code: def save_password(real_password, noise_level=5):
      if noise_level < 1:
          raise ValueError(
              "`noise_level` must be equal or greater than one"
          )
  
      binary_password = str2bin(real_password)
      bin_password_len = len(binary_password)
  
      data = [binary_password]
  
      for _ in range(noise_level):
          # The farther from the 0.5 value the less likely
          # password recovery
          noise = np.random.binomial(1, 0.55, bin_password_len)
          data.append(noise)
  
      dhnet = algorithms.DiscreteHopfieldNetwork(mode="sync")
      dhnet.train(np.array(data))
  
      return dhnet
  
file_path: neupy/examples/memory/password_recovery.py
imports: from __future__ import division, print_function
  import random
  import pprint
  import string
  from collections import OrderedDict
  from operator import itemgetter
  import numpy
  from tqdm import tqdm
  from neupy import algorithms
label_desc: Use image node_id 5 for calling a global function with example usage: save_password(real_password, noise_level) and returns: dhnet