text: import utils
  from torch.utils.data import DataLoader
  from data_api.data_loader import get_cvae_collate
  from module_test.cvae_dataset_test import get_dataset
  
  
  def test_main():
      dataset_config = utils.load_config(DATASET_CONFIG_PATH)
      train_set, test_set, valid_set = get_dataset(CORPUS_CONFIG_PATH, DATASET_CONFIG_PATH)
      cvae_collate = get_cvae_collate(
          tokenized_sent_per_case=dataset_config['tokenized_sent_per_case'],
          max_tokenized_sent_size=dataset_config['max_tokenized_sent_size']
      )
  
      train_loader = DataLoader(train_set, batch_size=100, shuffle=True, collate_fn=cvae_collate)
  
      # Without collate function
      # train_loader = DataLoader(train_set, batch_size=100, shuffle=True)
  
  
  def get_data_loader(corpus_config_path, dataset_config_path):
      dataset_config = utils.load_config(dataset_config_path)
      cvae_collate = get_cvae_collate(
          tokenized_sent_per_case=dataset_config['tokenized_sent_per_case'],
          max_tokenized_sent_size=dataset_config['max_tokenized_sent_size']
      )
      train_set, test_set, valid_set = get_dataset(corpus_config_path, dataset_config_path)
      train_loader = DataLoader(train_set, batch_size=100, shuffle=True, collate_fn=cvae_collate)
      test_loader = DataLoader(test_set, batch_size=100, shuffle=False, collate_fn=cvae_collate)
      valid_loader = DataLoader(valid_set, batch_size=100, shuffle=False, collate_fn=cvae_collate)
      return train_loader, test_loader, valid_loader
  
  
  if __name__ == '__main__':
      CORPUS_CONFIG_PATH = '../config_for_test_modules/cvae_corpus_kor.json'
      DATASET_CONFIG_PATH = '../config_for_test_modules/cvae_dataset_kor.json'
      test_main()
  