From 650838fd6fcb24e66bf82b3c75383f35433d7b8a Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Thu, 17 Jul 2025 01:11:07 -0700
Subject: [PATCH] Experimental CFGNorm node. (#8942)

This is from the new hidream e1 1 model code. Figured it might be useful as a generic cfg trick.
---
 comfy_extras/nodes_cfg.py | 28 +++++++++++++++++++++++++++-
 1 file changed, 27 insertions(+), 1 deletion(-)

diff --git a/comfy_extras/nodes_cfg.py b/comfy_extras/nodes_cfg.py
index 1fb686644..1acaf15bc 100644
--- a/comfy_extras/nodes_cfg.py
+++ b/comfy_extras/nodes_cfg.py
@@ -40,6 +40,32 @@ class CFGZeroStar:
         m.set_model_sampler_post_cfg_function(cfg_zero_star)
         return (m, )
 
+class CFGNorm:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"model": ("MODEL",),
+                             "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
+                            }}
+    RETURN_TYPES = ("MODEL",)
+    RETURN_NAMES = ("patched_model",)
+    FUNCTION = "patch"
+    CATEGORY = "advanced/guidance"
+
+    def patch(self, model, strength):
+        m = model.clone()
+        def cfg_norm(args):
+            cond_p = args['cond_denoised']
+            pred_text_ = args["denoised"]
+
+            norm_full_cond = torch.norm(cond_p, dim=1, keepdim=True)
+            norm_pred_text = torch.norm(pred_text_, dim=1, keepdim=True)
+            scale = (norm_full_cond / (norm_pred_text + 1e-8)).clamp(min=0.0, max=1.0)
+            return pred_text_ * scale * strength
+
+        m.set_model_sampler_post_cfg_function(cfg_norm)
+        return (m, )
+
 NODE_CLASS_MAPPINGS = {
-    "CFGZeroStar": CFGZeroStar
+    "CFGZeroStar": CFGZeroStar,
+    "CFGNorm": CFGNorm,
 }