code: def get_checkpoint_dir(output_dir, model_arch):
      """Get framework-agnostic architecture name. Used to save all PT/TF/Flax models into the same directory."""
  
      arch_name = model_arch.__name__
      if arch_name.startswith("TF"):
          arch_name = arch_name[2:]
      elif arch_name.startswith("Flax"):
          arch_name = arch_name[4:]
  
      return os.path.join(output_dir, arch_name)
  
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 9 for calling a global function with example usage: get_checkpoint_dir(output_dir, model_arch) and returns: os