code: def test_inverse():
      if is_torch_1_9_plus:
          wrappers = [ComplexTensor, torch.complex]
          modules = [FC, torch]
      else:
          wrappers = [ComplexTensor]
          modules = [FC]
  
      eye = torch.eye(3).expand(2, 3, 3)
      for complex_wrapper, complex_module in zip(wrappers, modules):
          mat = complex_wrapper(
              torch.from_numpy(mat_np.real),
              torch.from_numpy(mat_np.imag),
          )
          eye_complex = complex_wrapper(eye, torch.zeros_like(eye))
          assert complex_module.allclose(
              mat @ inverse(mat), eye_complex, atol=1e-6
          )
  
file_path: espnet/test/espnet2/enh/layers/test_complex_utils.py
imports: import numpy
  import pytest
  import torch
  import torch_complex.functional
  from packaging.version import parse
  from torch_complex.tensor import ComplexTensor
  from espnet2.enh.layers.complex_utils import cat, complex_norm, einsum, inverse, matmul, solve, stack, trace
label_desc: Use image node_id 4 for calling a global function with example usage: test_inverse() without return types