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Experimental CFGNorm node. (#8942)
This is from the new hidream e1 1 model code. Figured it might be useful as a generic cfg trick.
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@ -40,6 +40,32 @@ class CFGZeroStar:
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m.set_model_sampler_post_cfg_function(cfg_zero_star)
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m.set_model_sampler_post_cfg_function(cfg_zero_star)
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return (m, )
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return (m, )
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class CFGNorm:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"model": ("MODEL",),
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"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
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}}
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RETURN_TYPES = ("MODEL",)
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RETURN_NAMES = ("patched_model",)
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FUNCTION = "patch"
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CATEGORY = "advanced/guidance"
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def patch(self, model, strength):
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m = model.clone()
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def cfg_norm(args):
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cond_p = args['cond_denoised']
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pred_text_ = args["denoised"]
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norm_full_cond = torch.norm(cond_p, dim=1, keepdim=True)
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norm_pred_text = torch.norm(pred_text_, dim=1, keepdim=True)
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scale = (norm_full_cond / (norm_pred_text + 1e-8)).clamp(min=0.0, max=1.0)
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return pred_text_ * scale * strength
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m.set_model_sampler_post_cfg_function(cfg_norm)
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return (m, )
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NODE_CLASS_MAPPINGS = {
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NODE_CLASS_MAPPINGS = {
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"CFGZeroStar": CFGZeroStar
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"CFGZeroStar": CFGZeroStar,
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"CFGNorm": CFGNorm,
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}
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}
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