fix ?

wan/any2video.py

@@ -683,7 +683,7 @@ class WanAny2V:
         # init denoising
         updated_num_steps= len(timesteps)
         if callback != None:
-            from wgp import update_loras_slists
+            from wan.utils.utils import update_loras_slists
             update_loras_slists(self.model, loras_slists, updated_num_steps)
             callback(-1, None, True, override_num_inference_steps = updated_num_steps)
 

wan/diffusion_forcing.py

@@ -19,7 +19,7 @@ from wan.utils.utils import calculate_new_dimensions
 from .utils.fm_solvers import (FlowDPMSolverMultistepScheduler,
                                get_sampling_sigmas, retrieve_timesteps)
 from .utils.fm_solvers_unipc import FlowUniPCMultistepScheduler
-from wgp import update_loras_slists
+from wan.utils.utils import update_loras_slists
 
 class DTT2V:
 

wan/utils/utils.py

@@ -34,6 +34,12 @@ def seed_everything(seed: int):
     if torch.backends.mps.is_available():
         torch.mps.manual_seed(seed)
 
+def update_loras_slists(trans, slists, num_inference_steps ):
+    from mmgp import offload
+    slists = [ expand_slist(slist, num_inference_steps ) if isinstance(slist, list) else slist for slist in slists ]
+    nos = [str(l) for l in range(len(slists))]
+    offload.activate_loras(trans, nos, slists ) 
+
 def resample(video_fps, video_frames_count, max_target_frames_count, target_fps, start_target_frame ):
     import math
 

wgp.py

@@ -2107,7 +2107,8 @@ for file_path in models_def_paths:
     settings = json_def   
     existing_model_def = models_def.get(model_type, None) 
     if existing_model_def is not None:
-        existing_settings = models_def["settings"]
+        existing_settings = models_def.get("settings", None)
+        if existing_settings != None:
             existing_settings.update(settings)
         existing_model_def.update(model_def)
     else: