diff --git a/src/diffusers/models/__init__.py b/src/diffusers/models/__init__.py
index 49ee3ee6af6b..e3794939e25e 100644
--- a/src/diffusers/models/__init__.py
+++ b/src/diffusers/models/__init__.py
@@ -33,8 +33,8 @@
     _import_structure["consistency_decoder_vae"] = ["ConsistencyDecoderVAE"]
     _import_structure["controlnet"] = ["ControlNetModel"]
     _import_structure["dual_transformer_2d"] = ["DualTransformer2DModel"]
-    _import_structure["modeling_utils"] = ["ModelMixin"]
     _import_structure["embeddings"] = ["ImageProjection"]
+    _import_structure["modeling_utils"] = ["ModelMixin"]
     _import_structure["prior_transformer"] = ["PriorTransformer"]
     _import_structure["t5_film_transformer"] = ["T5FilmDecoder"]
     _import_structure["transformer_2d"] = ["Transformer2DModel"]
diff --git a/src/diffusers/schedulers/scheduling_euler_discrete.py b/src/diffusers/schedulers/scheduling_euler_discrete.py
index cef2c4113a48..310907b3bc44 100644
--- a/src/diffusers/schedulers/scheduling_euler_discrete.py
+++ b/src/diffusers/schedulers/scheduling_euler_discrete.py
@@ -290,8 +290,6 @@ def set_timesteps(self, num_inference_steps: int, device: Union[str, torch.devic
             self.timesteps = torch.from_numpy(timesteps.astype(np.float32)).to(device=device)
 
         self.sigmas = torch.cat([sigmas, torch.zeros(1, device=sigmas.device)])
-        if sigmas.device.type == "cuda":
-            self.sigmas = self.sigmas.tolist()
         self._step_index = None
 
     def _sigma_to_t(self, sigma, log_sigmas):