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Fix batch handling, attempt to deal with non-4 dimensional latents - #6

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Fix batch handling, attempt to deal with non-4 dimensional latents#6
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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.

Should close#5

Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:

image

Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!

@bleppingblepping mentioned this pull request Jun 14, 2025
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Extraltodeus merged commit ece7be1 into Extraltodeus:mainJun 16, 2025
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Oh wow! Thank you!!

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Extraltodeus commented Jun 16, 2025•
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I'd be curious on how to implement and ancestral version BTW!

I only gave this a weak try and got more noise at the end 😅

@blepping

blepping commented Jun 17, 2025

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I'd be curious on how to implement and ancestral version BTW!

I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py

I created a pull that adds ancestral support over in #7.

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Well it's impressive! Thank you very much! :D

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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
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Fix batch handling, attempt to deal with non-4 dimensional latents - #6
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Fix batch handling, attempt to deal with non-4 dimensional latents#6
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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
mentioned this pull request
Jun 14, 2025

Closed

@Extraltodeus
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Oh wow! Thank you!!
@Extraltodeus
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I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
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Jun 17, 2025

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I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
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Well it's impressive! Thank you very much! :D
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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
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Fix batch handling, attempt to deal with non-4 dimensional latents - #6
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Fix batch handling, attempt to deal with non-4 dimensional latents#6
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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
mentioned this pull request
Jun 14, 2025

Closed

@Extraltodeus
Extraltodeus
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Oh wow! Thank you!!
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I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
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Jun 17, 2025

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I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
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Well it's impressive! Thank you very much! :D
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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
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Fix batch handling, attempt to deal with non-4 dimensional latents - #6
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Merged
Fix batch handling, attempt to deal with non-4 dimensional latents#6
Extraltodeus merged 1 commit into
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blepping:fix_batch_handling
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Jun 12, 2025

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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
mentioned this pull request
Jun 14, 2025

Closed

@Extraltodeus
Extraltodeus
merged commit ece7be1
into
Extraltodeus:mainJun 16, 2025
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Extraltodeus
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Oh wow! Thank you!!
@Extraltodeus
Extraltodeus
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Jun 16, 2025•

edited

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I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
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Jun 17, 2025

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ContributorAuthor
I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
@Extraltodeus
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Well it's impressive! Thank you very much! :D
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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
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Fix batch handling, attempt to deal with non-4 dimensional latents - #6
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blepping:fix_batch_handling
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Merged
Fix batch handling, attempt to deal with non-4 dimensional latents#6
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blepping:fix_batch_handling
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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
mentioned this pull request
Jun 14, 2025

Closed

@Extraltodeus
Extraltodeus
merged commit ece7be1
into
Extraltodeus:mainJun 16, 2025
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Oh wow! Thank you!!
@Extraltodeus
Extraltodeus
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edited

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I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
commented
Jun 17, 2025

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ContributorAuthor
I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
@Extraltodeus
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Well it's impressive! Thank you very much! :D
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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
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Fix batch handling, attempt to deal with non-4 dimensional latents - #6
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Fix batch handling, attempt to deal with non-4 dimensional latents#6
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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
mentioned this pull request
Jun 14, 2025

Closed

@Extraltodeus
Extraltodeus
merged commit ece7be1
into
Extraltodeus:mainJun 16, 2025
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Oh wow! Thank you!!
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I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
commented
Jun 17, 2025

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ContributorAuthor
I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
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Well it's impressive! Thank you very much! :D
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, 'i');
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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
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Fix batch handling, attempt to deal with non-4 dimensional latents - #6
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blepping:fix_batch_handling
Jun 16, 2025
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Fix batch handling, attempt to deal with non-4 dimensional latents#6
Extraltodeus merged 1 commit into
Extraltodeus:mainfrom 
blepping:fix_batch_handling
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Jun 12, 2025

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As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
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Jun 14, 2025

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merged commit ece7be1
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Extraltodeus:mainJun 16, 2025
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Jun 16, 2025

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Oh wow! Thank you!!
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Jun 16, 2025•

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I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
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Jun 17, 2025

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I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
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Jun 19, 2025

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Well it's impressive! Thank you very much! :D
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ValueError: too many values to unpack (expected 5)


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Fix batch handling, attempt to deal with non-4 dimensional latents by blepping · Pull Request #6 · Extraltodeus/DistanceSampler · GitHub
Skip to content
Fix batch handling, attempt to deal with non-4 dimensional latents - #6
Merged
Extraltodeus merged 1 commit into
Extraltodeus:mainfrom 
blepping:fix_batch_handling
Jun 16, 2025
Merged
Fix batch handling, attempt to deal with non-4 dimensional latents#6
Extraltodeus merged 1 commit into
Extraltodeus:mainfrom 
blepping:fix_batch_handling
Conversation
@blepping
@bleppingblepping
commented
Jun 12, 2025

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Contributor
As noted in #5, DistanceSampler currently fails on batches. This pull implements the simplest/dumbest solution: we just cram the batch (and any extra dimensions) into the channel dimension. I don't know if this is a correct solution, but it does seem to work and produce reasonable results. These changes also fix DistanceSampler for non-4 dimensional (3+) dimensions. For example, video models like Wan use 5 dimensional latents. Theoretically these changes would also work with 3 dimensional latents but I don't know of any 1D VAE models to test with at the moment. I did test with Wan and it works, even with batches of video latents.
Should close#5
Not sure if you're interested but I can also submit a pull that allows setting the various DistanceSampler options in the node rather than having to configure them by preset:
image
Would also be pretty easy to add ancestral sampling support. Let me know if you'd accept a pull adding that kind of stuff!
@bleppingblepping
mentioned this pull request
Jun 14, 2025

Closed

@Extraltodeus
Extraltodeus
merged commit ece7be1
into
Extraltodeus:mainJun 16, 2025
@Extraltodeus
Extraltodeus
commented
Jun 16, 2025

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Owner
Oh wow! Thank you!!
@Extraltodeus
Extraltodeus
commented
Jun 16, 2025•

edited

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Owner
I'd be curious on how to implement and ancestral version BTW!
I only gave this a weak try and got more noise at the end 😅
@blepping
blepping
commented
Jun 17, 2025

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ContributorAuthor
I'd be curious on how to implement and ancestral version BTW!
I've actually had a working version (though based on an older version of Distance) in my Overly Complicated Sampling node pack for a while now: https://github.com/blepping/comfyui_overly_complicated_sampling/blob/heun_experiments/py/step_samplers/extraltodeus.py
I created a pull that adds ancestral support over in #7.
@Extraltodeus
Extraltodeus
commented
Jun 19, 2025

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Owner
Well it's impressive! Thank you very much! :D
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Successfully merging this pull request may close these issues.

ValueError: too many values to unpack (expected 5)


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@blepping@Extraltodeus