rewrite num_words to be different for two languages


my_keras.py -- some helpful functions to use keras



It predicts only start start start ...
either after random word2vec or after several hours of training
on real word2vec with two dictionaries.

write decorator to switch between random and real
types of learning


1. You should read this: https://arxiv.org/pdf/1609.08144.pdf
   about google seq2seq

2. https://www.kaggle.com/lystdo/lstm-with-word2vec-embeddings/code
   LSTM word2vec classification

3. https://github.com/keras-team/keras/blob/master/examples/lstm_seq2seq.py
   seq2seq char level

4. https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb
   a good tutorial from tf and keras (there are many tutorials there) and with explanation of
   some keras mistakes about sparse_cross_entropy

5. https://github.com/keras-team/keras/blob/master/examples/lstm_seq2seq.py -- lstm mashine
   translation (unfortunately, character level)