code: def test_add_factor_raises():
      f1 = Categorical([[0.8, 0.1]])
      f2 = JointCategorical([[[0.2, 0.1], [0.1, 0.6]]])
  
      model = FactorGraph()
      assert_raises(ValueError, model.add_factor, [f1])
  
      model = FactorGraph()
      assert_raises(ValueError, model.add_factor, None)
  
      model = FactorGraph()
      assert_raises(ValueError, model.add_factor, Exponential())
  
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 9 for calling a global function with example usage: test_add_factor_raises() without return types