[Euler Discrete] Fix sigma (#6078)

* [Euler Discrete] Fix sigma

* make style

src/diffusers/models/__init__.py

@@ -33,8 +33,8 @@ if is_torch_available():
     _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"]

src/diffusers/schedulers/scheduling_euler_discrete.py

@@ -290,8 +290,6 @@ class EulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
             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):