code: def __torch_dispatch__(self, func, types, args=(), kwargs=None):
      if kwargs is None:
          kwargs = {}
      rs = func(*args, **kwargs)
      logging.getLogger("LoggingTensor").info(
          f"{func.__module__}.{func.__name__}", args, kwargs, rs
      )
      return rs
  
imports: import torch
  from torch.utils._pytree import tree_map
  from typing import Iterator, List, Optional
  import logging
  import contextlib
  import itertools
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils.weak import WeakTensorKeyDictionary
  import functools
  from torch._C._profiler import gather_traceback, symbolize_tracebacks
label_desc: Use image node_id 1 for calling the LoggingTensorMode obj's underlying member method code with example usage: obj.__torch_dispatch__(func, types, args, kwargs) and returns: rs