code: def get_token_id_from_tokenizer(
      token_id_name, tokenizer, original_token_id
  ):
      """Use `tokenizer` to get the values of `bos_token_id`, `eos_token_ids`, etc.
  
      The argument `token_id_name` should be a string ending with `_token_id`, and `original_token_id` should be an
      integer that will be return if `tokenizer` has no token corresponding to `token_id_name`.
      """
  
      token_id = original_token_id
  
      if not token_id_name.endswith("_token_id"):
          raise ValueError(
              f"`token_id_name` is {token_id_name}, which doesn't end with `_token_id`!"
          )
  
      token = getattr(
          tokenizer, token_id_name.replace("_token_id", "_token"), None
      )
      if token is not None:
          if isinstance(tokenizer, PreTrainedTokenizerFast):
              token_id = tokenizer._convert_token_to_id_with_added_voc(
                  token
              )
          else:
              token_id = tokenizer._convert_token_to_id(token)
  
      return token_id
  
imports: import argparse
  import collections.abc
  import copy
  import inspect
  import json
  import multiprocessing
  import os
  import shutil
  import tempfile
  import traceback
  from pathlib import Path
  from check_config_docstrings import get_checkpoint_from_config_class
  from datasets import load_dataset
  from get_test_info import get_model_to_tester_mapping, get_tester_classes_for_model
  from huggingface_hub import Repository, create_repo, hf_api, upload_folder
  from transformers import CONFIG_MAPPING, FEATURE_EXTRACTOR_MAPPING, IMAGE_PROCESSOR_MAPPING, PROCESSOR_MAPPING, TOKENIZER_MAPPING, AutoTokenizer, LayoutLMv3TokenizerFast, PreTrainedTokenizer, PreTrainedTokenizerFast, logging
  from transformers.feature_extraction_utils import FeatureExtractionMixin
  from transformers.file_utils import is_tf_available, is_torch_available
  from transformers.image_processing_utils import BaseImageProcessor
  from transformers.models.auto.configuration_auto import AutoConfig, model_type_to_module_name
  from transformers.models.fsmt import configuration_fsmt
  from transformers.processing_utils import ProcessorMixin, transformers_module
  from transformers.tokenization_utils_base import PreTrainedTokenizerBase
label_desc: Use image node_id 14 for calling a global function with example usage: get_token_id_from_tokenizer(token_id_name, tokenizer, original_token_id) and returns: token_id