docstr: The max length of the model input. MT-NLG does not predict the logprob of the first
  input token so `max_sequence_length` is one token shorter than `max_request_length`.
docstr_tok: ["The","max","length","of","the","model","input",".","MT-NLG","does","not","predict","the","logprob","of","the","first","input","token","so","`","max_sequence_length","`","is","one","token","shorter","than","`","max_request_length","`","."]
code: def max_sequence_length(self) -> int:
      """
      The max length of the model input. MT-NLG does not predict the logprob of the first
      input token so `max_sequence_length` is one token shorter than `max_request_length`.
      """
      return self.max_request_length - 1
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/window_services/mt_nlg_window_service.py
imports: from .gpt2_window_service import GPT2WindowService
  from .tokenizer_service import TokenizerService
label_desc: Use image node_id 2 for calling the MTNLGWindowService obj's underlying member method code with example usage: obj.max_sequence_length() and returns: unknown