text: import torch.nn as nn
  import torch
  import random
  import math
  
  
  class RNN_PYTORCH(nn.Module):
      def __init__(self, input_size, hidden_size, output_size):
          super(RNN_PYTORCH, 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).to("cuda")
          hidden = self.i2h(combined)
          output = self.i2o(combined)
          output = self.softmax(output)
          return output, hidden
  
      def initHidden(self):
          return torch.zeros(1, self.hidden_size).to("cuda")
  