code: def test_full_loop_no_noise(self):
      sample = self.full_loop()
  
      result_sum = torch.sum(torch.abs(sample))
      result_mean = torch.mean(torch.abs(sample))
  
      assert abs(result_sum.item() - 172.0067) < 1e-2
      assert abs(result_mean.item() - 0.223967) < 1e-3
  
imports: import torch
  from diffusers import DDIMParallelScheduler
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 17 for calling the DDIMParallelSchedulerTest obj's underlying member method code with example usage: obj.test_full_loop_no_noise() without return types