code: def test_pow_of_3_inference_steps(self):
      # earlier version of set_timesteps() caused an error indexing alpha's with inference steps as power of 3
      num_inference_steps = 27
  
      for scheduler_class in self.scheduler_classes:
          sample = self.dummy_sample
          residual = 0.1 * sample
  
          scheduler_config = self.get_scheduler_config()
          scheduler = scheduler_class(**scheduler_config)
  
          scheduler.set_timesteps(num_inference_steps)
  
          # before power of 3 fix, would error on first step, so we only need to do two
          for i, t in enumerate(scheduler.prk_timesteps[:2]):
              sample = scheduler.step_prk(
                  residual, t, sample
              ).prev_sample
  
imports: import tempfile
  import torch
  from diffusers import PNDMScheduler
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 14 for calling the PNDMSchedulerTest obj's underlying member method code with example usage: obj.test_pow_of_3_inference_steps() without return types