code: def handle(self,
                 t_input: inference.TranslatorInput,
                 t_output: inference.TranslatorOutput,
                 t_walltime: float = 0.):
          
          assert len(t_output.beam_histories) >= 1, "Translator output should contain beam histories."
          # If the sentence was max_len split, we may have more than one history
          for h in t_output.beam_histories:
              # Add the number of steps in each beam
              h["number_steps"] = len(h["predicted_tokens"])  # type: ignore
              # Some outputs can have more than one beam, add the id for bookkeeping
              h["id"] = t_output.sentence_id  # type: ignore
              self.stream.write("%s\n" % json.dumps(h, sort_keys=True))
          self.stream.flush()
docs: :param t_input: Translator input.
          :param t_output: Translator output.
          :param t_walltime: Total wall-clock time for translation.