code: def test_correctness_validation(self) -> None:
      for grad_enabled in [False, True]:
          crypten.set_grad_enabled(grad_enabled)
  
          tensor = get_random_test_tensor(size=(2, 2), is_float=True)
          encrypted_tensor = crypten.cryptensor(tensor)
  
          # Test properties (non-tensor outputs)
          _ = encrypted_tensor.size()
  
          # Ensure correct validation works properly
          encrypted_tensor.add(1)
  
          # Ensure incorrect validation works properly for size
          encrypted_tensor.add = lambda y: crypten.cryptensor(0)
          with self.assertRaises(ValueError):
              encrypted_tensor.add(10)
  
          # Ensure incorrect validation works properly for value
          encrypted_tensor.add = lambda y: crypten.cryptensor(tensor)
          with self.assertRaises(ValueError):
              encrypted_tensor.add(10)
  
          # Test matmul in validation mode
          x = get_random_test_tensor(size=(3, 5), is_float=True)
          y = get_random_test_tensor(size=(1, 3), is_float=True)
  
          x = crypten.cryptensor(x)
          y = crypten.cryptensor(y)
          _ = y.matmul(x)
  
file_path: CrypTen/test/test_debug.py
imports: import crypten
  import torch
  from crypten.config import cfg
  from crypten.debug import configure_logging, pdb
  from test.multiprocess_test_case import get_random_test_tensor, MultiProcessTestCase
label_desc: Use image node_id 5 for calling the TestDebug obj's underlying member method code with example usage: obj.test_correctness_validation() without return types