improve handling of wan22 stages

Signed-off-by: Vladimir Mandic <mandic00@live.com>

CHANGELOG.md

@@ -2,7 +2,13 @@
 
 ## Update for 2025-07-30
 
+- **Feature**  
+  - Wan select which stage to run: *first/second/both* with configurable *boundary ration* when running both stages  
+    in settings -> model options  
+- **UI**  
+  - modernui checkbox/radio styling  
 - **Fixes**  
+  - fix Wan2.2 5B I2V workflow  
   - fix inpaint image metadata  
   - fix processing image save loop  
   - fix api progress reporting endpoint  

installer.py

@@ -593,7 +593,7 @@ def check_diffusers():
     t_start = time.time()
     if args.skip_all or args.skip_git:
         return
-    sha = '56d438727036b0918b30bbe3110c5fe1634ed19d' # diffusers commit hash
+    sha = 'c052791b5fe29ce8a308bf63dda97aa205b729be' # diffusers commit hash
     pkg = pkg_resources.working_set.by_key.get('diffusers', None)
     minor = int(pkg.version.split('.')[1] if pkg is not None else -1)
     cur = opts.get('diffusers_version', '') if minor > -1 else ''

modules/interrogate/interrogate.py

@@ -9,6 +9,7 @@ def interrogate(image):
     if isinstance(image, dict) and 'name' in image:
         image = Image.open(image['name'])
     if image is None:
+        shared.log.error('Interrogate: no image provided')
         return ''
     t0 = time.time()
     if shared.opts.interrogate_default_type == 'OpenCLiP':

modules/shared.py

@@ -200,7 +200,8 @@ options_templates.update(options_section(('model_options', "Models Options"), {
     "model_h1_sep": OptionInfo("<h2>HiDream</h2>", "", gr.HTML),
     "model_h1_llama_repo": OptionInfo("Default", "LLama repo", gr.Textbox),
     "model_wan_sep": OptionInfo("<h2>WanAI</h2>", "", gr.HTML),
-    "model_wan_disable_t2": OptionInfo(True, "Disable second stage"),
+    "model_wan_stage": OptionInfo("first", "Processing stage", gr.Radio, {"choices": ['first', 'second', 'both'] }),
+    "model_wan_boundary": OptionInfo(0.85, "Stage boundary ratio", gr.Slider, {"minimum": 0, "maximum": 1.0, "step": 0.05 }),
 }))
 
 options_templates.update(options_section(('vae_encoder', "Variational Auto Encoder"), {

pipelines/model_wanai.py

@@ -8,11 +8,6 @@ def load_transformer(repo_id, diffusers_load_config={}, subfolder='transformer')
     load_args, quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model', device_map=True)
     fn = None
 
-    if subfolder == 'transformer_2' and 'a14b' not in repo_id.lower():
-        return None
-    if subfolder == 'transformer_2' and shared.opts.model_wan_disable_t2:
-        return None
-
     if shared.opts.sd_unet is not None and shared.opts.sd_unet != 'Default':
         from modules import sd_unet
         if shared.opts.sd_unet not in list(sd_unet.unet_dict):
@@ -63,13 +58,28 @@ def load_wan(checkpoint_info, diffusers_load_config={}):
     repo_id = sd_models.path_to_repo(checkpoint_info)
     sd_models.hf_auth_check(checkpoint_info)
 
-    transformer = load_transformer(repo_id, diffusers_load_config, 'transformer')
-    transformer_2 = load_transformer(repo_id, diffusers_load_config, 'transformer_2')
+    if 'a14b' in repo_id.lower():
+        if shared.opts.model_wan_stage == 'first':
+            transformer = load_transformer(repo_id, diffusers_load_config, 'transformer')
+            transformer_2 = None
+        elif shared.opts.model_wan_stage == 'second':
+            transformer = load_transformer(repo_id, diffusers_load_config, 'transformer_2')
+            transformer_2 = None
+        elif shared.opts.model_wan_stage == 'both':
+            transformer = load_transformer(repo_id, diffusers_load_config, 'transformer')
+            transformer_2 = load_transformer(repo_id, diffusers_load_config, 'transformer_2')
+        else:
+            shared.log.error(f'Load model: type=WanAI stage="{shared.opts.model_wan_stage}" unsupported')
+            return None 
+    else:
+        transformer = load_transformer(repo_id, diffusers_load_config, 'transformer')
+        transformer_2 = None
+
     text_encoder = load_text_encoder(repo_id, diffusers_load_config)
 
     load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model')
-    boundary_ratio = 0.8 if transformer_2 is not None else None
-    shared.log.debug(f'Load model: type=WanAI model="{checkpoint_info.name}" repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args} boundary={boundary_ratio}')
+    boundary_ratio = shared.opts.model_wan_boundary if transformer_2 is not None else None
+    shared.log.debug(f'Load model: type=WanAI model="{checkpoint_info.name}" repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args} stage={shared.opts.model_wan_stage} boundary={boundary_ratio}')
 
     cls = diffusers.WanPipeline
     pipe = cls.from_pretrained(
@@ -88,6 +98,7 @@ def load_wan(checkpoint_info, diffusers_load_config={}):
 
     del text_encoder
     del transformer
+    del transformer_2
 
     sd_hijack_te.init_hijack(pipe)
     from modules.video_models import video_vae