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Author SHA1 Message Date
Dustin
d8bdb5e41d
Merge 0388ac4309 into 6bcd8b96ab 2026-05-06 14:05:52 -04:00
guill
6bcd8b96ab
Revert "Fix Content-Disposition header missing 'attachment;' prefix (#13093)" (#13733)
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This reverts commit ea6880b04b.
2026-05-06 10:08:35 -07:00
Comfy Org PR Bot
9c34f5f36a
Bump comfyui-frontend-package to 1.43.17 (#13723)
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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Alexander Brown <DrJKL0424@gmail.com>
2026-05-05 22:22:48 -07:00
Dustin
0388ac4309
Defensively truncate/pad nested noise components to match latent
When noise.is_nested with a different number of components than
latent_image, truncate extras or pad missing components with
torch.zeros_like, mirroring the denoise_mask handling pattern below.

Addresses CodeRabbit nitpick on #13318.
2026-05-03 23:52:08 -04:00
Dustin
2beca418ad
Fix noise/latent tensor mismatch when latent is nested but noise is not
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.
2026-04-07 06:07:26 -04:00
3 changed files with 18 additions and 7 deletions

View File

@ -1006,8 +1006,19 @@ class CFGGuider:
return latent_image
if latent_image.is_nested:
latent_image, latent_shapes = comfy.utils.pack_latents(latent_image.unbind())
noise, _ = comfy.utils.pack_latents(noise.unbind())
li_tensors = latent_image.unbind()
if noise.is_nested:
# Truncate extra noise components, pad missing ones with zeros
n_tensors = list(noise.unbind()[:len(li_tensors)])
for i in range(len(n_tensors), len(li_tensors)):
n_tensors.append(torch.zeros_like(li_tensors[i]))
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:
latent_shapes = [latent_image.shape]

View File

@ -1,4 +1,4 @@
comfyui-frontend-package==1.42.15
comfyui-frontend-package==1.43.17
comfyui-workflow-templates==0.9.69
comfyui-embedded-docs==0.4.4
torch

View File

@ -560,7 +560,7 @@ class PromptServer():
buffer.seek(0)
return web.Response(body=buffer.read(), content_type=f'image/{image_format}',
headers={"Content-Disposition": f"attachment; filename=\"{filename}\""})
headers={"Content-Disposition": f"filename=\"{filename}\""})
if 'channel' not in request.rel_url.query:
channel = 'rgba'
@ -580,7 +580,7 @@ class PromptServer():
buffer.seek(0)
return web.Response(body=buffer.read(), content_type='image/png',
headers={"Content-Disposition": f"attachment; filename=\"{filename}\""})
headers={"Content-Disposition": f"filename=\"{filename}\""})
elif channel == 'a':
with Image.open(file) as img:
@ -597,7 +597,7 @@ class PromptServer():
alpha_buffer.seek(0)
return web.Response(body=alpha_buffer.read(), content_type='image/png',
headers={"Content-Disposition": f"attachment; filename=\"{filename}\""})
headers={"Content-Disposition": f"filename=\"{filename}\""})
else:
# Use the content type from asset resolution if available,
# otherwise guess from the filename.
@ -614,7 +614,7 @@ class PromptServer():
return web.FileResponse(
file,
headers={
"Content-Disposition": f"attachment; filename=\"{filename}\"",
"Content-Disposition": f"filename=\"{filename}\"",
"Content-Type": content_type
}
)