class_docstr: Computes the Mean Squared Error loss.
  MSEMetric for this loss will be reporting the mean square error between length ratios.
class_docstr_tok: ["Computes","the","Mean","Squared","Error","loss",".","MSEMetric","for","this","loss","will","be","reporting","the","mean","square","error","between","length","ratios","."]
code: def create_metric(self) -> "LossMetric":
      return LossMetric(name=C.LENRATIO_MSE)
  
imports: import logging
  import math
  from abc import ABC, abstractmethod
  from typing import Any, Dict, Optional, Tuple
  import torch
  import numpy
  from .None import constants
  from .None import utils
label_desc: Use image node_id 3 for calling the MSELoss obj's underlying member method code with example usage: obj.create_metric() and returns: LossMetric