text: import torch
  import torch.nn as nn
  
  
  class RNN(nn.Module):
      def __init__(self, input_size: int, hidden_size: int, output_size: int):
          super(RNN, self).__init__()
          self.hidden_size = hidden_size
          self.i2h = nn.Linear(input_size + hidden_size, hidden_size)
          self.i2o = nn.Linear(input_size + hidden_size, output_size)
          self.softMax = nn.LogSoftmax(dim=1)
  
      def forward(self, _input, _hidden):
          combined = torch.cat((_input, _hidden), 1)
          hidden = self.i2h(combined)
          output = self.i2o(combined)
          output = self.softMax(output)
          return output, hidden
  
      def init_hidden(self):
          return torch.zeros(1, self.hidden_size)
  