61 lines
2.3 KiB
Markdown
61 lines
2.3 KiB
Markdown
# Documentation
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- Class name: RescaleCFG
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- Category: advanced/model
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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RescaleCFG节点旨在通过对其参数应用缩放因子来修改模型的配置。这种调整旨在增强模型的性能或使其适应不同的操作条件，而不会改变其基本架构。
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# Input types
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## Required
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- model
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- 模型参数至关重要，因为它定义了将被重新缩放的基础模型。它是节点操作的主要输入，以实现所需的缩放效果。
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- Comfy dtype: MODEL
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- Python dtype: torch.nn.Module
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- multiplier
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- 乘数参数至关重要，因为它决定了要应用于模型配置的缩放程度。它直接影响重新缩放过程的最终结果。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- rescaled_model
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- 重新缩放后的模型输出代表了应用缩放过程后的模型。它是节点操作的结果，并标志着模型的新配置。
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- Comfy dtype: MODEL
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- Python dtype: torch.nn.Module
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# Usage tips
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- Infra type: CPU
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# Source code
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```
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class RescaleCFG:
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'model': ('MODEL',), 'multiplier': ('FLOAT', {'default': 0.7, 'min': 0.0, 'max': 1.0, 'step': 0.01})}}
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RETURN_TYPES = ('MODEL',)
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FUNCTION = 'patch'
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CATEGORY = 'advanced/model'
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def patch(self, model, multiplier):
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def rescale_cfg(args):
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cond = args['cond']
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uncond = args['uncond']
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cond_scale = args['cond_scale']
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sigma = args['sigma']
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sigma = sigma.view(sigma.shape[:1] + (1,) * (cond.ndim - 1))
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x_orig = args['input']
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x = x_orig / (sigma * sigma + 1.0)
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cond = (x - (x_orig - cond)) * (sigma ** 2 + 1.0) ** 0.5 / sigma
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uncond = (x - (x_orig - uncond)) * (sigma ** 2 + 1.0) ** 0.5 / sigma
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x_cfg = uncond + cond_scale * (cond - uncond)
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ro_pos = torch.std(cond, dim=(1, 2, 3), keepdim=True)
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ro_cfg = torch.std(x_cfg, dim=(1, 2, 3), keepdim=True)
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x_rescaled = x_cfg * (ro_pos / ro_cfg)
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x_final = multiplier * x_rescaled + (1.0 - multiplier) * x_cfg
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return x_orig - (x - x_final * sigma / (sigma * sigma + 1.0) ** 0.5)
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m = model.clone()
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m.set_model_sampler_cfg_function(rescale_cfg)
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return (m,)
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``` |