code: def gmm():
      d = [Exponential([2.1, 0.3, 0.1]), Exponential([1.5, 3.1, 2.2])]
      return GeneralMixtureModel(d, priors=[0.7, 0.3])
  
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 3 for calling a global function with example usage: gmm() and returns: GeneralMixtureModel