code: def _count_rnn_module(self, m, x, y, module_name):
      input_size = m.input_size
      hidden_size = m.hidden_size
      num_layers = m.num_layers
  
      _, num_steps = self._get_bsize_nsteps(m, x)
      total_ops = self._count_cell_flops(
          input_size, hidden_size, module_name
      )
  
      for _ in range(num_layers - 1):
          if m.bidirectional:
              cell_flops = (
                  self._count_cell_flops(
                      hidden_size * 2, hidden_size, module_name
                  )
                  * 2
              )
          else:
              cell_flops = self._count_cell_flops(
                  hidden_size, hidden_size, module_name
              )
          total_ops += cell_flops
  
      total_ops *= num_steps
      return total_ops
  
imports: import functools
  from collections import Counter
  from prettytable import PrettyTable
  import torch
  import torch.nn
  from torch.nn.utils.rnn import PackedSequence
  from nni.compression.base.wrapper import ModuleWrapper
label_desc: Use image node_id 16 for calling the ModelProfiler obj's underlying member method code with example usage: obj._count_rnn_module(m, x, y, module_name) and returns: total_ops