified training templates  
-- Built-in `LoRA`, `Custom Diffusion`, `Dreambooth` training  
+- Built-in `LoRA`, `LyCORIS`, `Custom Diffusion`, `Dreambooth` training  
 
 Only Python library which is not auto-updated is `PyTorch` itself as that is very system specific  
 For some Torch optimizations notes, see Wiki

cli/train-lora.py

@@ -268,10 +268,6 @@ if __name__ == '__main__':
         time.sleep(1)
 
     if args.lycoris:
-        # python3 sd-scripts/train_network.py --network_module locon.locon_kohya --network_dim "RANK_FOR_TRANSFORMER" --network_alpha "ALPHA_FOR_TRANSFORMER" --network_args "conv_dim=RANK_FOR_CONV" "conv_alpha=ALPHA_FOR_CONV" "dropout=DROPOUT_RATE"
-        # options.network_dim = 'RANK_FOR_TRANSFORMER'
-        # options.network_alpha = 'ALPHA_FOR_TRANSFORMER'
-        # options.network_args = ['conv_dim=RANK_FOR_CONV', 'conv_alpha=ALPHA_FOR_CONV', 'dropout=DROPOUT_RATE']
         log.info({ 'using lycoris network': True })
         options.network_module = 'lycoris.kohya'
     if not args.notrain: