code: def test_initialization_raises(distributions):
      d1, d2, d3, d4, d12, d22, d32, d13 = distributions
  
      assert_raises(ValueError, BayesianNetwork, [d1, d12], [(d12, d1)])
      assert_raises(ValueError, BayesianNetwork, None, [(d1, d12)])
      assert_raises(ValueError, BayesianNetwork, [d1], [(d1, d12)])
      assert_raises(ValueError, BayesianNetwork, [d12], [(d1, d12)])
      assert_raises(ValueError, BayesianNetwork, [d1, d12], [(d1, d1)])
      assert_raises(
          ValueError, BayesianNetwork, [d1, d12], [(d12, d12)]
      )
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.bayesian_network import BayesianNetwork
  from pomegranate.distributions import Exponential
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import ConditionalCategorical
  from nose.tools import assert_raises
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 7 for calling a global function with example usage: test_initialization_raises(distributions) without return types