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"""
Credit: ComfyUI
https://github.com/comfyanonymous/ComfyUI/blob/v0.3.26/comfy_extras/nodes_mahiro.py
"""
import gradio as gr
import torch
import torch.nn.functional as F
from modules import scripts
from modules.infotext_utils import PasteField
from modules.shared import opts
class ScriptMahiro(scripts.ScriptBuiltinUI):
section = "cfg"
create_group = False
sorting_priority = 1
def title(self):
return "MaHiRo"
def show(self, is_img2img):
return scripts.AlwaysVisible if opts.show_mahiro else None
def ui(self, is_img2img):
enable = gr.Checkbox(
value=False,
label="MaHiRo",
elem_id=f"{'img2img' if is_img2img else 'txt2img'}_enable_mahiro",
scale=1,
)
self.infotext_fields = [PasteField(enable, "MaHiRo", api="mahiro")]
return [enable]
def after_extra_networks_activate(self, p, enable, *args, **kwargs):
if opts.show_mahiro and enable:
p.extra_generation_params.update({"MaHiRo": enable})
def process_before_every_sampling(self, p, enable, *args, **kwargs):
if not opts.show_mahiro or not enable:
return
@torch.inference_mode()
def mahiro_normd(args: dict):
scale: float = args["cond_scale"]
cond_p: torch.Tensor = args["cond_denoised"]
uncond_p: torch.Tensor = args["uncond_denoised"]
leap = cond_p * scale
u_leap = uncond_p * scale
cfg: torch.Tensor = args["denoised"]
merge = (leap + cfg) / 2
normu = torch.sqrt(u_leap.abs()) * u_leap.sign()
normm = torch.sqrt(merge.abs()) * merge.sign()
sim = F.cosine_similarity(normu, normm).mean()
simsc = 2 * (sim + 1)
wm = (simsc * cfg + (4 - simsc) * leap) / 4
return wm
unet = p.sd_model.forge_objects.unet.clone()
unet.set_model_sampler_post_cfg_function(mahiro_normd)
p.sd_model.forge_objects.unet = unet
print("using MaHiRo")
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