code: def test_state_dict(self):
      data_list, data_with_config, defaults = self._get_data()
      sparsifier = self._get_sparsifier(
          data_list, data_with_config, defaults
      )
      schedule_param = self._get_schedule_param()
      scheduler1 = self._get_scheduler(sparsifier, schedule_param)
  
      sparsifier.step()
      scheduler1.step()
  
      scheduler2 = self._get_scheduler(sparsifier, schedule_param)
      all_data = data_list + data_with_config
      for some_data in all_data:
          name, _, _ = self._get_name_data_config(some_data, defaults)
          assert (
              scheduler1.base_param[name] != scheduler2.base_param[name]
          )
          assert (
              scheduler1._last_param[name]
              == scheduler2.base_param[name]
          )
  
      scheduler1_state = scheduler1.state_dict()
      scheduler2.load_state_dict(scheduler1_state)
  
      for some_data in all_data:
          name, _, _ = self._get_name_data_config(some_data, defaults)
          assert (
              scheduler1.base_param[name] == scheduler2.base_param[name]
          )
          assert (
              scheduler1._last_param[name]
              == scheduler2._last_param[name]
          )
  
imports: import logging
  import warnings
  from torch.testing._internal.common_utils import TestCase
  from torch import nn
  import torch
  from typing import Tuple
  import copy
  from torch.ao.pruning._experimental.data_sparsifier import DataNormSparsifier
  from torch.ao.pruning._experimental.data_scheduler import BaseDataScheduler
label_desc: Use image node_id 9 for calling the TestBaseDataScheduler obj's underlying member method code with example usage: obj.test_state_dict() without return types