code: def test_mean(self):
      A = [[1, 2, 3], [4, 5, 6]]
      assert np.mean(A) == 3.5
      assert np.all(np.mean(A, 0) == np.array([2.5, 3.5, 4.5]))
      assert np.all(np.mean(A, 1) == np.array([2.0, 5.0]))
  
      # XXX: numpy emits a warning on empty slice
      assert np.isnan(np.mean([]))
  
      m = np.asarray(A)
      assert np.mean(A) == m.mean()
  
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 1 for calling the TestMean obj's underlying member method code with example usage: obj.test_mean() without return types