code: def test_backward_not_leaf_in(norm_vars, norm_means):
      layer = UtteranceMVN(norm_means=norm_means, norm_vars=norm_vars)
      x = torch.randn(2, 1000, requires_grad=True)
      x = x + 2
      y, _ = layer(x)
      y.sum().backward()
  
imports: import pytest
  import torch
  from espnet2.layers.utterance_mvn import UtteranceMVN
label_desc: Use image node_id 4 for calling a global function with example usage: test_backward_not_leaf_in(norm_vars, norm_means) without return types