context windows

nodes_sampler.py

@@ -1172,13 +1172,14 @@ class WanVideoSampler:
                 latent = add_noise(ttm_reference_latents, noise, timesteps[ttm_start_step].to(noise.device)).to(latent)
 
         # SteadyDancer
-        sdance_embeds = image_embeds.get("sdance_embeds", None)
-        sdancer_input = None
-        if sdance_embeds is not None:
-            print("Using SteadyDancer embeddings")
-            print(f"SteadyDancer embeds keys: {list(sdance_embeds.keys())}")
-            sdancer_input = sdance_embeds.copy()
-            sdancer_input = dict_to_device(sdancer_input, device, dtype)
+        sdancer_embeds = image_embeds.get("sdancer_embeds", None)
+        sdancer_data = sdancer_input = None
+        if sdancer_embeds is not None:
+            log.info("Using SteadyDancer embeddings:")
+            for k, v in sdancer_embeds.items():
+                log.info(f"  {k}: {v.shape if isinstance(v, torch.Tensor) else v}")
+            sdancer_data = sdancer_embeds.copy()
+            sdancer_data = dict_to_device(sdancer_data, device, dtype)
 
         #region model pred
         def predict_with_cfg(z, cfg_scale, positive_embeds, negative_embeds, timestep, idx, image_cond=None, clip_fea=None,
@@ -1357,6 +1358,13 @@ class WanVideoSampler:
                 else:
                     uni3c_data_input = uni3c_data
 
+                if context_window is not None and sdancer_data is not None and sdancer_data["cond_pos"].shape[1] != context_frames:
+                    sdancer_input = sdancer_data.copy()
+                    sdancer_input["cond_pos"] = sdancer_data["cond_pos"][:, context_window]
+                    sdancer_input["cond_neg"] = sdancer_data["cond_neg"][:, context_window] if sdancer_data.get("cond_neg", None) is not None else None
+                else:
+                    sdancer_input = sdancer_data
+
                 if s2v_pose is not None:
                     if not ((s2v_pose_start_percent <= current_step_percentage <= s2v_pose_end_percent) or \
                             (s2v_pose_end_percent > 0 and idx == 0 and current_step_percentage >= s2v_pose_start_percent)):

steadydancer/nodes.py

@@ -39,7 +39,7 @@ class WanVideoAddSteadyDancerEmbeds:
     CATEGORY = "WanVideoWrapper"
 
     def add(self, embeds, pose_latents_positive, pose_strength_spatial, pose_strength_temporal, start_percent=0.0, end_percent=1.0, pose_latents_negative=None, clip_vision_embeds=None):
-        sdance_embeds = {
+        sdancer_embeds = {
             "cond_pos": pose_latents_positive["samples"][0],
             "cond_neg": pose_latents_negative["samples"][0] if pose_latents_negative else None,
             "pose_strength_spatial": pose_strength_spatial,
@@ -50,7 +50,7 @@ class WanVideoAddSteadyDancerEmbeds:
         }
 
         updated = dict(embeds)
-        updated["sdance_embeds"] = sdance_embeds
+        updated["sdancer_embeds"] = sdancer_embeds
         return (updated,)