# In this project we will to a neural translation with seq2seq architecture using attention mechanism

from __future__ import unicode_literals, print_function, division
from io import open
import unicodedata
import string
import re
import random

import torch
import torch.nn as nn
from torch import optim
import torch.nn.functional as F

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

SOS_token = 0
EOS_token = 1

class Lang:
	def __init__(self, name):
		self.name = name
		self.word2index = {}
		self.word2count = {}
		self.index2word = {0: "SOS", 1: "EOS"}
		self.n_words = 2 # count sos and eos


	def addSentence(se)


