code: def __torch_dispatch__(self, func, types, args=(), kwargs=None):
      kwargs = kwargs if kwargs else {}
  
      out = func(*args, **kwargs)
      func_packet = func._overloadpacket
      if func_packet in flop_mapping:
          flop_count = flop_mapping[func_packet](
              args, normalize_tuple(out)
          )
          for par in self.parents:
              self.flop_counts[par][func_packet] += flop_count
      else:
          unmapped_ops.add(func_packet)
  
      return out
  
imports: import os
  from collections import defaultdict
  from numbers import Number
  from typing import Any, List
  import torch
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils._pytree import tree_map
  from torchvision.models._api import Weights
label_desc: Use image node_id 8 for calling the FlopCounterMode obj's underlying member method code with example usage: obj.__torch_dispatch__(func, types, args, kwargs) and returns: out