# coding: utf-8

# In[3]:

import numpy as np

import theano as theano

import theano.tensor as T

import time

import operator

from utils import load_data, load_model_parameters_theano, generate_sentences

#from gru_theano import *

from lstm_theano import *

import sys

# In[4]:

# Load data (this may take a few minutes)

VOCABULARY_SIZE = 8000

X_train, y_train, word_to_index, index_to_word = load_data("data/lyrics.txt", VOCABULARY_SIZE)

# In[21]:

# Load parameters of pre-trained model

model = load_model_parameters_theano('./data/LSTM-2016-04-12-05-40-8000-48-128.dat.npz')

# In[2]:

# Build your own model (not recommended unless you have a lot of time!)

LEARNING_RATE = 1e-3

NEPOCH = 20

HIDDEN_DIM = 128

#model = LSTMTheano(VOCABULARY_SIZE, HIDDEN_DIM)

#t1 = time.time()

#model.sgd_step(X_train[0], y_train[0], LEARNING_RATE)

#t2 = time.time()

#print "SGD Step time: ~%f milliseconds" % ((t2 - t1) * 1000.)

#train_with_sgd(model, X_train, y_train, LEARNING_RATE, NEPOCH, decay=0.9)

# In[23]:

#generate_sentences(model, 10, index_to_word, word_to_index)

generate_sentences(model, index_to_word, word_to_index)

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