code: def _get_name_data_config(self, some_data, defaults):
      config = copy.deepcopy(defaults)
      if isinstance(some_data, Tuple):
          # dealing with data_list
          name, data = some_data
      else:
          # dealing with data_with_config
          name, data, new_config = (
              some_data["name"],
              some_data["data"],
              some_data["config"],
          )
          config.update(new_config)
      return name, data, config
  
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 5 for calling the TestBaseDataScheduler obj's underlying member method code with example usage: obj._get_name_data_config(some_data, defaults) and returns: name,  data,  config