Organized the code

huggingface · Dec 5, 2023 · 7f63b05 · 7f63b05
1 parent 0601382
commit 7f63b05
Showing 1 changed file with 1 addition and 5 deletions.
diff --git a/src/diffusers/schedulers/scheduling_euler_discrete.py b/src/diffusers/schedulers/scheduling_euler_discrete.py
@@ -280,11 +280,7 @@ def set_timesteps(self, num_inference_steps: int, device: Union[str, torch.devic
             sigmas = self._convert_to_karras(in_sigmas=sigmas, num_inference_steps=self.num_inference_steps)
             timesteps = np.array([self._sigma_to_t(sigma, log_sigmas) for sigma in sigmas])
 
-        # Checking 'sigmas' type before datatype conversion
-        if isinstance(sigmas, np.ndarray):
-            sigmas = torch.from_numpy(sigmas).to(dtype=torch.float32, device=device)
-        else:
-            sigmas = sigmas.to(dtype=torch.float32, device=device)
+        sigmas = torch.from_numpy(sigmas).to(dtype=torch.float32, device=device)
 
         # TODO: Support the full EDM scalings for all prediction types and timestep types
         if self.config.timestep_type == "continuous" and self.config.prediction_type == "v_prediction":