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https://github.com/comfyanonymous/ComfyUI.git
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5bea1d2ec9
* Add MaHiRo (improved CFG) long explanation of what it is is [here](https://huggingface.co/spaces/yoinked/blue-arxiv) (2024-1208.1) note: if the node name has encoding issues (utf 8/whatever), id suggest to replace the face at the end with `(>w<)` * add it to nodes.py, add description, and make it a post_cfg function * fix * revert the sampler_cfg_function thing * switch cfg to args["denoised"]
42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
import torch
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import torch.nn.functional as F
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class Mahiro:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"model": ("MODEL",),
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}}
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RETURN_TYPES = ("MODEL",)
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RETURN_NAMES = ("patched_model",)
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FUNCTION = "patch"
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CATEGORY = "_for_testing"
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DESCRIPTION = "Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt."
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def patch(self, model):
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m = model.clone()
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def mahiro_normd(args):
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scale: float = args['cond_scale']
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cond_p: torch.Tensor = args['cond_denoised']
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uncond_p: torch.Tensor = args['uncond_denoised']
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#naive leap
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leap = cond_p * scale
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#sim with uncond leap
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u_leap = uncond_p * scale
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cfg = args["denoised"]
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merge = (leap + cfg) / 2
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normu = torch.sqrt(u_leap.abs()) * u_leap.sign()
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normm = torch.sqrt(merge.abs()) * merge.sign()
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sim = F.cosine_similarity(normu, normm).mean()
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simsc = 2 * (sim+1)
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wm = (simsc*cfg + (4-simsc)*leap) / 4
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return wm
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m.set_model_sampler_post_cfg_function(mahiro_normd)
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return (m, )
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NODE_CLASS_MAPPINGS = {
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"Mahiro": Mahiro
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"Mahiro": "Mahiro is so cute that she deserves a better guidance function!! (。・ω・。)",
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}
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