code: def init_hf_modules():
      """
      Creates the cache directory for modules with an init, and adds it to the Python path.
      """
      # This function has already been executed if HF_MODULES_CACHE already is in the Python path.
      if HF_MODULES_CACHE in sys.path:
          return
  
      sys.path.append(HF_MODULES_CACHE)
      os.makedirs(HF_MODULES_CACHE, exist_ok=True)
      init_path = Path(HF_MODULES_CACHE) / "__init__.py"
      if not init_path.exists():
          init_path.touch()
  
file_path: fastNLP/fastNLP/transformers/torch/models/auto/dynamic.py
imports: import importlib
  import os
  import re
  import shutil
  import sys
  from pathlib import Path
  from typing import Dict, Optional, Union
  from fastNLP.transformers.torch.file_utils import HF_MODULES_CACHE, TRANSFORMERS_DYNAMIC_MODULE_NAME, cached_path, hf_bucket_url, is_offline_mode
  from fastNLP.core.log import logger
label_desc: Use image node_id 1 for calling a global function with example usage: init_hf_modules() without return types