code: def get_populated_index():
      filename = "%s/%s_%s_populated.index" % (
          tmpdir,
          dbname,
          index_key,
      )
  
      if not os.path.exists(filename):
          index = get_trained_index()
          i0 = 0
          t0 = time.time()
          for xs in matrix_slice_iterator(xb, 100000):
              i1 = i0 + xs.shape[0]
              print(
                  "\radd %d:%d, %.3f s" % (i0, i1, time.time() - t0),
                  end=" ",
              )
              sys.stdout.flush()
              index.add(xs)
              i0 = i1
          print()
          print("Add done in %.3f s" % (time.time() - t0))
          print("storing", filename)
          faiss.write_index(index, filename)
      else:
          print("loading", filename)
          index = faiss.read_index(filename)
      return index
  
file_path: faiss/benchs/bench_polysemous_1bn.py
imports: import os
  import sys
  import time
  import numpy
  import re
  import faiss
  from multiprocessing.pool import ThreadPool
  from datasets import ivecs_read
label_desc: Use image node_id 7 for calling a global function with example usage: get_populated_index() and returns: index