class_docstr: This class simply wraps over a given a set of SummarizerSingleTensor's in order
  to summarise multiple input tensors.
  
  Basic usage:
  
  >>>from captum.attr.aggregator import Summarizer
  >>>from captum.attr._utils.stats import Mean, StdDev
  >>>
  >>>attrib = torch.tensor([1, 2, 3, 4, 5])
  >>>
  >>>summ = Summarizer([Mean(), StdDev(0])
  >>>summ.update(attrib)
  >>>
  >>>print(summ.summary['mean'])
code: def _copy_stats(self):
      import copy
  
      return copy.deepcopy(self._stats)
  
file_path: captum/captum/attr/_utils/summarizer.py
imports: from typing import Dict, List, Optional, Tuple, Type, Union
  import torch
  from captum.attr._utils.stat import Count, Max, Mean, Min, MSE, Stat, StdDev, Sum, Var
  from captum.log import log_usage
  from torch import Tensor
label_desc: Use image node_id 2 for calling the Summarizer obj's underlying member method code with example usage: obj._copy_stats() and returns: copy