class_docstr: The Stat class represents a statistic that can be updated and retrieved
  at any point in time.
  
  The basic functionality this class provides is:
  1. A update/get method to actually compute the statistic
  2. A statistic store/cache to retrieve dependent information
     (e.g. other stat values that are required for computation)
  3. The name of the statistic that is used for the user to refer to
class_docstr_tok: ["The","Stat","class","represents","a","statistic","that","can","be","updated","and","retrieved","at","any","point","in","time",".","The","basic","functionality","this","class","provides","is",":","1",".","A","update\/get","method","to","actually","compute","the","statistic","2",".","A","statistic","store\/cache","to","retrieve","dependent","information","(","e.g",".","other","stat","values","that","are","required","for","computation",")","3",".","The","name","of","the","statistic","that","is","used","for","the","user","to","refer","to"]
code: def update(self, x: Tensor):
      raise NotImplementedError()
  
imports: from typing import Any, Callable, List, Optional, TYPE_CHECKING
  import torch
  from torch import Tensor
label_desc: Use image node_id 4 for calling the Stat obj's underlying member method code with example usage: obj.update(x) without return types