text: # coding: utf-8
  
  from __future__ import division
  
  import models
  import data
  
  import theano
  import sys
  import codecs
  
  import theano.tensor as T
  import numpy as np
  
  def to_array(arr, dtype=np.int32):
      # minibatch of 1 sequence as column
      return np.array([arr], dtype=dtype).T
  
  def convert_punctuation_to_readable(punct_token):
      if punct_token == data.SPACE:
          return " "
      else:
          return punct_token[0]
  
  def punctuate(predict, word_vocabulary, punctuation_vocabulary, reverse_punctuation_vocabulary, reverse_word_vocabulary, text, f_out, show_unk):
  
      if len(text) == 0:
          sys.exit("Input text from stdin missing.")
  
      text = [w for w in text.split() if w not in punctuation_vocabulary] + [data.END]
  
      i = 0
  
      while True:
  
          subsequence = text[i:i+data.MAX_SEQUENCE_LEN]
  
          if len(subsequence) == 0:
              break
  
          converted_subsequence = [word_vocabulary.get(w, word_vocabulary[data.UNK]) for w in subsequence]
          if show_unk:
              subsequence = [reverse_word_vocabulary[w] for w in converted_subsequence]
  
          y = predict(to_array(converted_subsequence))
  
          f_out.write(subsequence[0])
  
          last_eos_idx = 0
          punctuations = []
          for y_t in y:
  
              p_i = np.argmax(y_t.flatten())
              punctuation = reverse_punctuation_vocabulary[p_i]
  
              punctuations.append(punctuation)
  
              if punctuation in data.EOS_TOKENS:
                  last_eos_idx = len(punctuations) # we intentionally want the index of next element
  
          if subsequence[-1] == data.END:
              step = len(subsequence) - 1
          elif last_eos_idx != 0:
              step = last_eos_idx
          else:
              step = len(subsequence) - 1
  
          for j in range(step):
              f_out.write(" " + punctuations[j] + " " if punctuations[j] != data.SPACE else " ")
              if j < step - 1:
                  f_out.write(subsequence[1+j])
  
          if subsequence[-1] == data.END:
              break
  
          i += step
  
  
  if __name__ == "__main__":
  
      if len(sys.argv) > 1:
          model_file = sys.argv[1]
      else:
          sys.exit("Model file path argument missing")
  
      show_unk = False
      if len(sys.argv) > 2:
          show_unk = bool(int(sys.argv[2]))
  
      x = T.imatrix('x')
  
      print ("Loading model parameters...")
      net, _ = models.load(model_file, 1, x)
  
      print ("Building model...")
      predict = theano.function(inputs=[x], outputs=net.y)
      word_vocabulary = net.x_vocabulary
      punctuation_vocabulary = net.y_vocabulary
      reverse_word_vocabulary = {v:k for k,v in net.x_vocabulary.items()}
      reverse_punctuation_vocabulary = {v:k for k,v in net.y_vocabulary.items()}
  
      with codecs.getwriter('utf-8')(sys.stdout) as f_out:
          while True:
              text = raw_input("\nTEXT: ").decode('utf-8')
              punctuate(predict, word_vocabulary, punctuation_vocabulary, reverse_punctuation_vocabulary, reverse_word_vocabulary, text, f_out, show_unk)
  