code: def priors():
      return torch.tensor(
          numpy.array(
              [
                  [0.5, 0.5],
                  [0.5, 0.5],
                  [0.5, 0.5],
                  [0.0, 1.0],
                  [0.5, 0.5],
                  [0.3, 0.7],
                  [0.6, 0.4],
                  [0.5, 0.5],
                  [0.0, 1.0],
                  [1.0, 0.0],
                  [0.5, 0.5],
              ]
          )
      )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.gmm import GeneralMixtureModel
  from pomegranate.hmm import DenseHMM
  from pomegranate.distributions import Exponential
  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 2 for calling a global function with example usage: priors() and returns: torch