diff --git a/extensions-builtin/forge_preprocessor_inpaint/scripts/preprocessor_inpaint.py b/extensions-builtin/forge_preprocessor_inpaint/scripts/preprocessor_inpaint.py
index d91b06a9..6bbc141f 100644
--- a/extensions-builtin/forge_preprocessor_inpaint/scripts/preprocessor_inpaint.py
+++ b/extensions-builtin/forge_preprocessor_inpaint/scripts/preprocessor_inpaint.py
@@ -56,7 +56,7 @@ class PreprocessorInpaintOnly(PreprocessorInpaint):
         unet = process.sd_model.forge_objects.unet.clone()
 
         def pre_cfg(model, c, uc, x, timestep, model_options):
-            noisy_latent = latent_image.to(x) + timestep.to(x) * torch.randn_like(latent_image).to(x)
+            noisy_latent = latent_image.to(x) + timestep[:, None, None, None].to(x) * torch.randn_like(latent_image).to(x)
             x = x * latent_mask.to(x) + noisy_latent.to(x) * (1.0 - latent_mask.to(x))
             return model, c, uc, x, timestep, model_options
 
diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py
index a1ae8c3b..b1dca624 100644
--- a/modules/sd_samplers_cfg_denoiser.py
+++ b/modules/sd_samplers_cfg_denoiser.py
@@ -173,7 +173,7 @@ class CFGDenoiser(torch.nn.Module):
         uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step)
 
         if self.mask is not None:
-            noisy_initial_latent = self.init_latent + sigma * torch.randn_like(self.init_latent).to(self.init_latent)
+            noisy_initial_latent = self.init_latent + sigma[:, None, None, None] * torch.randn_like(self.init_latent).to(self.init_latent)
             x = x * self.nmask + noisy_initial_latent * self.mask
 
         denoiser_params = CFGDenoiserParams(x, image_cond, sigma, state.sampling_step, state.sampling_steps, cond, uncond, self)