Fix uni3c on fp16 and add strength parameters

nodes.py

@@ -2738,6 +2738,9 @@ class WanVideoSampler:
                 "render_latent": uni3c_embeds["render_latent"],
                 "render_mask": uni3c_embeds["render_mask"],
                 "camera_embedding": uni3c_embeds["camera_embedding"],
+                "controlnet_weight": uni3c_embeds["controlnet_weight"],
+                "start": uni3c_embeds["start"],
+                "end": uni3c_embeds["end"],
             }
 
         #feta

uni3c/nodes.py

@@ -137,12 +137,12 @@ class WanVideoUni3C_embeds:
         return {"required": {
             "controlnet": ("WANVIDEOCONTROLNET",),
             "render_latent": ("LATENT",),
-            # "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}),
-            # "vace_start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Start percent of the steps to apply VACE"}),
-            # "vace_end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "End percent of the steps to apply VACE"}),
+            "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}),
+            "start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Start percent of the steps to apply the controlnet"}),
+            "end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "End percent of the steps to apply the controlnet"}),
             },
             "optional": {
-                "render_mask": ("MASK",),
+                "render_mask": ("MASK", {"tooltip": "NOT IMPLEMENTED!"}),
             },
         }
 
@@ -151,7 +151,7 @@ class WanVideoUni3C_embeds:
     FUNCTION = "process"
     CATEGORY = "WanVideoWrapper"
 
-    def process(self, controlnet, render_latent, render_mask=None):
+    def process(self, controlnet, render_latent, strength, start_percent, end_percent, render_mask=None):
 
         device = mm.get_torch_device()
 
@@ -163,6 +163,7 @@ class WanVideoUni3C_embeds:
         width = latents.shape[4] * 8
         
         if render_mask is not None:
+            raise NotImplementedError("render_mask is not implemented at this time")
             mask = torch.nn.functional.interpolate(
                     render_mask.unsqueeze(0).unsqueeze(0),  # Add batch and channel dims [1,1,T,H,W]
                     size=(nframe, height, width),
@@ -218,6 +219,9 @@ class WanVideoUni3C_embeds:
 
         uni3c_embeds = {
             "controlnet": controlnet,
+            "controlnet_weight": strength,
+            "start": start_percent,
+            "end": end_percent,
             "render_latent": latents.to(device),
             "render_mask": latent_mask,
             "camera_embedding": None

wanvideo/modules/model.py

@@ -1423,17 +1423,21 @@ class WanModel(ModelMixin, ConfigMixin):
                 kwargs['vace_context_scale'] = vace_scale_list
 
             #uni3c controlnet
+            pdc_controlnet_states = None
             if pcd_data is not None:
-                self.controlnet.to(self.main_device)
-                pdc_controlnet_states = self.controlnet(
-                    render_latent=render_latent.to(self.main_device), 
-                    render_mask=pcd_data["render_mask"], 
-                    camera_embedding=pcd_data["camera_embedding"], 
-                    temb=e.to(self.main_device),
-                    device=self.offload_device)
-                self.controlnet.to(self.offload_device)
+                if (pcd_data["start"] <= current_step_percentage <= pcd_data["end"]) or \
+                            (pcd_data["end"] > 0 and current_step == 0 and current_step_percentage >= pcd_data["start"]):
+                    self.controlnet.to(self.main_device)
+                    pdc_controlnet_states = self.controlnet(
+                        render_latent=render_latent.to(self.main_device, self.controlnet.dtype), 
+                        render_mask=pcd_data["render_mask"], 
+                        camera_embedding=pcd_data["camera_embedding"], 
+                        temb=e.to(self.main_device),
+                        device=self.offload_device)
+                    self.controlnet.to(self.offload_device)
 
             for b, block in enumerate(self.blocks):
+                #skip layer guidance
                 if self.slg_blocks is not None:
                     if b in self.slg_blocks and is_uncond:
                         if self.slg_start_percent <= current_step_percentage <= self.slg_end_percent:
@@ -1443,9 +1447,9 @@ class WanModel(ModelMixin, ConfigMixin):
                 x = block(x, **kwargs)
 
                 #uni3c controlnet
-                if pcd_data is not None:
-                    if b < len(pdc_controlnet_states):
-                        x += pdc_controlnet_states[b].to(x.device)
+                if pdc_controlnet_states is not None and b < len(pdc_controlnet_states):
+                    x += pdc_controlnet_states[b].to(x) * pcd_data["controlnet_weight"]
+                #controlnet
                 if (controlnet is not None) and (b % controlnet["controlnet_stride"] == 0) and (b // controlnet["controlnet_stride"] < len(controlnet["controlnet_states"])):
                     x += controlnet["controlnet_states"][b // controlnet["controlnet_stride"]] * controlnet["controlnet_weight"]