code: def gen_param_optim(self, tensors, lamb_option):
      ref_param = []
      tst_param = []
      for tensor in tensors:
          ref_param.append(torch.nn.Parameter(tensor.clone()))
          tst_param.append(torch.nn.Parameter(tensor.clone()))
  
      ref_optim = self.ref_optim(ref_param, **lamb_option)
      tst_optim = self.tst_optim(
          tst_param, use_nvlamb=True, **lamb_option
      )
  
      return (ref_param, tst_param, ref_optim, tst_optim)
  
imports: import unittest
  import os
  import torch
  from torch.optim import Optimizer
  import apex
  from apex.multi_tensor_apply import multi_tensor_applier
  from itertools import product
label_desc: Use image node_id 3 for calling the TestLamb obj's underlying member method code with example usage: obj.gen_param_optim(tensors, lamb_option) and returns: ref_param,  tst_param,  ref_optim,  tst_optim