code: def use_shared_vocab(args: argparse.Namespace) -> bool:
      """
      True if arguments entail a shared source and target vocabulary.
  
      :param: args: Arguments as returned by argparse.
      """
      weight_tying_type = args.weight_tying_type
      shared_vocab = args.shared_vocab
      if (
          C.WEIGHT_TYING_SRC in weight_tying_type
          and C.WEIGHT_TYING_TRG in weight_tying_type
      ):
          if not shared_vocab:
              logger.info(
                  "A shared source/target vocabulary will be used as weight tying source/target weight tying "
                  "is enabled"
              )
          shared_vocab = True
      return shared_vocab
  
imports: from .None import initial_setup
  import argparse
  import gc
  import logging
  import os
  import shutil
  import sys
  import tempfile
  from typing import Any, cast, Callable, Optional, Dict, List, Tuple, Type
  import torch
  import torch.distributed
  import torch.distributed.elastic.multiprocessing.errors
  from .None import arguments
  from .None import checkpoint_decoder
  from .None import constants
  from .None import convert_deepspeed
  from .None import data_io
  from .None import encoder
  from .None import layers
  from .None import loss
  from .None import lr_scheduler
  from .None import model
  from .None import optimizers
  from .None import training
  from .None import transformer
  from .None import utils
  from .None import vocab
  from .config import Config
  from .log import setup_main_logger
  from .utils import check_condition
label_desc: Use image node_id 7 for calling a global function with example usage: use_shared_vocab(args) and returns: shared_vocab