code: def test_cat(dim):
      if is_torch_1_9_plus:
          wrappers = [ComplexTensor, torch.complex]
          modules = [FC, torch]
      else:
          wrappers = [ComplexTensor]
          modules = [FC]
  
      for complex_wrapper, complex_module in zip(wrappers, modules):
          mat1 = complex_wrapper(
              torch.rand(2, 3, 4), torch.rand(2, 3, 4)
          )
          mat2 = complex_wrapper(
              torch.rand(2, 3, 4), torch.rand(2, 3, 4)
          )
          ret = cat([mat1, mat2], dim=dim)
          ret2 = complex_module.cat([mat1, mat2], dim=dim)
          assert complex_module.allclose(ret, ret2)
  
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 1 for calling a global function with example usage: test_cat(dim) without return types