diff --git a/src/diffusers/schedulers/scheduling_ddim_inverse.py b/src/diffusers/schedulers/scheduling_ddim_inverse.py
index 4b90ff22c2..cc35046b1b 100644
--- a/src/diffusers/schedulers/scheduling_ddim_inverse.py
+++ b/src/diffusers/schedulers/scheduling_ddim_inverse.py
@@ -333,7 +333,9 @@ class DDIMInverseScheduler(SchedulerMixin, ConfigMixin):
         """
         # 1. get previous step value (=t+1)
         prev_timestep = timestep
-        timestep = min(timestep - self.config.num_train_timesteps // self.num_inference_steps, self.num_train_timesteps-1)
+        timestep = min(
+            timestep - self.config.num_train_timesteps // self.num_inference_steps, self.num_train_timesteps - 1
+        )
 
         # 2. compute alphas, betas
         # change original implementation to exactly match noise levels for analogous forward process
diff --git a/tests/schedulers/test_scheduler_ddim_inverse.py b/tests/schedulers/test_scheduler_ddim_inverse.py
index 72eff8b6a1..ab6596b98b 100644
--- a/tests/schedulers/test_scheduler_ddim_inverse.py
+++ b/tests/schedulers/test_scheduler_ddim_inverse.py
@@ -51,7 +51,7 @@ class DDIMInverseSchedulerTest(SchedulerCommonTest):
         scheduler_config = self.get_scheduler_config(steps_offset=1)
         scheduler = scheduler_class(**scheduler_config)
         scheduler.set_timesteps(5)
-        assert torch.equal(scheduler.timesteps, torch.LongTensor([  1, 201, 401, 601, 801]))
+        assert torch.equal(scheduler.timesteps, torch.LongTensor([1, 201, 401, 601, 801]))
 
     def test_betas(self):
         for beta_start, beta_end in zip([0.0001, 0.001, 0.01, 0.1], [0.002, 0.02, 0.2, 2]):