code: def w():
      return torch.tensor(
          [1.0, 0.3, 1.0, 0.0, 0.0, 2.1, 3.1, 1.0, 1.2, 1.1, 2.0]
      )
  
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 4 for calling a global function with example usage: w() and returns: torch