class_docstr: factor type parameter
      
class_docstr_tok: ["factor","type","parameter"]
code: def __eq__(self, other):
      if isinstance(other, self.__class__):
          return self.__dict__ == other.__dict__
      else:
          return False
  
imports: import math
  import random
  import logging
  import copy
  import torch
  from torch import optim
  from torch import nn
  import torch.nn.functional
  import numpy
  import nni
  from nni.tuner import Tuner
label_desc: Use image node_id 6 for calling the Factor obj's underlying member method code with example usage: obj.__eq__(other) and returns: unknown, False