code: def test_nasty_clustering(self):
      d = 2
      rs = np.random.RandomState(123)
      x = np.zeros((100, d), dtype="float32")
      for i in range(5):
          x[i * 20 : i * 20 + 20] = rs.uniform(size=d)
  
      # we have 5 distinct points but ask for 10 centroids...
      km = faiss.Kmeans(d, 10, niter=10, verbose=True)
      km.train(x)
  
imports: from __future__ import absolute_import, division, print_function
  import numpy
  import faiss
  import unittest
  import array
  from common_faiss_tests import get_dataset_2
label_desc: Use image node_id 2 for calling the TestClustering obj's underlying member method code with example usage: obj.test_nasty_clustering() without return types