code: def test_masking_logic(self):
      model = nn.Linear(16, 16, bias=False)
      model.weight = nn.Parameter(torch.eye(16))
      x = torch.randn(3, 16)
      self.assertEqual(torch.mm(x, torch.eye(16)), model(x))
  
      mask = torch.zeros(16, 16)
      sparsity = utils.FakeSparsity(mask)
      parametrize.register_parametrization(model, "weight", sparsity)
  
      x = torch.randn(3, 16)
      self.assertEqual(torch.zeros(3, 16), model(x))
  
file_path: pytorch/test/ao/sparsity/test_parametrization.py
imports: import logging
  from torch import nn
  from torch.ao.pruning.sparsifier import utils
  from torch.nn.utils import parametrize
  import torch
  from torch.testing._internal.common_utils import TestCase
label_desc: Use image node_id 1 for calling the TestFakeSparsity obj's underlying member method code with example usage: obj.test_masking_logic() without return types