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