code: def test_add_distribution_raises(distributions):
      d1, d2, d3, d4, d12, d22, d32, d13 = distributions
  
      model = BayesianNetwork()
      assert_raises(ValueError, model.add_distribution, [d1])
      assert_raises(ValueError, model.add_distribution, None)
      assert_raises(ValueError, model.add_distribution, Exponential())
  
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 9 for calling a global function with example usage: test_add_distribution_raises(distributions) without return types