code: def X():
      return [
          [1, 2, 0, 0],
          [0, 0, 1, 0],
          [1, 1, 1, 0],
          [1, 2, 1, 1],
          [1, 1, 0, 1],
          [0, 1, 0, 1],
          [0, 1, 0, 0],
          [1, 0, 1, 1],
          [1, 1, 0, 1],
          [0, 2, 1, 0],
          [0, 0, 0, 1],
      ]
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.bayesian_network import BayesianNetwork
  from pomegranate.bayesian_network import _from_structure
  from pomegranate.bayesian_network import _learn_structure
  from pomegranate.bayesian_network import _categorical_exact
  from pomegranate.bayesian_network import _categorical_chow_liu
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import ConditionalCategorical
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 2 for calling a global function with example usage: X() and returns: list