text: import unittest
  import os
  import torch
  from trigger_attack.trigger_dataset import TriggerDataset
  from trigger_attack.trigger import Trigger
  from trigger_attack.trigger_models import TriggerModels
  from trojai_submission import data_tools
  
  import datasets
  from datasets.utils import set_progress_bar_enabled
  set_progress_bar_enabled(False)
  
  
  class TestTriggerDataset(unittest.TestCase):
      
      def setUp(self):
          current_script_dirname = os.path.dirname(os.path.abspath(__file__))
          model_filepath = os.path.join(current_script_dirname, 'data/round8_sample_dataset/models/id-00000000/model.pt')
          round_training_dataset_dirpath = os.path.join(current_script_dirname, 'data/round8_sample_dataset')
          tokenizer_filepath = os.path.join(current_script_dirname, 'data/round8_sample_dataset/tokenizers/tokenizer-roberta-base.pt')
          config = data_tools.load_config(model_filepath)
          clean_model_filepaths = data_tools.get_clean_model_filepaths(config, round_training_dataset_dirpath)
          device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
          
          models = TriggerModels(model_filepath, clean_model_filepaths, tokenizer_filepath, device=device)
          dataset = data_tools.load_examples(model_filepath, scratch_dirpath  ='.tmp')
  
          trigger_loc = 'both'
          trigger_source_labels = 'self'
          trigger_input_ids = torch.tensor([1]*10)
          trigger = Trigger(trigger_input_ids, trigger_loc, trigger_source_labels)
  
          task = 'qa'
          self.trigger_dataset = TriggerDataset(dataset, task, models, trigger)
  
      def test_init(self):
          '''
          '''
          return NotImplementedError
  
      def test_insert_new_trigger(self):
          return NotImplementedError
  
      def tearDown(self):
          return NotImplementedError
  
  
  if __name__ == '__main__':
      unittest.main(verbosity=3)