code: def test_full_loop_with_no_set_alpha_to_one(self):
      # We specify different beta, so that the first alpha is 0.99
      sample = self.full_loop(set_alpha_to_one=False, beta_start=0.01)
      result_sum = torch.sum(torch.abs(sample))
      result_mean = torch.mean(torch.abs(sample))
  
      assert abs(result_sum.item() - 149.0784) < 1e-2
      assert abs(result_mean.item() - 0.1941) < 1e-3
  
imports: import torch
  from diffusers import DDIMParallelScheduler
  from .test_schedulers import SchedulerCommonTest
label_desc: Use image node_id 20 for calling the DDIMParallelSchedulerTest obj's underlying member method code with example usage: obj.test_full_loop_with_no_set_alpha_to_one() without return types