Simple Network RNN

import numpy as np
import scipy.io as scio
import torch 
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
class SimpleRnn(nn.Module):
        def __init__(self,input_size,hidden_size,output_size,num_layers=1):    
                super(SimpleRnn,self).__init__()
                self.hidden_size=hidden_size
                self.num_layers=num_layers
                self.embedding=nn.Embedding(input_size,hidden_size)
                self.rnn=nn.RNN(hidden_size,hidden_size,num_layers,batch_first=True)
                self.fc=nn.Linear(hidden_size,output_size)
                self.softmax=nn.LogSoftmax(dim=1)  
        def forward(self,input,hidden):
                x=self.embedding(input)
                out,hidden=self.rnn(x,hidden)
                output=output[:,-1,:]
                output=self.fc(output)
                output=self.softmax(output)
                return output,hidden 

        def initHidden(self):
                return Variable(torch.zeros(self.num_layers,1,self.hidden_size))