nodes/Shakker-Labs-ComfyUI-IPAdapter-Flux
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Fix the start_percent > 0 error

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Badis
2024-11-25 10:13:12 +01:00
committed by GitHub
parent bc055780e6
commit 2819b48e98
1 changed files with 5 additions and 3 deletions
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flux/layers.py
+5 -3
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@@ -57,8 +57,9 @@ class DoubleStreamBlockIPA(nn.Module):
txt_attn, img_attn = attn[:, : txt.shape[1]], attn[:, txt.shape[1] :]
ip_hidden_states = self.ip_adapter(self.num_heads, img_q, self.image_emb, t).to(self.device)
ip_hidden_states = self.ip_adapter(self.num_heads, img_q, self.image_emb, t)
if ip_hidden_states is not None:
ip_hidden_states = ip_hidden_states.to(self.device)
img_attn = img_attn + ip_hidden_states
# calculate the img bloks
@@ -115,12 +116,13 @@ class SingleStreamBlockIPA(nn.Module):
# compute attention
attn = attention(q, k, v, pe=pe)
ip_hidden_states = self.ip_adapter(self.num_heads, q, self.image_emb, t).to(self.device)
ip_hidden_states = self.ip_adapter(self.num_heads, q, self.image_emb, t)
if ip_hidden_states is not None:
ip_hidden_states = ip_hidden_states.to(self.device)
attn = attn + ip_hidden_states
# compute activation in mlp stream, cat again and run second linear layer
output = self.linear2(torch.cat((attn, self.mlp_act(mlp)), 2))
x += mod.gate * output
if x.dtype == torch.float16:
x = torch.nan_to_num(x, nan=0.0, posinf=65504, neginf=-65504)
return x
return x