code: def test_tokenization_for_chat(self):
      multilingual_tokenizer = WhisperTokenizer.from_pretrained(
          "openai/whisper-tiny"
      )
      # This is in English, but it's just here to make sure the chat control tokens are being added properly
      test_chats = [
          [
              {
                  "role": "system",
                  "content": "You are a helpful chatbot.",
              },
              {"role": "user", "content": "Hello!"},
          ],
          [
              {
                  "role": "system",
                  "content": "You are a helpful chatbot.",
              },
              {"role": "user", "content": "Hello!"},
              {"role": "assistant", "content": "Nice to meet you."},
          ],
          [
              {"role": "assistant", "content": "Nice to meet you."},
              {"role": "user", "content": "Hello!"},
          ],
      ]
      tokenized_chats = [
          multilingual_tokenizer.apply_chat_template(test_chat)
          for test_chat in test_chats
      ]
      expected_tokens = [
          [
              3223,
              366,
              257,
              4961,
              5081,
              18870,
              13,
              50257,
              15947,
              0,
              50257,
          ],
          [
              3223,
              366,
              257,
              4961,
              5081,
              18870,
              13,
              50257,
              15947,
              0,
              50257,
              37717,
              220,
              1353,
              1677,
              291,
              13,
              50257,
          ],
          [37717, 220, 1353, 1677, 291, 13, 50257, 15947, 0, 50257],
      ]
      for tokenized_chat, expected_tokens in zip(
          tokenized_chats, expected_tokens
      ):
          self.assertListEqual(tokenized_chat, expected_tokens)
  
imports: import unittest
  from transformers.models.whisper import WhisperTokenizer, WhisperTokenizerFast
  from transformers.models.whisper.tokenization_whisper import _combine_tokens_into_words, _find_longest_common_sequence
  from transformers.testing_utils import require_jinja, slow
  from ...test_tokenization_common import TokenizerTesterMixin
label_desc: Use image node_id 10 for calling the SpeechToTextTokenizerMultilinguialTest obj's underlying member method code with example usage: obj.test_tokenization_for_chat() without return types