code: def test_transformation(self):
      sent2 = "The quick brown fox jumps over the lazy dog. "
      data_sample = SASample({"x": sent2, "y": "negative"})
      import random
  
      random.seed(100)
      swap_ins = MLMSuggestion(device="cpu")
  
      x = swap_ins.transform(data_sample, n=5)
      self.assertEqual(5, len(x))
      tokens = []
      for _sample in x:
          self.assertTrue(
              _sample.get_words("x")[:2]
              == data_sample.get_words("x")[:2]
          )
          self.assertTrue(
              _sample.get_words("x")[3] == data_sample.get_words("x")[3]
          )
          self.assertTrue(
              _sample.get_words("x")[-5:]
              == data_sample.get_words("x")[-5:]
          )
          tokens.append(
              _sample.get_words("x")[2] + _sample.get_words("x")[4]
          )
  
      self.assertTrue(5 == len(set(tokens)))
  
      special_sample = SASample({"x": "", "y": "negative"})
      self.assertEqual([], swap_ins.transform(special_sample))
      special_sample = SASample(
          {"x": "~!@#$%^7890\"'", "y": "negative"}
      )
      special_sample = swap_ins.transform(special_sample)[0]
      self.assertEqual("epilogue \"'", special_sample.get_text("x"))
  
imports: import unittest
  from textflint.input.component.sample import SASample
  from textflint.generation.transformation.UT.mlm_suggestion import MLMSuggestion
label_desc: Use image node_id 1 for calling the TestMLM obj's underlying member method code with example usage: obj.test_transformation() without return types