class_docstr: Data associated with a sequence.
  
  
  Args:
      prompt_token_ids: The token IDs of the prompt.
  
  Attributes:
      prompt_token_ids: The token IDs of the prompt.
      output_token_ids: The token IDs of the output.
      cumulative_logprob: The cumulative log probability of the output.
class_docstr_tok: ["Data","associated","with","a","sequence",".","Args",":","prompt_token_ids",":","The","token","IDs","of","the","prompt",".","Attributes",":","prompt_token_ids",":","The","token","IDs","of","the","prompt",".","output_token_ids",":","The","token","IDs","of","the","output",".","cumulative_logprob",":","The","cumulative","log","probability","of","the","output","."]
code: def append_token_id(self, token_id: int, logprob: float) -> None:
      self.output_token_ids.append(token_id)
      self.cumulative_logprob += logprob
      cur_timestamp = time.perf_counter()
      self.last_token_latency = cur_timestamp - self.updated_timestamp
      self.updated_timestamp = cur_timestamp
  
imports: import copy
  import enum
  import time
  from typing import Dict, List, Optional, Union
  from bigdl.llm.vllm.sampling_params import SamplingParams
  from bigdl.llm.utils.common import invalidInputError
label_desc: Use image node_id 2 for calling the SequenceData obj's underlying member method code with example usage: obj.append_token_id(token_id, logprob) without return types