Hi
I am going through several tutorials about seq2seq in pytorch but most of them are with using attention. I want to create simple seq2seq model.
I just need to know how to pass context vector into decorder.
Working on english to French dataset.
Below is my code:

class Encorder(nn.Module):
def init(self,n_vocab,n_embed,hidden_size):
    super(Encorder,self).__init__()
    
    self.hidden_size = hidden_size
    self.embed = nn.Embedding(n_vocab+1,n_embed)
    self.RNN = nn.RNN(n_embed,hidden_size,batch_first = True)

def forward(self,x):
    x = self.embed(x)
    x,hidden = self.RNN(x)
    assert x[:,-1,:].shape == hidden.squeeze(0).shape
    return x[:,-1,:]

def initHidden(self):
    return torch.zeros(1, 1, self.hidden_size, device=device)


For Decorder

class decorder(nn.Module):
def init(self,n_vocab,n_embed,hidden_size,output_size):
super(decorder,self).init()
    self.hidden_size = hidden_size
    self.embed = nn.Embedding(n_vocab+1,n_embed)
    self.RNN = nn.RNN(n_embed,hidden_size,batch_first = True)
    self.fc1 = nn.Linear(hidden_size,output_size)
    
    
def forward(self,x,hidden):
    #x = x.unsqueeze(0)
    x = self.embed(x)
    x,hidden = self.RNN(x,hidden)
    x = self.fc1(x)
    
    return x
def initHidden(self):
    return torch.zeros(1, 1, self.hidden_size, device=device)


Please let me know if some one need more info. I just want to make basic seq2seq (without attention)
Thanks in advance.
Stay safe. !!