From 24fb1b42fe2150c1e21f430c10f10cd7b94f81a3 Mon Sep 17 00:00:00 2001
From: kijai <40791699+kijai@users.noreply.github.com>
Date: Mon, 3 Mar 2025 01:35:36 +0200
Subject: [PATCH] bug fixes

---
 nodes.py                  | 9 +++++----
 wanvideo/modules/model.py | 7 +++----
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/nodes.py b/nodes.py
index edaf8d9..6b721ee 100644
--- a/nodes.py
+++ b/nodes.py
@@ -1266,6 +1266,7 @@ class WanVideoSampler:
                         positive_prompt = text_embeds["prompt_embeds"][prompt_index]
 
                         img_emb = image_embeds.get("image_embeds", None)
+                        partial_img_emb = None
                         if img_emb is not None:
                             print("img_emb shape", img_emb.shape)
                             partial_img_emb = img_emb[:, c, :, :]
@@ -1275,7 +1276,7 @@ class WanVideoSampler:
                         # Model inference - returns [frames, channels, height, width]
                         noise_pred_cond = transformer(
                             partial_latent_model_input, 
-                            y=[partial_img_emb],
+                            y=partial_img_emb,
                             t=timestep, 
                             current_step=i,
                             is_uncond=False,
@@ -1285,7 +1286,7 @@ class WanVideoSampler:
                         if cfg[i] != 1.0:
                             noise_pred_uncond = transformer(
                                 partial_latent_model_input, 
-                                y=[partial_img_emb],
+                                y=partial_img_emb,
                                 t=timestep, 
                                 current_step=i,
                                 is_uncond=True,
@@ -1322,14 +1323,14 @@ class WanVideoSampler:
                         t=timestep, 
                         current_step=i,
                         is_uncond=False,
-                        y=[image_embeds.get("image_embeds", None)],
+                        y=image_embeds.get("image_embeds", None),
                         context = [text_embeds["prompt_embeds"][0]],
                         **args
                     )[0].to(intermediate_device)
                     if cfg[i] != 1.0:
                         noise_pred_uncond = transformer(
                             latent_model_input, 
-                            y=[image_embeds.get("image_embeds", None)],
+                            y=image_embeds.get("image_embeds", None),
                             t=timestep, 
                             current_step=i,
                             is_uncond=True,
diff --git a/wanvideo/modules/model.py b/wanvideo/modules/model.py
index dce2a0e..a5e7bf5 100644
--- a/wanvideo/modules/model.py
+++ b/wanvideo/modules/model.py
@@ -609,13 +609,12 @@ class WanModel(ModelMixin, ConfigMixin):
         """        
         if self.model_type == 'i2v':
             assert clip_fea is not None and y is not None
-        # params
-        #device = self.patch_embedding.weight.device
+        
         if freqs.device != device:
             freqs = freqs.to(device)
-        
+
         if y is not None:
-            x = [torch.cat([u, v], dim=0) for u, v in zip(x, y)]
+            x = torch.cat([x, y], dim=0)
 
         # embeddings
         x = [self.patch_embedding(u.unsqueeze(0)) for u in x]