code: def test_pickle(self) -> None:
      # Set up example KeyedOptimizer 1.
      param_1_t = torch.tensor([1.0, 2.0])
      param_1 = Variable(param_1_t)
      keyed_optimizer_1 = KeyedOptimizer(
          {"param_1": param_1},
          {param_1: {"one": 1.0}},
          [{"params": [param_1], "param_group_val_0": 2.0}],
      )
  
      # Set up example KeyedOptimizer 2.
      param_2_t = torch.tensor([-1.0, -2.0])
      param_2 = Variable(param_2_t)
      keyed_optimizer_2 = KeyedOptimizer(
          {"param_2": param_2},
          {param_2: {"two": -1.0}},
          [{"params": [param_2], "param_group_val_0": -2.0}],
      )
  
      combined_optimizer = CombinedOptimizer(
          [("ko1", keyed_optimizer_1), ("", keyed_optimizer_2)]
      )
  
      bytesIO = io.BytesIO()
      torch.save(combined_optimizer, bytesIO)
      bytesIO.seek(0)
      reload_combined_optimizer = torch.load(bytesIO)
  
      for k in reload_combined_optimizer.state_dict():
          self.assertEqual(
              combined_optimizer.state_dict()[k],
              reload_combined_optimizer.state_dict()[k],
          )
  
imports: import io
  import os
  import unittest
  from typing import Any, Dict, List
  import torch
  import torch.distributed
  from torch.autograd import Variable
  from torch.distributed._shard import sharded_tensor, sharding_spec
  from torchrec.optim.keyed import CombinedOptimizer, KeyedOptimizer, KeyedOptimizerWrapper, OptimizerWrapper
  from torchrec.test_utils import get_free_port
label_desc: Use image node_id 1 for calling the TestCombinedOptimizer obj's underlying member method code with example usage: obj.test_pickle() without return types