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USO style reference. (#9677)

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Load the projector.safetensors file with the ModelPatchLoader node and use
the siglip_vision_patch14_384.safetensors "clip vision" model and the
USOStyleReferenceNode.
This commit is contained in:
comfyanonymous
2025-09-02 12:36:22 -07:00
committed by GitHub
parent e2d1e5dad9
commit 3412d53b1d
5 changed files with 222 additions and 8 deletions
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11
comfy/ldm/flux/model.py
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@@ -106,6 +106,7 @@ class Flux(nn.Module):
if y is None:
y = torch.zeros((img.shape[0], self.params.vec_in_dim), device=img.device, dtype=img.dtype)
patches = transformer_options.get("patches", {})
patches_replace = transformer_options.get("patches_replace", {})
if img.ndim != 3 or txt.ndim != 3:
raise ValueError("Input img and txt tensors must have 3 dimensions.")
@@ -117,9 +118,17 @@ class Flux(nn.Module):
if guidance is not None:
vec = vec + self.guidance_in(timestep_embedding(guidance, 256).to(img.dtype))
vec = vec + self.vector_in(y[:,:self.params.vec_in_dim])
vec = vec + self.vector_in(y[:, :self.params.vec_in_dim])
txt = self.txt_in(txt)
if "post_input" in patches:
for p in patches["post_input"]:
out = p({"img": img, "txt": txt, "img_ids": img_ids, "txt_ids": txt_ids})
img = out["img"]
txt = out["txt"]
img_ids = out["img_ids"]
txt_ids = out["txt_ids"]
if img_ids is not None:
ids = torch.cat((txt_ids, img_ids), dim=1)
pe = self.pe_embedder(ids)