code: def test_special_tokens(self):
      src_text = ["A long paragraph for summarization."]
      tgt_text = [
          "Summary of the text.",
      ]
      for tokenizer in [
          self.default_tokenizer,
          self.default_tokenizer_fast,
      ]:
          inputs = tokenizer(
              src_text, text_target=tgt_text, return_tensors="pt"
          )
          input_ids = inputs["input_ids"]
          labels = inputs["labels"]
          self.assertTrue(
              (input_ids[:, 0] == tokenizer.bos_token_id).all().item()
          )
          self.assertTrue(
              (labels[:, 0] == tokenizer.bos_token_id).all().item()
          )
          self.assertTrue(
              (input_ids[:, -1] == tokenizer.eos_token_id).all().item()
          )
          self.assertTrue(
              (labels[:, -1] == tokenizer.eos_token_id).all().item()
          )
  
imports: import json
  import os
  import unittest
  from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
  from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_tokenizers, require_torch
  from transformers.utils import cached_property
  from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors
label_desc: Use image node_id 11 for calling the TestTokenizationMvp obj's underlying member method code with example usage: obj.test_special_tokens() without return types