| """ |
| Credit: ComfyUI |
| https://github.com/comfyanonymous/ComfyUI/blob/v0.3.7/comfy_extras/nodes_model_advanced.py#L257 |
| """ |
|
|
| import gradio as gr |
| import torch |
|
|
| from modules import scripts |
| from modules.infotext_utils import PasteField |
| from modules.shared import opts |
|
|
|
|
| class ScriptRescaleCFG(scripts.ScriptBuiltinUI): |
| section = "cfg" |
| create_group = False |
|
|
| def title(self): |
| return "RescaleCFG" |
|
|
| def show(self, is_img2img): |
| return scripts.AlwaysVisible if opts.show_rescale_cfg else None |
|
|
| def ui(self, is_img2img): |
| cfg = gr.Slider( |
| value=0.0, |
| minimum=0.0, |
| maximum=1.0, |
| step=0.05, |
| label="Rescale CFG", |
| elem_id=f"{'img2img' if is_img2img else 'txt2img'}_rescale_cfg_scale", |
| scale=4, |
| ) |
|
|
| self.infotext_fields = [PasteField(cfg, "Rescale CFG", api="rescale_cfg")] |
|
|
| return [cfg] |
|
|
| def after_extra_networks_activate(self, p, cfg, *args, **kwargs): |
| if opts.show_rescale_cfg and cfg > 0.0: |
| p.extra_generation_params.update({"Rescale CFG": cfg}) |
|
|
| def process_before_every_sampling(self, p, cfg, *args, **kwargs): |
| if not opts.show_rescale_cfg or cfg < 0.05: |
| return |
| if p.is_hr_pass: |
| return |
|
|
| self.apply_rescale_cfg(p, cfg) |
|
|
| @staticmethod |
| def apply_rescale_cfg(p, cfg): |
|
|
| @torch.inference_mode() |
| def rescale_cfg(args): |
| cond = args["cond"] |
| uncond = args["uncond"] |
| cond_scale = args["cond_scale"] |
| sigma = args["sigma"] |
| sigma = sigma.view(sigma.shape[:1] + (1,) * (cond.ndim - 1)) |
| x_orig = args["input"] |
|
|
| x = x_orig / (sigma * sigma + 1.0) |
| cond = ((x - (x_orig - cond)) * (sigma**2 + 1.0) ** 0.5) / (sigma) |
| uncond = ((x - (x_orig - uncond)) * (sigma**2 + 1.0) ** 0.5) / (sigma) |
|
|
| x_cfg = uncond + cond_scale * (cond - uncond) |
| ro_pos = torch.std(cond, dim=(1, 2, 3), keepdim=True) |
| ro_cfg = torch.std(x_cfg, dim=(1, 2, 3), keepdim=True) |
|
|
| x_rescaled = x_cfg * (ro_pos / ro_cfg) |
| x_final = cfg * x_rescaled + (1.0 - cfg) * x_cfg |
|
|
| return x_orig - (x - x_final * sigma / (sigma * sigma + 1.0) ** 0.5) |
|
|
| unet = p.sd_model.forge_objects.unet.clone() |
| unet.set_model_sampler_cfg_function(rescale_cfg) |
| p.sd_model.forge_objects.unet = unet |
|
|
| print(f"rescale_cfg = {cfg}") |
|
|
