text: #!/usr/bin/env python3
  
  import numpy as np # numpy...
  # from sklearn.externals import joblib # for persistence (loading, storing the GMM model)
  # import argparse # command line parsing
  # import pandas as pd # for loading data from e.g. csv files
  # import h5py
  import time
  
  # Get histogram
  # -----------------------------------------------------------------
  def get_histogram(n_clusters):
      histogram = np.array(np.zeros(n_clusters))
      #return histogram.astype('float32')
      return histogram
  # -----------------------------------------------------------------
  
  
  N = 9000000
  all_k_hist = []
  row = 0
  
  print("Encoding...")
  t0 = time.time()
  while row < N:
      if row % 100000 == 0:
          print("row:", row, end='\r', flush=True)
  
      k_hist = get_histogram(2048)
      # print("type(k_hist)", type(k_hist))
      # print("k_hist.shape", k_hist.shape)
      # print("k_hist.dtype", k_hist.dtype)
      all_k_hist.append(k_hist)
  
      row += 1
  
  t1 = time.time()
  print("Elapsed time={:.2f} s".format(t1 - t0))
  
  
  