class_docstr: Computes the Poisson regression loss.
  MSEMetric for this loss will be reporting the mean
  square error between lengths, not length ratios!
class_docstr_tok: ["Computes","the","Poisson","regression","loss",".","MSEMetric","for","this","loss","will","be","reporting","the","mean","square","error","between","lengths",",","not","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 PoissonLoss obj's underlying member method code with example usage: obj.create_metric() and returns: LossMetric