code: def gru_cell(input, hidden, w_ih, w_hh, b_ih, b_hh):
      gi = torch.mm(input, w_ih.t()) + b_ih
      gh = torch.mm(hidden, w_hh.t()) + b_hh
      i_r, i_i, i_n = gi.chunk(3, 1)
      h_r, h_i, h_n = gh.chunk(3, 1)
  
      resetgate = torch.sigmoid(i_r + h_r)
      inputgate = torch.sigmoid(i_i + h_i)
      newgate = torch.tanh(i_n + resetgate * h_n)
      hy = newgate + inputgate * (hidden - newgate)
  
      return hy
  
file_path: pytorch/benchmarks/fastrnns/cells.py
imports: from typing import Tuple
  import torch
  from torch import Tensor
label_desc: Use image node_id 6 for calling a global function with example usage: gru_cell(input, hidden, w_ih, w_hh, b_ih, b_hh) and returns: hy