code: def distributions():
      d1 = Exponential([1.0])
      d2 = Gamma([1.1], [2.0])
      d3 = Categorical([[0.3, 0.7]])
      return d1, d2, d3
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Exponential
  from pomegranate.distributions import Gamma
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import IndependentComponents
  from ._utils import _test_initialization_raises_one_parameter
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._utils import _test_efd_from_summaries
  from ._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 6 for calling a global function with example usage: distributions() and returns: d1,  d2,  d3