code: def test_call(self):
      tokenizer = self.tokenizer_class.from_pretrained(
          "bert-base-uncased"
      )
  
      text_1 = tokenizer.encode(
          "question sequence", add_special_tokens=False
      )
      text_2 = tokenizer.encode(
          "title sequence", add_special_tokens=False
      )
      text_3 = tokenizer.encode(
          "text sequence", add_special_tokens=False
      )
      expected_input_ids = (
          [101] + text_1 + [102] + text_2 + [102] + text_3
      )
      encoded_input = tokenizer(
          questions=["question sequence"],
          titles=["title sequence"],
          texts=["text sequence"],
      )
      self.assertIn("input_ids", encoded_input)
      self.assertIn("attention_mask", encoded_input)
      self.assertListEqual(
          encoded_input["input_ids"][0], expected_input_ids
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/models/dpr/test_tokenization_dpr.py
imports: from transformers import DPRContextEncoderTokenizer, DPRContextEncoderTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast, DPRReaderOutput, DPRReaderTokenizer, DPRReaderTokenizerFast
  from transformers.testing_utils import require_tokenizers, slow
  from transformers.tokenization_utils_base import BatchEncoding
  from ..bert.test_tokenization_bert import BertTokenizationTest
label_desc: Use image node_id 2 for calling the DPRReaderTokenizationTest obj's underlying member method code with example usage: obj.test_call() without return types