<gh_stars>0
# Load Packages
from __future__ import print_function
from keras.callbacks import LambdaCallback
from keras.models import Model, load_model, Sequential
from keras.layers import Dense, Activation, Dropout, Input, Masking
from keras.layers import LSTM
from keras.utils.data_utils import get_file
from keras.preprocessing.sequence import pad_sequences
import numpy as np
import random
import sys
import io


def on_epoch_end(epoch, logs):
    # Function invoked at end of each epoch. Prints generated text.
    None
    #start_index = random.randint(0, len(text) - Tx - 1)
    
    #generated = ''
    #sentence = text[start_index: start_index + Tx]
    #sentence = '0'*Tx
    #usr_input = input("Write the beginning of your poem, the Shakespearian machine will complete it.")
    # zero pad the sentence to Tx characters.
    #sentence = ('{0:0>' + str(Tx) + '}').format(usr_input).lower()
    #generated += sentence
#
    #sys.stdout.write(usr_input)

    #for i in range(400):
"""
        #x_pred = np.zeros((1, Tx, len(chars)))

        for t, char in enumerate(sentence):
            if char != '0':
                x_pred[0, t, char_indices[char]] = 1.

        preds = model.predict(x_pred, verbose=0)[0]
        next_index = sample(preds, temperature = 1.0)
        next_char = indices_char[next_index]

        generated += next_char
        sentence = sentence[1:] + next_char

        sys.stdout.write(next_char)
        sys.stdout.flush()
        
        if next_char == '\n':
            continue
        
    # Stop at the end of a line (4 lines)
    print()
 """   




