Add Moebius latent shift looping

https://github.com/YisuiTT/Mobius/

nodes.py

@@ -1216,6 +1216,23 @@ class WanVideoFlowEdit:
     def process(self, **kwargs):
         return (kwargs,)
     
+class WanVideoLoopArgs:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                "shift_skip": ("INT", {"default": 6, "min": 0}),
+            },
+        }
+
+    RETURN_TYPES = ("LOOPARGS", )
+    RETURN_NAMES = ("loop_args",)
+    FUNCTION = "process"
+    CATEGORY = "WanVideoWrapper"
+    DESCRIPTION = "Looping through latent shift as shown in https://github.com/YisuiTT/Mobius/"
+
+    def process(self, **kwargs):
+        return (kwargs,)
+    
 class WanVideoSampler:
     @classmethod
     def INPUT_TYPES(s):
@@ -1247,6 +1264,7 @@ class WanVideoSampler:
                 "batched_cfg": ("BOOLEAN", {"default": False, "tooltip": "Batc cond and uncond for faster sampling, possibly faster on some hardware, uses more memory"}),
                 "slg_args": ("SLGARGS", ),
                 "rope_function": (["default", "comfy"], {"default": "default", "tooltip": "!EXPERIMENTAL! Comfy's RoPE implementation doesn't use complex numbers and can thus be compiled, that should be a lot faster when using torch.compile"}),
+                "loop_args": ("LOOPARGS", ),
             }
         }
 
@@ -1257,7 +1275,7 @@ class WanVideoSampler:
 
     def process(self, model, text_embeds, image_embeds, shift, steps, cfg, seed, scheduler, riflex_freq_index, 
         force_offload=True, samples=None, feta_args=None, denoise_strength=1.0, context_options=None, 
-        teacache_args=None, flowedit_args=None, batched_cfg=False, slg_args=None, rope_function="default"):
+        teacache_args=None, flowedit_args=None, batched_cfg=False, slg_args=None, rope_function="default", loop_args=None):
         #assert not (context_options and teacache_args), "Context options cannot currently be used together with teacache."
         patcher = model
         model = model.model
@@ -1650,7 +1668,13 @@ class WanVideoSampler:
             thresholds = thresholds.unsqueeze(1).unsqueeze(1).unsqueeze(1).unsqueeze(1).to(device)
             masks = mask.repeat(len(timesteps), 1, 1, 1, 1).to(device) 
             masks = masks > thresholds
-        
+
+        if loop_args is not None:
+            latent_shift_loop = True
+            is_looped = True
+            latent_skip = loop_args["shift_skip"]
+            shift_idx = 0
+        #main loop start
         for idx, t in enumerate(tqdm(timesteps)):    
             if flowedit_args is not None:
                 if idx < skip_steps:
@@ -1669,6 +1693,11 @@ class WanVideoSampler:
                     # end diff diff
 
             latent_model_input = latent.to(device)
+
+            ### latent shift
+            if latent_shift_loop:
+                latent_model_input = torch.cat([latent_model_input[:, shift_idx:]] + [latent_model_input[:, :shift_idx]], dim=1)
+
             timestep = torch.tensor([t]).to(device)
             current_step_percentage = idx / len(timesteps)
 
@@ -1878,6 +1907,12 @@ class WanVideoSampler:
                     text_embeds["negative_prompt_embeds"], 
                     timestep, idx, image_cond, clip_fea,
                     teacache_state=self.teacache_state)
+
+            if latent_shift_loop:
+                #reverse latent shift
+                noise_pred = torch.cat([noise_pred[:, latent_video_length - shift_idx:]] + [noise_pred[:, :latent_video_length - shift_idx]], dim=1)
+                shift_idx = (shift_idx + latent_skip) % latent_video_length
+                
             
             if flowedit_args is None:
                 latent = latent.to(intermediate_device)
@@ -2196,6 +2231,7 @@ NODE_CLASS_MAPPINGS = {
     "WanVideoControlEmbeds": WanVideoControlEmbeds,
     "WanVideoSLG": WanVideoSLG,
     "WanVideoTinyVAELoader": WanVideoTinyVAELoader,
+    "WanVideoLoopArgs": WanVideoLoopArgs
     }
 NODE_DISPLAY_NAME_MAPPINGS = {
     "WanVideoSampler": "WanVideo Sampler",
@@ -2223,4 +2259,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "WanVideoControlEmbeds": "WanVideo Control Embeds",
     "WanVideoSLG": "WanVideo SLG",
     "WanVideoTinyVAELoader": "WanVideo Tiny VAE Loader",
+    "WanVideoLoopArgs": "WanVideo Loop Args"
     }