code: def test_mask_squash(self):
      model = SimpleLinear()
      sparsifier = NearlyDiagonalSparsifier(nearliness=1)
      sparsifier.prepare(model, config=None)
      sparsifier.step()
      sparsifier.squash_mask()
      for g in sparsifier.groups:
          module = g["module"]
          assert not is_parametrized(module, "weight")
          assert not hasattr(module, "mask")
          weights = module.weight
          height, width = weights.shape
          assert torch.all(
              weights == torch.eye(height, width) * weights
          )
  
imports: import itertools
  import logging
  import re
  import torch
  from torch import nn
  from torch.ao.pruning import BaseSparsifier, WeightNormSparsifier, FakeSparsity, NearlyDiagonalSparsifier
  from torch.nn.utils.parametrize import is_parametrized
  from torch.testing._internal.common_utils import TestCase
  from torch.testing._internal.common_pruning import SimpleLinear, MockSparseLinear, ImplementedSparsifier
label_desc: Use image node_id 4 for calling the TestNearlyDiagonalSparsifier obj's underlying member method code with example usage: obj.test_mask_squash() without return types