1.7 KiB
1.7 KiB
Documentation
- Class name: Automatic CFG
- Category: model_patches/automatic_cfg/presets
- Output node: False
Automatic CFG节点通过基于'boost'标志调整参数来为模型应用动态配置,从而增强其性能。这种调整旨在优化模型的运行,可能会提高效率和输出质量。
Input types
Required
- model
- model参数代表将应用动态配置的模型。它对于定义进行调整和优化的基础至关重要。
- Comfy dtype: MODEL
- Python dtype: torch.nn.Module
- boost
- boost标志决定了配置调整的强度。启用boost会应用更激进的优化策略,可能会显著提升模型性能。
- Comfy dtype: BOOLEAN
- Python dtype: bool
Output types
- model
- 输出是输入模型的修改版本,通过动态配置调整进行了优化,以提高性能。
- Comfy dtype: MODEL
- Python dtype: torch.nn.Module
Usage tips
- Infra type:
CPU - Common nodes: unknown
Source code
class simpleDynamicCFG:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"model": ("MODEL",),
"boost" : ("BOOLEAN", {"default": True}),
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
CATEGORY = "model_patches/automatic_cfg/presets"
def patch(self, model, boost):
advcfg = advancedDynamicCFG()
m = advcfg.patch(model,
skip_uncond = boost,
uncond_sigma_start = 15, uncond_sigma_end = 1,
automatic_cfg = "hard" if boost else "soft"
)[0]
return (m, )