def _preprocess_token_ids(self, token_ids, skip_special_tokens: bool = False):
        """
        Pre-process the token ids for decoding by removing the prompt tokens ids and timestamp token ids.

        Args:
            token_ids (`Union[int, List[int], np.ndarray, torch.Tensor, tf.Tensor]`):
                List of tokenized input ids. Typically, obtained using the `__call__` method of the tokenizer.
            skip_special_tokens (`bool`, *optional*, defaults to `False`):
                Whether or not to remove special tokens from the token ids. If `True`, the prompt token ids will be
                removed.
        """
        if skip_special_tokens:
            prompt_token_id = self.convert_tokens_to_ids("<|startofprev|>")
            decoder_start_token_id = self.convert_tokens_to_ids("<|startoftranscript|>")
            token_ids = self._strip_prompt(token_ids, prompt_token_id, decoder_start_token_id)

        return token_ids

        Pre-process the token ids for decoding by removing the prompt tokens ids and timestamp token ids.

        Args:
            token_ids (`Union[int, List[int], np.ndarray, torch.Tensor, tf.Tensor]`):
                List of tokenized input ids. Typically, obtained using the `__call__` method of the tokenizer.
            skip_special_tokens (`bool`, *optional*, defaults to `False`):
                Whether or not to remove special tokens from the token ids. If `True`, the prompt token ids will be
                removed.
        
dpkd/transformers/src/transformers/models/whisper/tokenization_whisper.py