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 run_all_checks(
      self, data_list, defaults, data_with_config, norm_type="L1"
  ):
      assert norm_type in ["L1", "L2"]
      kwargs = {
          "sparsifier_type": DataNormSparsifier,
          "sparsifier_kwargs": {"norm": norm_type},
      }
      self.check_constructor(
          data_list, data_with_config, defaults, **kwargs
      )
      self.check_squash_mask(
          data_list, data_with_config, defaults, **kwargs
      )
      self.check_add_data(
          data_list, data_with_config, defaults, **kwargs
      )
      self.check_state_dict(
          data_list, data_with_config, defaults, **kwargs
      )
      self.check_step(
          data_list, data_with_config, defaults, norm_type=norm_type
      )
      self.check_step_2_of_4(norm_type=norm_type)
      self.check_sparsity_level(
          data_list, data_with_config, defaults, norm_type=norm_type
      )
      self.check_memory_reference(
          data_list, data_with_config, defaults, **kwargs
      )
  
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 1 for calling the _NormDataSparsifierTestCase obj's underlying member method code with example usage: obj.run_all_checks(data_list, defaults, data_with_config, norm_type) without return types