nodes/kijai-ComfyUI-WanVideoWrapper
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fixup when context lens are none

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kabachuha
2025-06-12 15:30:30 +03:00
parent bdf7a3d02a
commit e8d3f1cca5
2 changed files with 7 additions and 6 deletions
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nodes.py
-3
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@@ -3064,11 +3064,8 @@ class WanVideoSampler:
negative_embeds = negative_embeds * len(positive_embeds)
if use_nag:
print("Nag triggered!")
nag_negative_prompt_embeds = negative_embeds
print(positive_embeds.shape)
positive_embeds = torch.cat([positive_embeds, nag_negative_prompt_embeds], dim=0)
print(positive_embeds.shape)
if not batched_cfg:
#cond
wanvideo/modules/model.py
+7 -3
View File
@@ -380,8 +380,12 @@ class WanT2VCrossAttention(WanSelfAttention):
batch_size = b
context_positive = context[:batch_size]
context_negative = context[batch_size:]
context_lens_positive = context_lens[:batch_size]
context_lens_negative = context_lens[batch_size:]
if context_lens is not None:
context_lens_positive = context_lens[:batch_size]
context_lens_negative = context_lens[batch_size:]
else:
context_lens_positive = None
context_lens_negative = None
k_positive = self.norm_k(self.k(context_positive)).view(batch_size, -1, n, d)
v_positive = self.v(context_positive).view(batch_size, -1, n, d)
@@ -408,7 +412,7 @@ class WanT2VCrossAttention(WanSelfAttention):
x_text = hidden_states_guidance * self.nag_alpha + hidden_states_positive * (1 - self.nag_alpha)
print("Nag applied in apply_guidance!")
#print("Nag applied in apply_guidance!")
else:
k = self.norm_k(self.k(context)).view(b, -1, n, d)
v = self.v(context).view(b, -1, n, d)