code: def forward(self, x, hidden):
      # get prev_t, cell_t from states
      hx, cx = hidden
      Wx = F.linear(x, self.weight_ih)
      Uz = F.linear(hx, self.weight_hh)
  
      # Section 2.1 in https://arxiv.org/pdf/1606.06630.pdf
      gates = (
          self.alpha * Wx * Uz
          + self.beta_i * Wx
          + self.beta_h * Uz
          + self.bias
      )
  
      # Same as LSTMCell after this point
      ingate, forgetgate, cellgate, outgate = gates.chunk(4, 1)
  
      ingate = F.sigmoid(ingate)
      forgetgate = F.sigmoid(forgetgate)
      cellgate = F.tanh(cellgate)
      outgate = F.sigmoid(outgate)
  
      cy = (forgetgate * cx) + (ingate * cellgate)
      hy = outgate * F.tanh(cy)
  
      return hy, cy
  
file_path: translate/pytorch_translate/rnn_cell.py
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the MILSTMCellBackend obj's underlying member method code with example usage: obj.forward(x, hidden) and returns: hy,  cy