code: def add_nvs_train_parameters(params):
      params.add_argument(
          "--bow-task-weight",
          type=float_greater_or_equal(0.0),
          default=1.0,
          help="The weight of the auxiliary Bag-of-word (BOW) loss when --neural-vocab-selection is "
          "enabled. Default %(default)s.",
      )
  
      params.add_argument(
          "--bow-task-pos-weight",
          type=float_greater_or_equal(0.0),
          default=10,
          help="The weight of the positive class (the set of words present on the target side) for the "
          "BOW loss when --neural-vocab-selection is set as x * num_negative_class / "
          "num_positive_class where x is the --bow-task-pos-weight. Higher values will bias more "
          "towards recall, resulting in larger vocabularies at test time trading off larger "
          "vocabularies for higher translation quality. Default %(default)s.",
      )
  
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 30 for calling a global function with example usage: add_nvs_train_parameters(params) without return types