code: def _get_data(self):
      tensor1, param1, emb1 = (
          torch.randn(5, 5),
          nn.Parameter(torch.randn(10, 10)),
          nn.Embedding(50, 5),
      )
      data_list = [
          ("tensor1", tensor1),
          ("param1", param1),
          ("emb1", emb1),
      ]
      defaults = {
          "sparsity_level": 0.7,
          "sparse_block_shape": (1, 4),
          "zeros_per_block": 2,
      }
      data_with_config = [
          {
              "name": "tensor2",
              "data": torch.randn(4, 4),
              "config": {"sparsity_level": 0.3},
          }
      ]
      return data_list, data_with_config, defaults
  
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 1 for calling the TestBaseDataScheduler obj's underlying member method code with example usage: obj._get_data() and returns: data_list,  data_with_config,  defaults