code: def test_add_edge_raises():
      m1 = Categorical([[0.5, 0.5]])
      m2 = Categorical([[0.5, 0.5]])
      m3 = Categorical([[0.5, 0.5]])
  
      f1 = Categorical([[0.8, 0.1]])
      f2 = JointCategorical([[[0.2, 0.1], [0.1, 0.6]]])
  
      model = FactorGraph([f1, f2], [m1, m2])
      assert_raises(ValueError, model.add_edge, f2, f1)
      assert_raises(ValueError, model.add_edge, f2, m1)
      assert_raises(ValueError, model.add_edge, f1, m1)
      assert_raises(ValueError, model.add_edge, m1, m2)
      assert_raises(ValueError, model.add_edge, m3, f1)
      assert_raises(ValueError, model.add_edge, None, f1)
      assert_raises(ValueError, model.add_edge, m1, None)
      assert_raises(ValueError, model.add_edge, m1, m1)
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.factor_graph import FactorGraph
  from pomegranate.distributions import Exponential
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import JointCategorical
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 13 for calling a global function with example usage: test_add_edge_raises() without return types