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View Code? Open in Web Editor NEWPerturbed-Attention Guidance and Smoothed Energy Guidance for ComfyUI and SD Forge
License: MIT License
Perturbed-Attention Guidance and Smoothed Energy Guidance for ComfyUI and SD Forge
License: MIT License
Using this with Forge. Could you add an option to disable it during the Highres-fix?
It seems to look good when used without highres fix, but when used with highres fix it seems to lead to a lot of extra duplications.
I would like to request having the extension import its own settings after using the send to buttons in the PNG info tab.
This extension has implementation of Perturbed attention guidance
sd-webui-incantations
Hey there, thanks for the amazing work!
I updated ComfyUI today and installed the Advanced node from this repo. This broke my comfyui install by making my image generations deep fried, with and without the PAG (Advanced) node : https://imgur.com/a/JJanqFK
When I disable the extension/custom node, things go back to normal.
Just thought I'd mention it!
I've noticed that PAG does not work with TensorRT models. Is this feasible? The extra speed boost would be nice to use with PAG, and some models just don't have great output without it.
*** Error running post_sample: E:\stable-diffusion-webui-forge\extensions\sd-perturbed-attention\scripts\pag.py
Traceback (most recent call last):
File "E:\stable-diffusion-webui-forge\modules\scripts.py", line 867, in post_sample
script.post_sample(p, ps, *script_args)
File "E:\stable-diffusion-webui-forge\extensions\sd-perturbed-attention\scripts\pag.py", line 81, in post_sample
if p.enable_hr and hr_override:
AttributeError: 'StableDiffusionProcessingImg2Img' object has no attribute 'enable_hr'
---
hello, i just install the repo to check your node but on a workflow with 3 ipadapter and a controlnet, i'm running out of memory on a RTX3090. Just can use it on very basic workflow , is that normal?
The adaptive scale seems to behave in a non-intuitive way, I added a print(signal_scale)
after line 79 in pag_nodes.py to inspect the values and with 11 steps and 4 PAG scale this is what I get
Adaptive scale .1: 3.9, 3.9, 3.9, 3.8, 3.8, 3.8, 3.7, 3.7, 3.7, 3.6, 3.6
Adaptive scale .3: 3.9, 1.0, -1., -4., -7., -10, -13, -16, -19, -22, -25
Adaptive scale .5: 3.7, -19, -41, -64, -87, -10, -13, -15, -17, -20, -22
Both .3 and .5 disable PAG after the first step, where one (or at least I) would expect it to decay and zero out only after ~30% and ~50% of the steps respectively, or maybe decay by 10%, 30% and 50% every step, idk, but the way it currently works seems very unintuitive, am I missing something?
I have noticed that if I add your more advanced PAG node to my comfyui SVD workflow 5 times on blocks 0 - 5 on the unet output setting that it really seems to enhance the video. The issue I'm having is it gets very slow then. I was wanting to mess around with the sigma_start / sigma_end
setting but I don't really know what numbers you would suggest for a regular ksampler.
I also have been messing around with a separate ksampler with Nvidia align your steps, and wondering if that would also affect what I set sigma_start / sigma_end to.
And last question, I was wondering about rescale
setting and how high it goes, is 1 the highest and what you recommend there.
Basically just trying to get an idea for a good balanced tradeoff where you can still get good benefits without it slowing down too much. Thanks again for making this repo.
Sorry, this is not an issue, just a question: connect the PAG's model input to the CheckpointLoader or to the LORA's output? Thanks.
Setting the Adaptive Scale to > 0 does cause an error in Forge if the batch size is set to anything other than 1.
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