diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 30cb5c4b..ebc0d896 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -11,7 +11,7 @@ from modules import prompt_parser, devices, processing, images
 
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
-from modules.script_callbacks import CGFDenoiserParams, cfg_denoiser_callback
+from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
 
 
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
@@ -279,7 +279,11 @@ class CFGDenoiser(torch.nn.Module):
         image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond])
         sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma])
 
-        cfg_denoiser_callback(CGFDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps))
+        denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps)
+        cfg_denoiser_callback(denoiser_params)
+        x_in = denoiser_params.x
+        image_cond_in = denoiser_params.image_cond
+        sigma_in = denoiser_params.sigma
 
         if tensor.shape[1] == uncond.shape[1]:
             cond_in = torch.cat([tensor, uncond])