diff --git a/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py b/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
index 4a0ce91e96c1..f277e5a1eb95 100644
--- a/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
+++ b/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
@@ -227,7 +227,7 @@ def decode_latents(self, latents):
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 
-    def check_inputs(self, prompt, image, noise_level, callback_steps):
+    def check_inputs(self, prompt, image, callback_steps):
         if not isinstance(prompt, str) and not isinstance(prompt, list):
             raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
 
@@ -285,7 +285,6 @@ def __call__(
         image: Union[torch.FloatTensor, PIL.Image.Image, List[PIL.Image.Image]],
         num_inference_steps: int = 75,
         guidance_scale: float = 9.0,
-        noise_level: int = 0,
         negative_prompt: Optional[Union[str, List[str]]] = None,
         generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
         latents: Optional[torch.FloatTensor] = None,
@@ -386,7 +385,7 @@ def __call__(
         """
 
         # 1. Check inputs
-        self.check_inputs(prompt, image, noise_level, callback_steps)
+        self.check_inputs(prompt, image, callback_steps)
 
         # 2. Define call parameters
         batch_size = 1 if isinstance(prompt, str) else len(prompt)