code: def test_special_tokens_initialization(self):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(
              f"{tokenizer.__class__.__name__} ({pretrained_name})"
          ):
              added_tokens = [f"<extra_id_{i}>" for i in range(100)] + [
                  AddedToken("<special>", lstrip=True)
              ]
  
              tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                  pretrained_name,
                  additional_special_tokens=added_tokens,
                  **kwargs,
              )
              tokenizer_cr = self.rust_tokenizer_class.from_pretrained(
                  pretrained_name,
                  additional_special_tokens=added_tokens,
                  **kwargs,
                  from_slow=True,
              )
              tokenizer_p = self.tokenizer_class.from_pretrained(
                  pretrained_name,
                  additional_special_tokens=added_tokens,
                  **kwargs,
              )
  
              p_output = tokenizer_p.encode(
                  "Hey this is a <special> token"
              )
              r_output = tokenizer_r.encode(
                  "Hey this is a <special> token"
              )
              cr_output = tokenizer_cr.encode(
                  "Hey this is a <special> token"
              )
  
              special_token_id = tokenizer_r.encode(
                  "<special>", add_special_tokens=False
              )[0]
  
              self.assertEqual(p_output, r_output)
              self.assertEqual(cr_output, r_output)
              self.assertTrue(special_token_id in p_output)
              self.assertTrue(special_token_id in r_output)
              self.assertTrue(special_token_id in cr_output)
  
imports: import json
  import os
  import tempfile
  import unittest
  from transformers import SPIECE_UNDERLINE, AddedToken, BatchEncoding, SiglipTokenizer
  from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
  from transformers.utils import cached_property, is_tf_available, is_torch_available
  from ...test_tokenization_common import TokenizerTesterMixin
label_desc: Use image node_id 15 for calling the SiglipTokenizationTest obj's underlying member method code with example usage: obj.test_special_tokens_initialization() without return types