code: def test_mean_values(self):
      # rmat = np.random.random((4, 5))
      rmat = np.arange(20, dtype=float).reshape((4, 5))
      cmat = rmat + 1j * rmat
  
      import warnings
  
      with warnings.catch_warnings():
          warnings.simplefilter("error")
          for mat in [rmat, cmat]:
              for axis in [0, 1]:
                  tgt = mat.sum(axis=axis)
                  res = np.mean(mat, axis=axis) * mat.shape[axis]
                  assert_allclose(res, tgt)
  
              for axis in [None]:
                  tgt = mat.sum(axis=axis)
                  res = np.mean(mat, axis=axis) * mat.size
                  assert_allclose(res, tgt)
  
imports: from unittest import skipIf, SkipTest
  import numpy
  import pytest
  from pytest import raises
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TEST_WITH_TORCHDYNAMO, TestCase, xpassIfTorchDynamo
label_desc: Use image node_id 2 for calling the TestMean obj's underlying member method code with example usage: obj.test_mean_values() without return types