old_contents: import os
  from unittest.mock import patch
  
  from torchtext.datasets.qqp import QQP
  
  from ..common.case_utils import TempDirMixin, zip_equal, get_random_unicode
  from ..common.torchtext_test_case import TorchtextTestCase
  
  
  def _get_mock_dataset(root_dir):
      """
      root_dir: directory to the mocked dataset
      """
      base_dir = os.path.join(root_dir, "QQP")
      os.makedirs(base_dir, exist_ok=True)
  
      seed = 1
      file_name = "quora_duplicate_questions.tsv"
      txt_file = os.path.join(base_dir, file_name)
      mocked_data = []
      print(txt_file)
      with open(txt_file, "w", encoding="utf-8") as f:
          f.write("id\tqid1\tqid2\tquestion1\tquestion2\tis_duplicate\n")
          for i in range(5):
              label = seed % 2
              rand_string_1 = get_random_unicode(seed)
              rand_string_2 = get_random_unicode(seed + 1)
              dataset_line = (label, rand_string_1, rand_string_2)
              # append line to correct dataset split
              mocked_data.append(dataset_line)
              f.write(f"{i}\t{i}\t{i}\t{rand_string_1}\t{rand_string_2}\t{label}\n")
              seed += 1
  
      return mocked_data
  
  
  class TestQQP(TempDirMixin, TorchtextTestCase):
      root_dir = None
      samples = []
  
      @classmethod
      def setUpClass(cls):
          super().setUpClass()
          cls.root_dir = cls.get_base_temp_dir()
          print(cls.root_dir)
          cls.samples = _get_mock_dataset(cls.root_dir)
          cls.patcher = patch("torchdata.datapipes.iter.util.cacheholder._hash_check", return_value=True)
          cls.patcher.start()
  
      @classmethod
      def tearDownClass(cls):
          cls.patcher.stop()
          super().tearDownClass()
  
      def test_qqp(self):
          dataset = QQP(root=self.root_dir)
  
          samples = list(dataset)
          expected_samples = self.samples
          for sample, expected_sample in zip_equal(samples, expected_samples):
              self.assertEqual(sample, expected_sample)
  
new_contents: import os
  from unittest.mock import patch
  
  from torchtext.datasets.qqp import QQP
  
  from ..common.case_utils import TempDirMixin, zip_equal, get_random_unicode
  from ..common.torchtext_test_case import TorchtextTestCase
  
  
  def _get_mock_dataset(root_dir):
      """
      root_dir: directory to the mocked dataset
      """
      base_dir = os.path.join(root_dir, "QQP")
      os.makedirs(base_dir, exist_ok=True)
  
      seed = 1
      file_name = "quora_duplicate_questions.tsv"
      txt_file = os.path.join(base_dir, file_name)
      mocked_data = []
      with open(txt_file, "w", encoding="utf-8") as f:
          f.write("id\tqid1\tqid2\tquestion1\tquestion2\tis_duplicate\n")
          for i in range(5):
              label = seed % 2
              rand_string_1 = get_random_unicode(seed)
              rand_string_2 = get_random_unicode(seed + 1)
              dataset_line = (label, rand_string_1, rand_string_2)
              # append line to correct dataset split
              mocked_data.append(dataset_line)
              f.write(f"{i}\t{i}\t{i}\t{rand_string_1}\t{rand_string_2}\t{label}\n")
              seed += 1
  
      return mocked_data
  
  
  class TestQQP(TempDirMixin, TorchtextTestCase):
      root_dir = None
      samples = []
  
      @classmethod
      def setUpClass(cls):
          super().setUpClass()
          cls.root_dir = cls.get_base_temp_dir()
          cls.samples = _get_mock_dataset(cls.root_dir)
          cls.patcher = patch("torchdata.datapipes.iter.util.cacheholder._hash_check", return_value=True)
          cls.patcher.start()
  
      @classmethod
      def tearDownClass(cls):
          cls.patcher.stop()
          super().tearDownClass()
  
      def test_qqp(self):
          dataset = QQP(root=self.root_dir)
  
          samples = list(dataset)
          expected_samples = self.samples
          for sample, expected_sample in zip_equal(samples, expected_samples):
              self.assertEqual(sample, expected_sample)
  
subject: Delete prints in test_qqp.py (#1734)