class_docstr: Calculates the variance of a tensor, with an order. e.g.
  if `order = 1` then it will calculate sample variance.
  
  This is equal to mse / (n - order)
class_docstr_tok: ["Calculates","the","variance","of","a","tensor",",","with","an","order",".","e.g",".","if","`","order","=","1","`","then","it","will","calculate","sample","variance",".","This","is","equal","to","mse","\/","(","n","-","order",")"]
code: def get(self) -> Optional[Tensor]:
      mse = self.mse.get()
      n = self.n.get()
  
      if mse is None:
          return None
  
      if n <= self.order:
          return torch.zeros_like(mse)
  
      # NOTE: The following ensures mse is a float tensor.
      #   torch.true_divide is available in PyTorch 1.5 and later.
      #   This is for compatibility with 1.4.
      return mse.to(torch.float64) / (n - self.order)
  
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 Var obj's underlying member method code with example usage: obj.get() and returns: unknown, None, torch