code: def test_distributions(self):
      # checking bag of words as inputs
      vec_1 = [(2, 1), (3, 4), (4, 1), (5, 1), (1, 1), (7, 2)]
      vec_2 = [(1, 1), (3, 8), (4, 1)]
      result = matutils.jaccard(vec_2, vec_1)
      expected = 1 - 0.3
      self.assertAlmostEqual(expected, result)
  
      # checking ndarray, csr_matrix as inputs
      vec_1 = np.array([[1, 3], [0, 4], [2, 3]])
      vec_2 = csr_matrix([[1, 4], [0, 2], [2, 2]])
      result = matutils.jaccard(vec_1, vec_2)
      expected = 1 - 0.388888888889
      self.assertAlmostEqual(expected, result)
  
      # checking ndarray, list as inputs
      vec_1 = np.array([6, 1, 2, 3])
      vec_2 = [4, 3, 2, 5]
      result = matutils.jaccard(vec_1, vec_2)
      expected = 1 - 0.333333333333
      self.assertAlmostEqual(expected, result)
  
imports: import logging
  import unittest
  from gensim import matutils
  from scipy.sparse import csr_matrix
  import numpy
  import math
  from gensim.corpora.mmcorpus import MmCorpus
  from gensim.models import ldamodel
  from gensim.test.utils import datapath, common_dictionary, common_corpus
label_desc: Use image node_id 2 for calling the TestJaccard obj's underlying member method code with example usage: obj.test_distributions() without return types