code: def gen_grad(self, ref_param, tst_param):
      for p_ref, p_tst in zip(ref_param, tst_param):
          p_ref.grad = torch.rand_like(p_ref)
          p_tst.grad = p_ref.grad
  
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 4 for calling the TestLamb obj's underlying member method code with example usage: obj.gen_grad(ref_param, tst_param) without return types