""" 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")