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Fix noise/latent tensor mismatch when latent is nested but noise is not

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When using LTXAV (audio+video) workflows, latent_image is a NestedTensor
but noise may be a regular tensor. Calling unbind() on non-nested noise
splits along dim=0 (channels), producing a shape mismatch at noise_scaling.

Check whether noise is nested before unbinding. If not, pad with zero-noise
for additional components (e.g. audio), which is semantically correct since
those components don't need denoising in the video sampler.
This commit is contained in:
Dustin 2026-04-07 06:07:26 -04:00
parent b615af1c65
commit 2beca418ad
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1 changed files with 10 additions and 2 deletions
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comfy/samplers.py
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@ -1006,8 +1006,16 @@ class CFGGuider:
return latent_image return latent_image
if latent_image.is_nested: if latent_image.is_nested:
latent_image, latent_shapes = comfy.utils.pack_latents(latent_image.unbind()) li_tensors = latent_image.unbind()
noise, _ = comfy.utils.pack_latents(noise.unbind()) if noise.is_nested:
n_tensors = noise.unbind()
else:
# Noise only covers video -- pad remaining components (audio) with zeros
n_tensors = [noise]
for i in range(1, len(li_tensors)):
n_tensors.append(torch.zeros_like(li_tensors[i]))
latent_image, latent_shapes = comfy.utils.pack_latents(li_tensors)
noise, _ = comfy.utils.pack_latents(n_tensors)
else: else:
latent_shapes = [latent_image.shape] latent_shapes = [latent_image.shape]