code: def count_module(self, m, x, y, name):
      # assume x is tuple of single tensor
      result = self.ops[type(m)](m, x, y)
      output_size = y[0].size() if isinstance(y, tuple) else y.size()
  
      total_result = {
          "name": name,
          "input_size": tuple(x[0].size()),
          "output_size": tuple(output_size),
          "module_type": type(m).__name__,
          **result,
      }
  
      self._push_result(total_result)
  
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 20 for calling the ModelProfiler obj's underlying member method code with example usage: obj.count_module(m, x, y, name) without return types