code: def test_fit_structure(X):
      model = BayesianNetwork(structure=((1, 2), (3,), (3,), ()))
      model.fit(X)
  
      assert_array_almost_equal(
          model.distributions[0].probs[0],
          [
              [[1.0000, 0.0000], [0.5000, 0.5000]],
              [[0.5000, 0.5000], [0.0000, 1.0000]],
              [[0.0000, 1.0000], [0.5000, 0.5000]],
          ],
      )
      assert_array_almost_equal(
          model.distributions[1].probs[0],
          [[0.2000, 0.4000, 0.4000], [0.3333, 0.5000, 0.1667]],
          4,
      )
      assert_array_almost_equal(
          model.distributions[2].probs[0],
          [[0.4000, 0.6000], [0.6667, 0.3333]],
          4,
      )
      assert_array_almost_equal(
          model.distributions[3].probs, [[0.4545, 0.5455]], 4
      )
  
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 27 for calling a global function with example usage: test_fit_structure(X) without return types