diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py
index 816405dd..17eabf3d 100644
--- a/modules/sd_samplers_cfg_denoiser.py
+++ b/modules/sd_samplers_cfg_denoiser.py
@@ -65,7 +65,7 @@ class CFGDenoiser(torch.nn.Module):
     def inner_model(self):
         raise NotImplementedError()
 
-    def combine_denoised(self, x_out, conds_list, uncond, cond_scale):
+    def combine_denoised(self, x_out, conds_list, uncond, cond_scale, timestep, x):
         model_options = self.inner_model.inner_model.forge_objects.unet.model_options
 
         denoised_uncond = x_out[-uncond.shape[0]:]
@@ -75,6 +75,12 @@ class CFGDenoiser(torch.nn.Module):
             for cond_index, weight in conds:
                 denoised[i] += (x_out[cond_index] - denoised_uncond[i]) * (weight * cond_scale)
 
+        if "sampler_cfg_function" in model_options or "sampler_post_cfg_function" in model_options:
+            cond_scale = float(cond_scale)
+            model = self.inner_model.inner_model.forge_objects.unet
+
+            a = 0
+
         return denoised
 
     def combine_denoised_for_edit_model(self, x_out, cond_scale):
@@ -239,9 +245,9 @@ class CFGDenoiser(torch.nn.Module):
         if is_edit_model:
             denoised = self.combine_denoised_for_edit_model(x_out, cond_scale)
         elif skip_uncond:
-            denoised = self.combine_denoised(x_out, conds_list, uncond, 1.0)
+            denoised = self.combine_denoised(x_out, conds_list, uncond, 1.0, sigma_in, x_in)
         else:
-            denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale)
+            denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale, sigma_in, x_in)
 
         # Blend in the original latents (after)
         if not self.mask_before_denoising and self.mask is not None: