code: def test_inverse_backwar_leaf_in(stats_file, norm_vars, norm_means):
      layer = GlobalMVN(
          stats_file, norm_means=norm_means, norm_vars=norm_vars
      )
      x = torch.randn(2, 3, 80, requires_grad=True)
      y, _ = layer.inverse(x)
      y.sum().backward()
  
file_path: espnet/test/espnet2/layers/test_global_mvn.py
imports: from pathlib import Path
  import numpy
  import pytest
  import torch
  from espnet2.layers.global_mvn import GlobalMVN
label_desc: Use image node_id 6 for calling a global function with example usage: test_inverse_backwar_leaf_in(stats_file, norm_vars, norm_means) without return types