In the pytorch Seq2Seq tutorial provided at pytorch website, in the decoder there is a extra relu step between Embedding and GRU but in the encoder there is no relu. Why is that? How this make any difference ? Can anyone Elaborate?

class DecoderRNN(nn.Module):
def init(self, hidden_size, output_size):
super(DecoderRNN, self).init()
self.hidden_size = hidden_size
    self.embedding = nn.Embedding(output_size, hidden_size)
    self.gru = nn.GRU(hidden_size, hidden_size)
    self.out = nn.Linear(hidden_size, output_size)
    self.softmax = nn.LogSoftmax(dim=1)
def forward(self, input, hidden):
    output = self.embedding(input).view(1, 1, -1)
    *output = F.relu(output)*
    output, hidden = self.gru(output, hidden)
    output = self.softmax(self.out(output[0]))
    return output, hidden

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



class EncoderRNN(nn.Module):
def init(self, input_size, hidden_size):
super(EncoderRNN, self).init()
self.hidden_size = hidden_size
    self.embedding = nn.Embedding(input_size, hidden_size)
    self.gru = nn.GRU(hidden_size, hidden_size)

def forward(self, input, hidden):
    embedded = self.embedding(input).view(1, 1, -1)
    output = embedded
    output, hidden = self.gru(output, hidden)
    return output, hidden

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