From da6a1979ff16cae8bebc3475849ffcc4114aa2c9 Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Tue, 28 Jan 2025 18:47:45 -0500
Subject: [PATCH] cleanup lora overrides

Signed-off-by: Vladimir Mandic <mandic00@live.com>
---
 modules/lora/extra_networks_lora.py | 11 ++++++----
 modules/lora/network_overrides.py   | 31 +++++++++++++++--------------
 scripts/xyz_grid_shared.py          |  2 +-
 3 files changed, 24 insertions(+), 20 deletions(-)

diff --git a/modules/lora/extra_networks_lora.py b/modules/lora/extra_networks_lora.py
index 448b214ac..357c5291f 100644
--- a/modules/lora/extra_networks_lora.py
+++ b/modules/lora/extra_networks_lora.py
@@ -179,11 +179,14 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
             networks.previously_loaded_networks = networks.loaded_networks.copy()
             debug_log(f'Load network: type=LoRA active={[n.name for n in networks.previously_loaded_networks]} deactivate')
         if shared.native and len(networks.diffuser_loaded) > 0:
-            if hasattr(shared.sd_model, "unload_lora_weights") and hasattr(shared.sd_model, "text_encoder"):
-                if not (shared.compiled_model_state is not None and shared.compiled_model_state.is_compiled is True):
+            if not (shared.compiled_model_state is not None and shared.compiled_model_state.is_compiled is True):
+                if hasattr(shared.sd_model, "unfuse_lora"):
+                    try:
+                        shared.sd_model.unfuse_lora()
+                    except Exception:
+                        pass
+                if hasattr(shared.sd_model, "unload_lora_weights"):
                     try:
-                        if shared.opts.lora_fuse_diffusers:
-                            shared.sd_model.unfuse_lora()
                         shared.sd_model.unload_lora_weights() # fails for non-CLIP models
                     except Exception:
                         pass
diff --git a/modules/lora/network_overrides.py b/modules/lora/network_overrides.py
index 81bd07ce1..65448ef2d 100644
--- a/modules/lora/network_overrides.py
+++ b/modules/lora/network_overrides.py
@@ -2,31 +2,32 @@ from modules import shared
 
 
 maybe_diffusers = [ # forced if lora_maybe_diffusers is enabled
-    'aaebf6360f7d', # sd15-lcm
-    '3d18b05e4f56', # sdxl-lcm
-    'b71dcb732467', # sdxl-tcd
-    '813ea5fb1c67', # sdxl-turbo
+    # 'aaebf6360f7d', # sd15-lcm
+    # '3d18b05e4f56', # sdxl-lcm
+    # 'b71dcb732467', # sdxl-tcd
+    # '813ea5fb1c67', # sdxl-turbo
     # not really needed, but just in case
-    '5a48ac366664', # hyper-sd15-1step
-    'ee0ff23dcc42', # hyper-sd15-2step
-    'e476eb1da5df', # hyper-sd15-4step
-    'ecb844c3f3b0', # hyper-sd15-8step
-    '1ab289133ebb', # hyper-sd15-8step-cfg
-    '4f494295edb1', # hyper-sdxl-8step
-    'ca14a8c621f8', # hyper-sdxl-8step-cfg
-    '1c88f7295856', # hyper-sdxl-4step
-    'fdd5dcd1d88a', # hyper-sdxl-2step
-    '8cca3706050b', # hyper-sdxl-1step
+    # '5a48ac366664', # hyper-sd15-1step
+    # 'ee0ff23dcc42', # hyper-sd15-2step
+    # 'e476eb1da5df', # hyper-sd15-4step
+    # 'ecb844c3f3b0', # hyper-sd15-8step
+    # '1ab289133ebb', # hyper-sd15-8step-cfg
+    # '4f494295edb1', # hyper-sdxl-8step
+    # 'ca14a8c621f8', # hyper-sdxl-8step-cfg
+    # '1c88f7295856', # hyper-sdxl-4step
+    # 'fdd5dcd1d88a', # hyper-sdxl-2step
+    # '8cca3706050b', # hyper-sdxl-1step
 ]
 
 force_diffusers = [ # forced always
     '816d0eed49fd', # flash-sdxl
     'c2ec22757b46', # flash-sd15
+    '22c8339e7666', # spo-sdxl-10ep
 ]
 
 force_models = [ # forced always
-    'sc',
     # 'sd3',
+    'sc',
     'kandinsky',
     'hunyuandit',
     'hunyuanvideo',
diff --git a/scripts/xyz_grid_shared.py b/scripts/xyz_grid_shared.py
index efd70724b..a3f7a3da9 100644
--- a/scripts/xyz_grid_shared.py
+++ b/scripts/xyz_grid_shared.py
@@ -213,7 +213,7 @@ def list_lora():
     import sys
     lora = [v for k, v in sys.modules.items() if k == 'networks' or k == 'modules.lora.networks'][0]
     loras = [v.fullname for v in lora.available_networks.values()]
-    return ['None'] + loras
+    return ['None'] + sorted(loras)
 
 
 def apply_lora(p, x, xs):