code: def _get_result(self, m, flops):
      # assume weight is called `weight`, otherwise it's not applicable
      # if user customize the operation, the callback function should
      # return the dict result, inluding calculated flops, params and weight_shape.
  
      result = {
          "flops": flops,
          "params": _get_params(m),
          "weight_shape": tuple(m.weight.size())
          if hasattr(m, "weight")
          else 0,
      }
      return 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 3 for calling the ModelProfiler obj's underlying member method code with example usage: obj._get_result(m, flops) and returns: result