code: def test_fill_covars():
      full = np.arange(12).reshape(3, 2, 2) + 1
      np.testing.assert_equal(fill_covars(full, "full", 3, 2), full)
  
      diag = np.arange(6).reshape(3, 2) + 1
      expected = np.array(
          [[[1, 0], [0, 2]], [[3, 0], [0, 4]], [[5, 0], [0, 6]]]
      )
      np.testing.assert_equal(fill_covars(diag, "diag", 3, 2), expected)
  
      tied = np.arange(4).reshape(2, 2) + 1
      expected = np.array(
          [[[1, 2], [3, 4]], [[1, 2], [3, 4]], [[1, 2], [3, 4]]]
      )
      np.testing.assert_equal(fill_covars(tied, "tied", 3, 2), expected)
  
      spherical = np.array([1, 2, 3])
      expected = np.array(
          [[[1, 0], [0, 1]], [[2, 0], [0, 2]], [[3, 0], [0, 3]]]
      )
      np.testing.assert_equal(
          fill_covars(spherical, "spherical", 3, 2), expected
      )
  
imports: import numpy
  from numpy.testing import assert_allclose
  from hmmlearn.utils import normalize, fill_covars
label_desc: Use image node_id 3 for calling a global function with example usage: test_fill_covars() without return types