code: def add_score_cli_args(params):
      add_training_data_args(params, required=True)
      add_vocab_args(params)
      add_device_args(params)
      add_batch_args(
          params,
          default_batch_size=56,
          default_batch_type=C.BATCH_TYPE_SENTENCE,
      )
  
      params = params.add_argument_group("Scoring parameters")
  
      params.add_argument(
          "--model",
          "-m",
          required=True,
          help="Model directory containing trained model.",
      )
  
      params.add_argument(
          C.TRAINING_ARG_MAX_SEQ_LEN,
          type=multiple_values(num_values=2, greater_or_equal=1),
          default=None,
          help="Maximum sequence length in tokens."
          'Use "x:x" to specify separate values for src&tgt. Default: Read from model.',
      )
  
      # common params with translate CLI
      add_length_penalty_args(params)
      add_brevity_penalty_args(params)
  
      params.add_argument(
          "--output",
          "-o",
          default=None,
          help="File to write output to. Default: STDOUT.",
      )
  
      params.add_argument(
          "--output-type",
          default=C.OUTPUT_HANDLER_SCORE,
          choices=C.OUTPUT_HANDLERS_SCORING,
          help="Output type. Default: %(default)s.",
      )
  
      params.add_argument(
          "--score-type",
          choices=C.SCORING_TYPE_CHOICES,
          default=C.SCORING_TYPE_DEFAULT,
          help="Score type to output. Default: %(default)s",
      )
      params.add_argument(
          "--softmax-temperature",
          type=float,
          default=None,
          help="Controls peakiness of model predictions. Values < 1.0 produce "
          "peaked predictions, values > 1.0 produce smoothed distributions.",
      )
  
      params.add_argument(
          "--dtype",
          default=None,
          choices=[
              None,
              C.DTYPE_FP32,
              C.DTYPE_FP16,
              C.DTYPE_BF16,
              C.DTYPE_INT8,
          ],
          help="Data type. Default: infers from saved model.",
      )
  
      add_logging_args(params)
  
imports: import argparse
  import os
  import sys
  import types
  from typing import Any, Callable, Dict, List, Tuple, Optional
  import yaml
  from sockeye.utils import smart_open
  from .None import constants
label_desc: Use image node_id 34 for calling a global function with example usage: add_score_cli_args(params) without return types