# Write dictionary import json with open('model4_js/vocab/word2idx.json', 'w') as fp: json.dump(word2idx, fp) with open('model4_js/vocab/idx2word.json', 'w') as fp: json.dump(idx2word, fp) with open('model4_js/vocab/idx2tag.json', 'w') as fp: json.dump(idx2tag, fp) from keras.preprocessing.sequence import pad_sequences # Convert each sentence from list of Token to list of word_index X = [[word2idx[w[0]] for w in s] for s in sentences] # Padding each sentence to have the same lenght X = pad_sequences(maxlen=dataProcessor.getMaxLength(), sequences=X, padding='post', value=word2idx['pad']) # Convert Tag/Label to tag_index y = [[tag2idx[w[1]] for w in s] for s in sentences] # Padding each sentence to have the same lenght y = pad_sequences(maxlen=dataProcessor.getMaxLength(), sequences=y, padding='post', value=tag2idx['pad']) from keras.utils import to_categorical # One-Hot encode