class_docstr: This helper test class takes in any supported type of and runs some tests.
  This inherits the TestBaseDataSparsifierRuner wherein some functions are
  over-ridden to take accomodate the specific sparsifier.
  TODO: Change the structure by creating a separate test case class for each
        member function
class_docstr_tok: ["This","helper","test","class","takes","in","any","supported","type","of","and","runs","some","tests",".","This","inherits","the","TestBaseDataSparsifierRuner","wherein","some","functions","are","over-ridden","to","take","accomodate","the","specific","sparsifier",".","TODO",":","Change","the","structure","by","creating","a","separate","test","case","class","for","each","member","function"]
code: def check_step_2_of_4(self, norm_type):
      # overriding default config for test purposes
      default_config = {
          "sparsity_level": 1.0,
          "zeros_per_block": 2,
          "sparse_block_shape": (1, 4),
      }
      data_list = [("test_data", torch.randn(4, 4))]
  
      sparsifier = DataNormSparsifier(
          data_list=data_list, norm=norm_type, **default_config
      )
      sparsifier.step()
  
      for some_data in data_list:
          name, _ = some_data
          mask = sparsifier.get_mask(name=name)
          mask = mask.to(torch.float)
          self.assertAlmostEqual(
              1.0 - mask.mean().item(), 0.5, places=2
          )
          for row in mask:
              for idx in range(0, len(row), 4):
                  block = row[idx : idx + 4]
                  block, _ = block.sort()
                  assert (block[:2] == 0).all()
                  assert (block[2:] != 0).all()
  
imports: import logging
  import torch
  from torch.nn.utils.parametrize import is_parametrized
  from torch.testing._internal.common_utils import TestCase
  from typing import Tuple
  from torch import nn
  import itertools
  import math
  import copy
  from torch.ao.pruning._experimental.data_sparsifier import BaseDataSparsifier, DataNormSparsifier
  from torch.ao.pruning._experimental.data_sparsifier.quantization_utils import post_training_sparse_quantize
label_desc: Use image node_id 4 for calling the _NormDataSparsifierTestCase obj's underlying member method code with example usage: obj.check_step_2_of_4(norm_type) without return types