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Fix WanI2VCrossAttention so that it expects to receive transformer_options

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Jedrzej Kosinski 2025-08-29 02:31:16 -07:00
parent 2d13bf1c7a
commit 1ae6fe14a7
1 changed files with 3 additions and 3 deletions
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6
comfy/ldm/wan/model.py
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@ -117,7 +117,7 @@ class WanI2VCrossAttention(WanSelfAttention):
# self.alpha = nn.Parameter(torch.zeros((1, ))) # self.alpha = nn.Parameter(torch.zeros((1, )))
self.norm_k_img = operation_settings.get("operations").RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity() self.norm_k_img = operation_settings.get("operations").RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()
def forward(self, x, context, context_img_len): def forward(self, x, context, context_img_len, transformer_options={}):
r""" r"""
Args: Args:
x(Tensor): Shape [B, L1, C] x(Tensor): Shape [B, L1, C]
@ -132,9 +132,9 @@ class WanI2VCrossAttention(WanSelfAttention):
v = self.v(context) v = self.v(context)
k_img = self.norm_k_img(self.k_img(context_img)) k_img = self.norm_k_img(self.k_img(context_img))
v_img = self.v_img(context_img) v_img = self.v_img(context_img)
img_x = optimized_attention(q, k_img, v_img, heads=self.num_heads) img_x = optimized_attention(q, k_img, v_img, heads=self.num_heads, transformer_options=transformer_options)
# compute attention # compute attention
x = optimized_attention(q, k, v, heads=self.num_heads) x = optimized_attention(q, k, v, heads=self.num_heads, transformer_options=transformer_options)
# output # output
x = x + img_x x = x + img_x