Encoder Class for seq-2-seq modelling in PyTorch

encoder_pytorch.py

class Encoder(nn.Module):
  def __init__(self, input_size, hidden_size, bidirectional = True):
    super(Encoder, self).__init__()
    self.hidden_size = hidden_size
    self.input_size = input_size
    self.bidirectional = bidirectional
    
    self.lstm = nn.LSTM(input_size, hidden_size, bidirectional = bidirectional)
  
  def forward(self, inputs, hidden):
    
    output, hidden = self.lstm(inputs.view(1, 1, self.input_size), hidden)
    return output, hidden
    
  def init_hidden(self):
    return (torch.zeros(1 + int(self.bidirectional), 1, self.hidden_size),
      torch.zeros(1 + int(self.bidirectional), 1, self.hidden_size))