code: def test_from_summaries_null():
      d = Normal([1, 2], [1, 2], covariance_type="diag")
      assert_raises(ValueError, d.from_summaries)
      assert d.means[0] != 1 and d.means[1] != 2
      assert d.covs[0] != 1 and d.covs[1] != 2
      assert_array_almost_equal(d._w_sum, [0.0, 0.0])
      assert_array_almost_equal(d._xw_sum, [0.0, 0.0])
      assert_array_almost_equal(d._xxw_sum, [0.0, 0.0])
  
      d = Normal([1, 2], [1, 2], covariance_type="diag", inertia=0.5)
      assert_raises(ValueError, d.from_summaries)
      assert d.means[0] != 1 and d.means[1] != 2
      assert d.covs[0] != 1 and d.covs[1] != 2
      assert_array_almost_equal(d._w_sum, [0.0, 0.0])
      assert_array_almost_equal(d._xw_sum, [0.0, 0.0])
      assert_array_almost_equal(d._xxw_sum, [0.0, 0.0])
  
      d = Normal(
          [1, 2],
          [1, 2],
          covariance_type="diag",
          inertia=0.5,
          frozen=True,
      )
      d.from_summaries()
      _test_fit_params(d, [1, 2], [1, 2])
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Normal
  from ._utils import _test_initialization_raises_two_parameters
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._utils import _test_efd_from_summaries
  from ._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 28 for calling a global function with example usage: test_from_summaries_null() without return types