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Add FluxKontextMultiReferenceLatentMethod node. (#9356)

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This node is only useful if someone trains the kontext model to properly
use multiple reference images via the index method.

The default is the offset method which feeds the multiple images like if
they were stitched together as one. This method works with the current
flux kontext model.
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comfyanonymous
2025-08-15 12:50:39 -07:00
committed by GitHub
parent 027c63f63a
commit c308a8840a
3 changed files with 39 additions and 8 deletions
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24
comfy/ldm/flux/model.py
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@@ -224,19 +224,27 @@ class Flux(nn.Module):
if ref_latents is not None:
h = 0
w = 0
index = 0
index_ref_method = kwargs.get("ref_latents_method", "offset") == "index"
for ref in ref_latents:
h_offset = 0
w_offset = 0
if ref.shape[-2] + h > ref.shape[-1] + w:
w_offset = w
if index_ref_method:
index += 1
h_offset = 0
w_offset = 0
else:
h_offset = h
index = 1
h_offset = 0
w_offset = 0
if ref.shape[-2] + h > ref.shape[-1] + w:
w_offset = w
else:
h_offset = h
h = max(h, ref.shape[-2] + h_offset)
w = max(w, ref.shape[-1] + w_offset)
kontext, kontext_ids = self.process_img(ref, index=1, h_offset=h_offset, w_offset=w_offset)
kontext, kontext_ids = self.process_img(ref, index=index, h_offset=h_offset, w_offset=w_offset)
img = torch.cat([img, kontext], dim=1)
img_ids = torch.cat([img_ids, kontext_ids], dim=1)
h = max(h, ref.shape[-2] + h_offset)
w = max(w, ref.shape[-1] + w_offset)
txt_ids = torch.zeros((bs, context.shape[1], 3), device=x.device, dtype=x.dtype)
out = self.forward_orig(img, img_ids, context, txt_ids, timestep, y, guidance, control, transformer_options, attn_mask=kwargs.get("attention_mask", None))