code: def full_loop(self, scheduler=None, **config):
      if scheduler is None:
          scheduler_class = self.scheduler_classes[0]
          scheduler_config = self.get_scheduler_config(**config)
          scheduler = scheduler_class(**scheduler_config)
  
      scheduler_class = self.scheduler_classes[0]
      scheduler_config = self.get_scheduler_config(**config)
      scheduler = scheduler_class(**scheduler_config)
  
      num_inference_steps = 10
      model = self.dummy_model()
      sample = self.dummy_sample_deter
      scheduler.set_timesteps(num_inference_steps)
  
      for i, t in enumerate(scheduler.timesteps):
          residual = model(sample, t)
          sample = scheduler.step(residual, t, sample).prev_sample
  
      return sample
  
imports: import tempfile
  import torch
  from diffusers import DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 4 for calling the UniPCMultistepSchedulerTest obj's underlying member method code with example usage: obj.full_loop(scheduler) and returns: sample