code: def _set_gradient(self, params, grad_values=None):
      if grad_values is None:
          grad_values = [0.1, 0.1]
      for i in range(len(params)):
          params[i].grad = torch.tensor([grad_values])
  
imports: from abc import ABC, abstractmethod
  from unittest.mock import MagicMock
  import torch
  import torch.nn
  from classy_vision.generic.util import split_batchnorm_params
  from classy_vision.models import ClassyModel
  from classy_vision.optim import build_optimizer, build_optimizer_schedulers
  from classy_vision.optim.param_scheduler import LinearParamScheduler
label_desc: Use image node_id 5 for calling the TestOptimizer obj's underlying member method code with example usage: obj._set_gradient(params, grad_values) without return types